Tag Archives: Business executives

Earlier, we discussed how analytics with statistics is valuable and beneficial in making business decisions and formulating strategies.

There appears an increasing level of interest among math scientists to work on topics, like machine learning, that are changing people’s lives through its application in business.

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“A topic that is attracting more and more attention is mathematical aspects of machine learning. There are many directions; one that interests me is how I could use some of these exciting new tools in my own research. Another very ambitious and noble goal is to create a mathematical theory of machine learning. When does it fail, and when we can we hope for good results?”

— Maryna Viazovska, 2022 Fields Medal winner, in a Q&A with Nature

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This Veracle is about how the mathematicians’ work is instrumental in pushing the boundaries of making data-driven decisions in business.

Let us begin with a little fun challenge: Take a look at the four knights on the cover picture. Can you exchange the positions of the black and white knights on the given chess board?

If you can, then you may have it in you to win the Fields medal.

What is Fields Medal and how is it relevant to business?

The Fields Medal is the most* prestigious award a mathematician can receive. The International Mathematical Union presents the medal to young math scientists for outstanding contributions in mathematics. The Fields Medal is only awarded every four years.

This year, four mathematicians are the winners of the Fields Medal. They received their awards earlier this month in Helsinki, Finland.

They have earned this distinguished honour for solving or moving closer to solving longstanding “open problems.”

An open problem is a known stated problem which has not yet been solved. It is assumed to have an objective and verifiable solution.

The answers to open problems pave ways for innovative ideas and possibilities. In business context, these answers facilitate, among other things, making business decisions better and faster.

How is their work exciting and significant?

Business decision making has become too complex. Business executives must consider both qualitative and quantitative information to make decisions.

Qualitative information uses subjective judgements. This includes non-quantifiable data such as employee expertise, people attitude towards change, and company culture among other intangible aspects.

However, quantitative information uses data. Now, organisations have too much data available to them. They have data generated by operational transactions, market research, and external sources. Organisations must analyse this exponentially growing data to make decisions. Moreover, they must make many of these decisions in the runtime.

To that end, businesses need more advanced computational algorithms to sift through zettabytes of data to analyse and arrive at useful insights. The conventional techniques are highly time and cost intensive.

This is where work of the Fields Medallists becomes significant.

How does mathematics help business decisions?

This year’s Field Medallists’ works are centred on number theory, probabilistic theory, and combinatorics, among other more intricate topics.

Here are a few examples of business applications of the topics of their work.

Number theory deals with the properties and relationships of numbers.

It has helped in public key cryptography, such as RSA algorithm. This has enabled confidential communications, digital signatures, and secure online transactions for e-commerce companies.

Probability theory is the branch of math concerned with calculating the likelihood of an event. It has numerous applications in business.

From all kinds of risk assessment and modelling (like that for investment and insurance) to sales forecasting, most prediction algorithms use probability theory.

Combinatorics is the study of objects and connections between them. Simply speaking, it has applications wherever we need to arrange things using permutations and combinations.

One can see examples of combinatorics everywhere. It can help in optimising communication networks and logistics. Combinatorics had a crucial role in manufacturing. For example, modular toy manufacturing.

How does it matter to Veravizion?

At Veravizion, we help our clients thoroughly understand their customers. The objective is to devise and implement effective marketing strategies for their business growth.

This involves figuring out our customers’ real target customers, understanding their purchase motivations, performing causal analysis, optimising resource allocations, and in general solving their business problems.

In this process, we apply several techniques such as clustering, regression, optimisation, resource planning, and various other statistical analyses. These are based on pure math and statistical concepts like probability theory, combinatorics, and mathematical optimisation.

Are there any areas of business where you think we can consider using math and statistics?

How else does math help businesses?

* The Abel Prize is also regarded as a top award in mathematics. According to the annual Academic Excellence Survey by ARWU, the Fields Medal is consistently regarded as the top award in the field of mathematics worldwide, and in another survey conducted by IREG in 2013–14, the Fields Medal came closely after the Abel Prize as the second most prestigious international award in mathematics.

Related Posts:

• What are isolated evidence and random variation?
• How can we make difficult decisions?
• Buy, Build, or Get the job done?

<– Is analytics all hype and no substance?

Want to succeed in your venture? Don’t start with planning –>

Cover Photo courtesy: https://en.chessbase.com

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Analytics is the process of discovering, interpreting, and communicating meaningful patterns in data. It helps us make decisions based on data and hard facts.

Most companies now use analytics to make data-driven decisions. They expect that good insights can really take their business to the next level.

Unfortunately, good insights rarely emerge.

Is analytics all hype then?

Here is a startling finding.

Research by PwC and Iron Mountain indicates that three in four businesses extract little or no advantage whatsoever from using analytics. According to the study, 43 percent of companies surveyed “obtain little tangible benefit from their information,” while 23 percent “derive no benefit whatsoever.”

Now, everyone and their uncle is claiming to use analytics in their business. If it was really useful, the world’s GDP have gone through the roof.

So, why are businesses not able to leverage analytics?

This HBR article and the PwC research discuss the root cause. Both studies point to lack of the right capabilities and competencies required to make good use of the information companies have.

This finding really warrants the question. What capabilities and competencies do we need to extract real value from data?

In fewer words, what makes analytics valuable and beneficial?

The answer is STATISTICS.

Statistics makes analytics insightful.

Analytics without statistics is bland, blunt, and bootless. It is like Ron’s broken wand in (the Harry Potter movie) The Chamber of Secrets.

Analytics without statistics, at best, gives us dull observations like ‘focus on the millennials.’ At worst, we get costly and impractical recommendations like ‘redesign the entire supply chain.’

This lack of benefits from analytics leaves businesspeople disappointed.

On the contrary,

Analytics + Statistics = INSIGHTFUL Recommendations

What is meant by insightful?

An analysis is ‘insightful’ when it goes beyond the superficial. It gives an accurate and deep (hitherto unexplored) understanding about the subject. Besides, an insightful analysis helps us break our long-held beliefs and preconceived notions that hold us back.

Here are two diverse examples of insightful findings.

Example 1: who revolves around whom?

The western world during Aristotle’s time (c. 384 B.C. to 322 B.C.) believed that the Sun revolved around the Earth. For 1,000 years, Aristotle’s view of a stationary Earth at the centre of a revolving universe dominated the studies of the universe. Surya Siddhanta and later Copernicus’ work showed that it was the other way round. That ours is a heliocentric solar system in which the Earth and the other planets revolve around the Sun.

That is insightful.

Example 2: how do you shave?

Gillette first entered the Indian market in 1984. But they failed to sell razors despite trying for many years. They even launched their newest triple-blade system in 2004. However, sales were flat for a long time. Why? Gillette did not understand the Indian consumers. They had tested the product with only a few Indian Students at MIT and hence had missed crucial insights about shaving habits in India. A large part of Indian men did not have access to running water and had longer and thicker hair (than Americans). Based on these enlightening insights, they launched Gillette Guard for the Indian market, tasted success for the first time, and never looked back.

Connecting the dots…

So, how does statistics make analytics insightful?

Statistics solves two problems: ‘isolated evidence’ and ‘random variation.’

It does so by employing systematic numerical methods to analyse enormous quantities of data representative of the entire population. Statistics helps us make inferences on the whole population from those in a representative sample. The representative sampling assures that inferences and conclusions can extend from the sample to the overall population.

Ideally, everyone using analytics must incorporate statistical techniques.

But there is one hitch.

In fact, there are three:

• Statistics is complex. If there is one subject which is universally hated, it is statistics. Advanced statistics can get overly complicated. If they must, people use only the descriptive statistics which is easier. They tend to stay away from inferential statistics which is responsible for drawing inferences and conclusions.

• Use of statistics needs expertise. One needs in-depth understanding of statistics to be able to apply it completely and correctly. Moreover, there are different statistical techniques for different data types. One must identify the right techniques to use depending upon the nature and quantity of data available. Many a times, we need to apply statistics in multiple stages (like the Bonferroni correction) to get more accurate results.

• Building expertise takes time and efforts. Naturally, it is costly. It involves having the right people with deep level of knowledge and experience to apply analytics. Most people stop at the basics.

Due to this, it is rare to see use of statistics in analytics. Hence, despite being beneficial for business, useful analytical insights are hard to achieve.

Thus, analytics without statistics is anything but useful. But analytics with statistics is powerful. It delivers meaningful benefits.

That is why, at Veravizion, statistics is the indispensable part of all our analytics and consulting work.

There are several instances where the right kind of analytics (that include statistics) have rendered spectacular results. Analytics is reshaping industries like retail, consumer goods, healthcare, banking, and agriculture, among others. But that is a topic for another Veracle.

What has been your experience of implementing analytics?

Related Posts:

• Most important thing in analytics
• Data Science: The next frontier for business competitiveness (external)
• Analytics in Healthcare: A Veravizion Case Study

<– What are isolated evidence and random variation

Fields Medal, Open Problem, and Business Decisions –>

Cover Photo courtesy: Online stat psu edu

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We know that inferential statistics helps people to make intelligent and accurate conclusions about a greater population based on analysis results of a small sample. Simply put, we can make estimations about populations based on a small sample of people.

One example: if we met a small group of doctors and find that the cardiologists among them earned more than general physicians, we could infer that cardiologists, generally, earned more than physicians.

Another example: In exit polls, the pollsters ask a small group of people at polling stations about who they have voted. Based on their responses, the pollsters make a generalised estimation on who is likely to win from that constituency.

However, there can be two problems in here.

1. Isolated evidence
2. Random variation

Isolated evidence

The problem of isolated evidence happens when we draw inferences based on only a few cases. Such inferences might not be accurate.

Like the above example, if we happen to know only the top cardiologists who earn high salaries, we might be tempted to generalise that all cardiologists earn high salaries. This is because we personally know a few that earn high salaries. Here, we have isolated evidence of only a few known cardiologists that do not represent the entire population of cardiologists.

In case of isolated evidence, we generalise based on known cases. So, there is an element of cognitive bias. Since cognitive biases strongly influence our decisions, we tend to generalise based on these cognitive biases. It influences so much that we look at every evidence in the light of our cognitive biases.

This problem is more likely to occur in the context of personal experiences.

For example, if we do not have a good experience of a certain product (or a service or an institution), we will desist our friend from using it. Ours may be a case of isolated evidence of bad experience with that product (or service or person). Most other people might have had other experiences. In short, our isolated evidence is not enough to conclude whether something is good or bad.

Random variation

The problem of random variation happens when we have insufficient sample data which may not be representative of the population. Here, we are likely to make inaccurate predictions about the entire population based on inadequate data. In such cases, any observed trend is out of randomness.

Random variation is independent of the effects of cognitive and systematic biases. We must aim to collate sufficient data points to nullify the effect of random variation. In general, the larger the sample size, the smaller the effect of random variation on our estimation. As the sample size increases, the random variation decreases, and the estimation accuracy increases.

In the above polling example, the pollsters may survey only a few people from a tiny number of polling stations. The variation thus obtained is more likely to be random than indicative of the entire population.

Don’t they sound the same?

It is easy to confuse between isolated evidence and random variation.

We can even say that isolated evidence is a special case of random variation.

However, there is one key difference.

Isolated evidence is rooted in the form of personal bias. Whereas the random variation comes purely from inadequate sample data.

That is why isolated evidence is more prevalent in people’s personal experiences. So, a friend asking us not to purchase a product is a case of isolated evidence. The star rating of the product on an e-commerce platform is statistical evidence and solves this problem if the rating is given by thousands of unknown people.

So, the next time we are tempted to make a conclusion based on a small sample size, check whether it is statistical evidence, or a case of isolated evidence or random variation.

Related Posts:

• Most Popular Perspectives from 2015
• Two Finals, Two Ties, and the Common Winner
• Fields Medal, Open Problem, and Business Decisions

<– How can we make difficult decisions?

Is analytics all hype and no substance? –>

If you liked reading this article, then please subscribe to our blog – Veracles. That way, you can receive interesting insights in email.

Also, please do follow Veravizion on LinkedIn, Twitter or Facebook to receive easy updates.

We make decisions all the time. Some decisions are easy while others are difficult.

Why are some decisions difficult to make?

It is because they involve a trade-off.

A trade-off is an exchange of something of value for another, usually as a compromise. Simply put, it is a situation that presents us with two or more desirable choices, but we can choose only one.

1. Easy decisions – involve little or no trade-offs
2. Difficult decisions – involve tough trade-offs

Naturally, there is a tension involved where you have to trade-off (or lose) something of value for another.

Consider these examples involving trade-offs.

In healthcare, a patient suffering from seizures is offered the choice of brain surgery or long-term medication. The brain surgery can cure the condition but has low probability of success and may impair some other function like speech or memory. Whereas the medication may or may not be highly effective and cause unintended side effects like excessive drowsiness.

It is a gut-wrenching trade-off.

In career, we want a high-paying job having future growth prospects. But it may require frequent travel to different time zones and odd working hours. The decision involves a trade-off between career and health. Moreover, the job comes with the pain of staying away from family.

Unfortunately, such situations are common in business.

In business, a CEO may need to choose between closing the loss-making plant (and firing hundreds of employees) and attempting a turnaround possibly incurring further losses (and risking the survival of the entire business).

Thus, a trade-off implies an opportunity cost, or a sacrifice, or a pain to gain something. And these things hurt. That is why, decisions involving a trade-off are painful and difficult.

A tough trade-off makes us freeze or flee in the face of tough decisions.

How do we resolve a trade-off?

There is an interesting aspect about how the human psychology works when forced to face a trade-off.

In deciding between two options, we like to choose the higher value option over a lower value alternative.

Likewise, we prefer picking the less risky option over the riskier one. This is because human brain equates uncertainty with danger and causes anxiety. So, it wants us to make such decisions quickly to minimize the anxiety and stress.

In short, both the rational brain (i.e., prefrontal cortex) and the emotional brain (i.e., limbic system) are in action.

In such a situation, the key is to listen to the rational brain.

When forced to face a trade-off, be fiercely rational.

This is easier said that done. Because it is extremely difficult to suppress the limbic brain. Only a well-defined process can help.

That is why, to make difficult decisions, we need a rational decision-making process that:

• gives us the best value option (with higher probability of success),
• is quick and efficient (saving the anxiety and pain), and
• helps us achieve the organisation’s purpose and vision.

In business context, the need for such a methodical decision-making process is vital. The analytics based decision-making process fills this space.

Analytics based decision-making process

This process satisfies all the above criteria:

• It gives us the best value option. Analytics uses tools like classification and decision trees. These tools evaluate a quantitative value for each decision option. We can compare these values to better assess the trade-offs. We can weigh cost and benefits of each decision. Overall, this process helps us choose the best value option.

• It is quick and efficient (and saves from anxiety). Analytics employs proven techniques and frameworks applied on data. These techniques are time-tested and use data as factual inputs. This brings objectivity in the decision-making process. As a result, the process takes away the emotional anxiety and appears unbiased.

• It helps achieve our long-term vision. Most importantly, analytics makes use of statistical algorithms based on probability. This entails assessing each decision with the likelihood of achieving organisational objectives.

Thus, analytics based decision-making process helps in achieving organisational objectives in a facts-based, timely, and efficient manner.

More benefits…

There is an additional yet understated benefit in using analytics for decision making.

The approach helps in communicating and justifying the decision to all the stakeholders. The pyramid principle made popular by Barbara Minto uses analytical reasoning to communicate a decision. It enables managers to get buy-in from the shareholders and employees for successful implementation of decisions.

In sum, analytics helps make, communicate, and justify difficult decisions.

What approach do you take to make important decisions?

Related Posts:

• Buy, Build, or Get the job done?
• Does Your Business Have a Working Strategy?
• Why do Businesses hire Management Consultants?

<– What business are you really in?

What are isolated evidence and random variation –>

Cover Photo courtesy: Vladislav Babienko on unsplash

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Are you a survival-oriented or a growth-oriented executive?

Top executives at any organisation are responsible for growth of the business. Their professional careers grow (only) if their business grows.

The responsibility lies squarely on the chief executive officer. They are in charge to set the strategic direction and align everyone to it to achieve their goals.

However, the chief executive officer role is a complex one to shoulder.

Over the years, the top executive failure rate has varied from 30% to as high as 60% leading to CEO turnover. Significant proportion of this attrition is involuntary. According to The Conference Board, a staggering 30.5 percent CEOs were sacked by their boards in 2019. PwC’s Strategy and CEO Success study puts the lost market value due to this forced attrition at an estimated $112 billion annually.

One reason for this high CEO turnover is failure to deliver desired results in line with stated strategic goals.

These CEOs often have best ivy-league-education and rich execution experience. They have consistently delivered high performance in their previous roles. Yet, they fail in meeting the objectives as CEO.

While there are various reasons behind it, there is one that is less obvious.

The reason has come to the fore more prominently in the current China-virus pandemic.

It is CEOs’ inherent attitude to managing business strategy.

CEOs fall in two categories based on their mindset towards business strategy.

1. Survival-oriented CEOs
2. Growth-oriented CEOs

Survival-oriented CEOs are cost-focused. They believe in maintaining profitability by driving the expenses down. They do not think of investing in growth stimulating actions.

During times of crisis, survival-oriented CEOs follow survive-today-grow-tomorrow principle. They shift focus to short-term. As part of that, they cut costs and downsize operations. These actions help them show good short-term results. But long-term growth prospects of the organisation fall in jeopardy.

Their focus, tactical rather than strategic, can be hope strategy at best.

Being a survival-oriented CEO is justified in some exceptionally challenging situations. This is especially true if the actions are temporary taken just to tide over the crisis.

But this is where it gets counter-intuitive.

A CEO is successful when they achieve long-term results despite the challenges, whatsoever.

On the contrary, Growth-oriented CEOs are revenue-focused. They stay committed to achieving their long-term goals despite the challenges.

The growth-oriented CEOs usually follow a very deliberate strategy to grow. They employ innovation and data-driven strategy for future growth. Most importantly, they commit resources to achieve the business goals while adapting to any changes the challenges may present.

Even during crisis, the growth-oriented CEOs do not lose sight of the strategic goals. They fervently keep long-term outlook. The short-term results may suffer in their tenure, but they are more likely to show good results in the longer term.

Such CEOs spend their time and efforts towards planning and pursuing a working business strategy.

Mr. Bezos is one such CEO. Data science and innovation are hallmarks of his growth strategy. In his words:

“We can’t be in Survival mode. We have to be in Growth mode.”

You can find out your attitude as a chief executive. Take the CEO Genome quiz.

So, have you noticed a survival-oriented or a growth-oriented behaviour recently? What actions did they take that made you think so?

Related Posts:

• Is business strategy really indispensable?
• Can a business still win with a Nope Strategy?
• Online Business Growth – The Easy or The Right Way?

<– Why do Businesses hire Management Consultants?

How E-Retail KPIs different from traditional Retail KPIs? –>

You can also subscribe to our blog – Veracles – to receive interesting articles and insights in email. We would love to read your perspectives and comments on that.

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Cover photo credit: Dietmar Becker on unsplash

To succeed in business and to achieve your professional goals, you need to be able to do two things:

1. Make the right decisions
2. To be able to justify the right decisions to stakeholders to take them forward

Making the right decisions helps because it saves time and money. Besides, it helps you avoid heartburn caused by the consequences of making wrong decisions. This is especially true when there is a lot at stake in that decision.

Nonetheless, making the right decisions is not enough.

It is equally important to be able to justify the right decisions to get buy-in.

Why?

It doesn’t matter if a decision is right if you cannot get buy-in to implement it.

Do all situations require decision-making?

No, not all.

There is no decision to make in a TINA (“There is no alternative”) situation.

However, the decision-making process kicks in when you have two or more options.

Businesses routinely have to make decisions like Buy-Build, Invest-Hold-Divest, or Strategic Transformation-Operational Excellence.

It becomes hard, complex, and stressful, if the options are similar to one another.

Some examples:

• Introduce a new product line or stretch the existing product line.

• Whether your company should invest in improving existing technical capabilities or hiring technical talent from outside.

• Consulting firms in online retail having to decide whether to advise a client to invest more in technology or in physical stores.

Decision-Making

In essence, the decision making process involves the following five aspects – Objectives, Options, Process, Timelines, and Stakeholders:

• Why do you need to make a decision – the objective(s)?
  • Are your objectives clear? Do your objectives align with those of your colleagues or do they contradict?

• What different choices do you have – the options?
  • Have you considered all possible available options for evaluation? Are these options very similar to one another?

• How do you make the decision – the process?
  • Is it opinion-based (aka gut-feel based) or facts-based (aka data-driven)?

• When do you need to make the decision – the timeline?
  • Is your decision-making quick enough or is it time-consuming?

• Who do you need to get the buy-in from – the stakeholders?
  • Can you justify your decision to the stakeholders to get their approval for implementation?

Ideally, businesses must make decisions that are organisation-objective-oriented, facts-based, quick and efficient, and unbiased. Such decisions are invariably optimal for the business.

However, in real-life business situations, decision-making can be tricky:

The objectives of people involved in decision-making may not always align. Thus, they may not arrive at a decision at all.

Personal biases may interfere with business objectives, so the end decision may be unfairly influenced.

The time taken to make a decision may be so long that the particular business situation itself might change in the course of taking the decision, rendering the decision irrelevant.

The subjective process – basing decisions on people’s opinions rather than data – is difficult to justify to get buy-in.

Thus, in reality, businesses tend to make decisions that are subjective, opinion-based, time-consuming, and biased.

Such decisions tend to be highly sub-optimal. They do not invoke the confidence required to invest time, money, and resources to take them forward for implementation.

A decision made in this manner is full of risk and uncertainty.

Guess what?

Risk and Uncertainty are the two things business executives do not like, and want to minimize.

That is why businesses and other organisations look to external management consultants for help in making decisions.

It helps them manage the risk and uncertainty involved in the decision-making process and in the aftermath.

How management consultants help in decision-making?

Management consultants are extremely objective-oriented. They are adept at working with specific details keeping the big-picture in mind, and leaving out extraneous details.

They are highly analytical. It is their job to ensure completeness and correctness of analysis. They apply specialised skills, tools, and techniques designed to analyze different options. Moreover, they leverage their cross-domain expertise acquired from executing similar engagements from the past.

They bring an external, objective perspective. They trust data and facts more than people opinions. Relying on data removes any personal (emotional) bias.

They are particularly sensitive to the urgency of making a decision. They acknowledge that a timely decision is more important than a perfect one*.

Very importantly, management consultants arrive at a decision in an analytical and logical manner. Moreover, they help in explaining and justifying the decision to stakeholders with the help of facts and data.

A decision made in this manner raises the confidence level to commit organizational resources towards its implementation.

This is why businesses and other organizations hire consultants in their decision-making.

How do you make decisions in your business or professional world?

*One important side-note here:

In this aspect, American decision-making differs from German decision-making. In the American business context, external forces like customer request or market need often guide decision-making. So, they think that it is better to make a suboptimal decision quickly, rather than make a better or optimal decision too slow or too late.

On the contrary, Germans believe that the time allotted to a decision should be determined by the nature of the decision. They believe that it is not dictated by external pressures such as customer request or market need or competitor actions. [Source: commentator John Otto Magee on differences in American and German decision-making process]

Author: Sumit Patil

Related Posts:

• Buy, Build, or Get the job done?
• How Deliberate Strategy Can Be the Working Strategy!
• How can we make difficult decisions?

<– How will you measure your business, and life

Are you survival-oriented or a growth-oriented executive? –>

You can also subscribe to our blog – Veracles – to receive interesting articles and insights in email. We would love to read your perspectives and comments on that.

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Cover photo credit: Kan Chana

The day, last Friday, started on a sad note when I read about the untimely demise of Professor Clayton Christensen, author of ‘How will you measure your life”.

He is more popularly known as the author of nine terrific books on Disruptive Innovation, most notable among them being ‘The Innovator’s Dilemma’.

Professor Christensen had conducted a series of management lectures (https://www.youtube.com/watch?reload=9&v=rpkoCZ4vBSI) for our Saïd Business School MBA-cohort in NMLT at Oxford. I had become a fan of him and really wanted to meet him to tell how much I enjoyed his lectures.

However, there was no way I could meet him just-like-that given his stature. Having said that, Oxford is a place where you can get randomly lucky, especially when it comes to meeting important people.

And lucky I got on that day in late-June almost seven-years ago, when I had a chance meeting with him in the lobby of SBS.

I still remember the day vividly, for it was a cherishable moment for me.

I was chatting with Leo, the ever-helpful receptionist at the front-desk, when I saw him coming from ‘The Jam Factory’ side.

I got really excited at the prospect of saying Hello to him.

When he entered the lobby, he appeared to be deeply engrossed in some thoughts. I observed that he was very tall physically too.

Unsure of whether or not to disturb him, I still went up to him and wished him, only half-expecting a reciprocal greeting in return.

To my pleasant surprise, he stopped and smiled at me. I gathered courage, introduced myself, and told him how much I had enjoyed his sessions, particularly the way he narrated the disruption in the steel industry and the concept of ‘getting the job done’.

He thanked me with a smile and asked me what I wanted to do post my MBA. I told him my plans as briefly as I could.

He seemed genuinely interested and further asked me what purpose I wanted to fulfil that will help me achieve success and happiness [from it]. Clearly not ready for such a question, I mumbled something which roughly translated as ‘I will work very hard to…something something’.

On hearing my answer, he gave me one of the kindest smiles I have received.

He then told me this, which were very insightful words for me.

He said, “Success and happiness are two different things.”

“Once the purpose is clear, everything else will follow.”

“First know what will make you truly happy.”

Furthermore, he told me to achieve a balance [in everything].

I thanked him for his advice. After this little conversation, we wished each other well, and he moved on.

That was the last I saw him on the campus.

I was perplexed as to how such a busy and great man still found time to speak with (then) a student like me.

Later, I learnt that he had recently had a non-management book published.

The book was ‘How will you measure your life’.

I found this small 240-page book full of wisdom, for business as well as for life.

It comes from a man who was not just a great management strategist, but a great thinker, philosopher, and a genuine advisor.

Then I found it, there in the book, is written a sentence by him which solved my perplexion.

“I came to understand that while many of us might default to measuring our lives by summary statistics, such as number of people presided over, number of awards, or dollars accumulated in a bank, and so on, the only metrics that will truly matter to my life are the individuals whom I have been able to help, one by one, to become better people…. These are the metrics that matter in measuring my life.”

You indeed have, Professor Clayton Christensen!

Rest in peace!

<– Two Finals, Two Ties, and the Common Winner

Why do Businesses hire Management Consultants? –>

The article “Does your business have a working strategy” mentioned three types of strategies that organizations employ to grow and prosper. The subsequent Veracles discussed the first two – Nope and Hope – strategies.

In this post, we discuss the third type. It is called Deliberate Strategy. It focuses on developing a working strategy for your organization. Here we discuss “How deliberate strategy can be the working strategy for your business.”

What is Deliberate Strategy?

Deliberate Strategy is employed in an organization where business executives are:

• growth-oriented and are looking for new areas of growth, and
• have the risk propensity to commit resources to new approach

In this approach, businesses invest resources to develop a bespoke strategy tailored specifically to their business context.

In other words, businesses take deliberate steps within the context of their business situation to increase the likelihood of achieving long-term goals.

In short, the business outcome is not left to chance. Every aspect of operating and growing the business is deliberately and meticulously planned.

As a matter of fact, it is like a journey one undertakes to reach a destination.

Let us explain the analogy.

A journey has four parts: a starting point, a destination to reach, the route that takes from the starting point to the destination, and the resources required to undertake and complete the journey under any eventuality.

Likewise, developing a deliberate strategy requires an organization to take the following four actions:

1. Understand the current business context.
2. Define business goals.
3. Develop plan to achieve the business goals from the current business situation.
4. Commit resources to achieve the business goals while adapting to any changes.

Let us look at these four steps in more detail.

1. Understand the current business context.

This is the first step. The business executives developing a deliberate strategy need to first develop a complete understanding of the current business context with respect to the external business environment.

Initially, this involves obtaining customer intelligence, acknowledging operational capabilities, understanding product portfolio, acquiring competitor insights, and baselining financial metrics. This step will help you get a sense of your core ideology, financial and operational resources, organization strengths, weaknesses, and problem areas.

Why is understanding the business context important?

Because an organization has to first clearly define a business objective in order to achieve the objective. Here, the business context provides a frame of reference to define appropriate business objectives. For example, a firm with annual sales of $10million grappling with scale-up challenges cannot directly aim to become a $1billion organization.

Moreover, the business context serves as the baseline against which the firm can measure and compare the progress.

2. Define business goals.

Now, organizational purpose and vision are the guiding light for business executives defining business goals. The organizational vision will not be achieved if the goals are unclear. Therefore, it is necessary that business goals are clearly defined. Doing so helps the executives to communicate them unambiguously to all layers of the organization.

A well-defined business goal adheres to the QTR [read: Quarter] principle:

• Quantitative – firstly, it has to be measurable
• Timebound – secondly, it has to have a definite time frame within which to achieve it
• Reasonable – and it should realistic, even if difficult, to achieve in the given time frame

To illustrate, here are some examples of some meaningful business goals (set by real-life firms):

• Grow annual revenues to $865 million at a CAGR of 20% within three years
• Conquer 5% more market share in our target market by the end of the year
• Reduce operational costs to realize 15% profitability YoY within two years

At this point, a QTR-based business goal establishes the destination for a business to reach within a stipulated time.

3. Develop plan to acheive the business goals.

This is the third important step. Once the business goal is defined, the CEO and the top management need to put together a route to that end. Here, a customer-centric plan acts as the route.

This step is especially crucial to developing a deliberate strategy. In fact, this is where a Deliberate Strategy differs from a Hope strategy (or any other best practices strategy).

A Hope strategy is forward-designed and forward-implemented.

Whereas, a Deliberate Strategy is backward-designed but forward-implemented.

Let me explain.

A Hope strategy involves employing strategies and best practices that have worked for other businesses. Naturally, these strategies are picked up by an organization and customized for their use and implemented to reach the business goals. Thus, it follows a forward path.

On the contrary, a Deliberate Strategy starts from the end-point, i.e. the business goals. Mainly, it involves figuring out what is required to reach that state and then coming backward by designing a slew of bespoke actions to reach that state. This is how it is backward-designed.

This is the key difference between the two.

4. Commit resources to achieve the business goals while adapting to any changes.

This is the final step. Once the plan is defined and the business strategy is rolled out, the organization commits to the implementation journey along the strategic route.

As we know, a business strategy for an organization exists within the context of its current business situation. However, the business situation is part of the larger business environment. It generally includes the market (which buys) and the industry (which sells) among other stakeholders, like suppliers, regulators, government, and technology.

Meanwhile, the business environment is constantly changing.

Buyers (or customers), sellers (or competitors) and suppliers keep entering and leaving the business environment, like new passengers en route your journey.

Like you, your competitors are also persistently working on their own strategies to grow and capture market share.

Additionally, governments keep looking for newer ways to tax businesses. Also, the regulators are bringing new regulations to safeguard fair competition. Similarly, technological advancements are disrupting the way of doing business.

On the whole, the business environment is continually changing.

Therefore, it is imperative to keep looking for any changes that risk the execution of your bespoke strategy. Accordingly, the business needs to keep collecting data points and reviewing its strategy at regular intervals to ensure that the journey is on the right track.

To sum up, these are the actions that make for a working strategy.

How Veravizion implements Deliberate Strategy?

At Veravizion, we have developed our own framework that we call contextual problem solving with deliberate strategy. This framework facilitates the development of deliberate strategy using a Context-Drivers-Solution-Impact cycle. Also, it applies to any business across industries.

There are many companies that have employed Deliberate Strategies in the past to grow predictably. In particular, 3M, Amazon, Apple, Boeing, Google, Nike, Nordstrom, Procter & Gamble, are a few examples.

While reading the names of these well-known companies, it is easy to think that deliberate strategy works only for the big ones.

However, it is not so.

In reality, most of these companies were virtually a nobody BEFORE implementing deliberate strategies.

3M were miners. Their earlier venture, started in 1902, to mine corundum failed. In the past, 3M also tried their hands at other things like making sandpaper. They failed less, yet did not succeed like success.

Later, they chose to embrace “innovation and collaboration” as their Deliberate strategy. Today, 3M is known as the world’s most innovative company.

More Examples of Deliberate Strategy…

Here is an interesting example from “Built to Last”, the bestselling book by Jim Collin and Jerry Porras.

Boeing, until 1952, had been building aircraft primarily for the military. They had virtually no presence in the commercial aircraft market. Moreover, Boeing relied heavily on orders from their only major client – the U.S. Air Force – to survive. In short, nobody knew Boeing. Back then, their competitors Douglas Aircraft dominated and ruled the commercial market with their propeller-driven planes. While Boeing wanted to enter the commercial market with a big, fast, advanced, and better-performing aircraft.

If Boeing had followed the Nope strategy, we would never have known of them.

If Boeing had followed Hope strategy, they would have probably leveraged the competitor strategies of the time and would have built a better propeller plane at best.

Instead, Boeing embraced a Deliberate Strategy.

Boeing’s purpose and vision were to be on the leading edge of aeronautics pioneering aviation. Taking inspiration from there, Boeing announced their goal to make a jet plane for the commercial market. No other aircraft company had done that before them. Moreover, such a project was going to cost them about three times their average annual after-tax profit – roughly a quarter of their entire corporate net worth – to develop a prototype for the jet. But Boeing committed to it. Later, the strategy resulted in such fine planes as 707, 727, 737, 747, and 777. Douglas aircraft could never quite catch up to Boeing. Douglas struggled to survive by merging with McDonnell aircraft in 1967. Eventually, Boeing acquired McDonnell Douglas in 1997.

Apple is a more recent example of a business that became successful by devising and implementing a Deliberate Strategy. Apple believes in “breaking the status-quo”.

The strategy helped them differentiate in the crowded smartphone market and create an enviable position for them. As a result, Apple was the most valuable brand in the world for eight straight years.

To sum it up with key insights…

Deliberate Strategy helps an organization achieve its business objectives in a decisive and predictable manner.

The predictability comes only by acting deliberately.

The whole process is highly intentional, methodical, and purposeful.

And Deliberate Strategy is universal. The above framework would still work if you replace an organization with an individual or an institution.

There are many examples of successful implementation of deliberate strategy in all spheres of life.

Deliberate strategy is the difference between many successes and failures.

An organization’s strategy is its source of sustainable competitive advantage. Should one squander it away by following someone else’s strategy? What do you think?

Related Posts:

• Analytics in Healthcare: A Veravizion Case Study
• Does Your Business Have a Working Strategy?
• Customer-centric Sales is the New Competitive Advantage

<– Can Hope be a Real Business Strategy?

Two Finals, Two Ties, and the Common Winner –>

You can also subscribe to our blog – Veracles – to receive interesting articles and insights in email. We would love to read your perspectives and comments on that.

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Cover photo credit: Brad Wetzler

Other photos: 3M.com, Boeing.com, Apple.com

The last Veracle was third of the six on business strategy. It tried to answer whether a business can still win with no strategy. While there are businesses that do not employ any strategy, one can witness more businesses following hope as a strategy. The hope strategy looks like this – let us take these actions that similar businesses take, and hopefully, we will achieve our objectives. So, the perplexing question here is – Can HOPE be a real business strategy?

What is Hope Strategy?

Hope strategy is one where businesses do a lot of the same activities in the hope that it will help them grow.

Hope strategy is most frequently observed in businesses where:

• business executives are keen for the positive growth outcome,
• but are not inclined to commit resources required for it.

Now, this seems counter-intuitive.

When a business executive is keen to grow a business, they would naturally want to invest resources to grow, right?! Not quite.

Ideally, business executives have two options to grow their business:

1. Invest resources to develop a bespoke strategy tailored to their business context and implement it meticulously.
2. Employ ideas, strategies, and best practices implemented before them by similar businesses in their industry.

The first option mentioned above is to develop a bespoke strategy. That is, this is Deliberate Strategy for your business. This option may appear costlier, at least in the short term, as it involves investing resources in designing a new strategy from scratch. But it isn’t. We will discuss this option later in the next Veracle.

The second option, which involves employing ideas, strategies, and best practices of similar businesses, appears to provide a proven path to progress in the short term.

Ironically, many businesses tend to take the second option out of the misplaced belief that the strategies that have worked for other businesses will work for theirs too. It is far too common to hear, “it has worked for them, why won’t it work for us?”

This belief is the basis for the hope strategy.

However, the problem is that the second option does not sound wrong.

Let us recall “the ship’s voyage” metaphor (cited in the previous Veracle) where we had likened a business to a ship sailing on a voyage to its destination.

The second option is akin to setting the course of a ship by looking at the lights of passing ships. In ship lore, this is a terrible blunder.

Likewise, setting the strategic direction of a business by looking at the strategies employed by similar businesses is a huge mistake.

That is why the second option is deceptive.

In short, what may have worked for other businesses, may not work for yours. This is because the business contexts are very different.

This is the key insight.

How to recognize Hope Strategy?

Businesses following a hope strategy exhibit three symptoms:

1. Lack of clarity about self-identity
2. Frequent change in the strategic direction. Taking actions on whims.
3. Business running in a perpetual reactive fire-fighting mode

When a business has not developed a bespoke strategy of their own, they tend to adopt the strategies and best practices from the leading companies in their industry. In the worse cases, they adopt spur-of-the-moment ideas as strategies.

As a result, there is stress on doing a lot of those things and doing them right. There are too many initiatives and employees are working on too many pursuits simultaneously (without conviction).

Eventually, this approach causes them to lose their core identity over time.

While the business itself might be operating successfully, pursuing too many things causes frequent changes in direction.

Such a business might continue operating until the time it is able to innovate and satiate customer demands. However, the lack of a strategic direction coupled with any external challenges triggers the inevitable declining spiral.

Sony and Yahoo, are two of the many examples of businesses following hope strategy and declining.

Sony, with its miniaturization strategy, was at the top of the music industry before the digital era began. Digitalization happened in the early 2000s and there was a new trend of (illegally) downloading music online. Despite having the technology to launch a product for digital music, Sony did not invest in it. Sony only hoped that the trend would go away, eventually letting their music products business getting doomed.

Let us discuss Yahoo! in more detail.

Yahoo! is another case of how a pioneering business floundered in just hoping that some strategy would emerge.

InitiallYahoo! started in 1994 as a one stop shop web portal where it brought together news and other online services helping users navigate the internet. So, in a way, it was a gateway to the internet for most users of the time.

Exhibit 1 shows Yahoo homepage of 1994 when it was launched.

During late 1990s (and early 2000s), it was an undisputed leader of the web with its email, online search and news. The company not only survived the dot com crash of 2000, its sales climbed multi-fold between 2001 and 2008 (as shown by the share price rise in Exhibit 2).

In early 2008, Microsoft intended to acquire Yahoo for $44.6 billion, an offer Yahoo formally rejected citing shareholder’s interest. Eventually, Verizon acquired Yahoo, once worth almost $125 billion, for $4.8 billion, underscoring the company’s fall.

So, what went wrong? How does a good company like Yahoo fail so miserably?

Numerous reasons have been put forth to explain Yahoo’s failure. Here are some of the prominent ones:

• Yahoo was jack of all trades, master of none. They tried to do many things – Yahoo Search, Yahoo Finance, Yahoo Mail, Yahoo Messenger, Yahoo News, and Yahoo Sports among others – but didn’t focus on being best in one.
• Yahoo remained the same portal it was a decade ago and did not innovate.
• Yahoo was late to mobile, according to a senior editor at Harvard business review
• They did not focus on hiring the right talent; Yahoo apparently short-changed engineering, and media people were viewed more important, according to an EECS professor at Michigan.
• Yahoo failed as Marissa Mayer could not perform the turnaround.

All these reasons seem right. And, it is easy to blame Marissa Mayer, who was at the helm from 2012 to 2017, for the ultimate decline.

But the real reason goes much deeper, and much earlier than that.

A close observation of the above five points reveal that these are symptoms of one common underlying cause: While doing so many things, Yahoo kept praying that something will work, some strategy will emerge, and they will survive.

The above conclusion may sound too simplistic, almost frivolous.

However, lack of a clear explicit strategy explains all the above symptoms.

Issue with Self-Identity

Yahoo started as a web portal and generated most of its revenue from selling advertising on the different service platforms it created. The key Yahoo services became so popular at one time that they started treating themselves as a media company, rather than a technology company.

There was a lack of clarity about self-identity.

So, the focus of hiring and talent retention philosophy kept shifting from engineering to media. As a result, Yahoo failed to innovate and remained the same portal even after a decade. Meanwhile, Google and Facebook hired top engineers (doing core programming) and leapfrogged Yahoo with better sleeker products. Gmail beat Yahoo Mail, Google Search outperformed Yahoo Search, and WhatsApp surpassed Yahoo Messenger impacting Yahoo sales.

As a company strategy, Yahoo started taking mobile seriously only after 2012, whereas other competing businesses already had an operational mobile strategy by then. Google’s Eric Schmidt mentioned mobile as one of their strategic areas in as early as 2006.

What about Strategic Direction?

The lack of strategic direction is evident considering Yahoo saw 8 CEOs in 20 years, and 6 CEOs within just 4 years. Founder and CEO Jerry Yang stepped down in December 2008 citing conflict of opinion in terms of strategic direction. His successor, Carol Bartz, openly admitted that she also grappled with the question of what Yahoo is, when she took over in 2009.

The acutest confirmation of lack of explicit strategy came during Marissa Mayer tenure when she spent over $2 billion binge acquiring 53 mobile-based companies, none of them really successful. Check out Exhibit-3 to see if you can identify some of them.

In summary, it can be said that Yahoo! grappled with a clear explicit strategy for a very long time. Over the years, the CEOs just pursued what seemed right at the time hoping that some strategy would emerge. In the end, the hope strategy did them in.

Having said thus, it is appropriate to add here that it is very convenient to retrospectively dissect businesses and tell what went wrong. Wouldn’t it be more useful (for you and your business) if you knew the right way to define strategy, and more importantly, be able to tell whether it is going well? The next two Veracles attempt to do just that.

Related Posts:

• Does Your Business Have a Working Strategy?
• Are you survival-oriented or a growth-oriented executive?
• Online Business Growth – The Easy or The Right Way?

<– Can a business still win with a Nope Strategy?

How Deliberate Strategy Can Be the Working Strategy! –>

You can also subscribe to our blog – Veracles – to receive interesting articles and insights in email. We would love to read your perspectives and comments on that.

Do follow Veravizion on LinkedIn, Twitter or Facebook to receive easy updates.

Cover photo credit: hbu.edu

The Nope Strategy is first of the three types discussed in the previous Veracle titled “Does your business have a working strategy”. It raises a pertinent question, “Can a business still win with a Nope Strategy?”

To give you a quick recap, we read that a business suffers with Nope Strategy when its business-executives:

• do not want to lose the status quo, so they just want to protect their turf rather than look for new areas of predictable growth, and
• do not commit any resources for new growth strategy

What happens at a business that has no growth strategy?

Three things ensue –

When a business has no clear strategy, it does not have a specific direction to pursue nor a plan to communicate to its employees.

In such a scenario, the employees do not feel connected by any common long-term objective (even if there is one). Employees tend to work in a silo and perform their tasks on a tactical day-to-day level.

Gradually, the organisation loses track of what customers want. As the business lacks any formal strategy, it is not able to cope when there is an external change (in the micro- or macro-economic environment) like change in customer buying preferences or a change in technology.

When that happens at a company having Nope Strategy, the change triggers the downfall and eventual close-down of the business.

Let me explain this situation with “the ship’s voyage” metaphor.

When a ship sets sail on a voyage, its port of destination is known. And, the captain must work out and navigate the right route to reach the port of destination.

Similarly, a business operates with an aim to achieve certain objective. And, the business executives must design and implement the right strategy to achieve the objective.

A ship must keep sailing along the planned route to reach its port of destination. A ship without a planned route slowly strays eventually losing steam, stalls, and sinks.

Likewise, a business must keep operating with the right strategy to achieve its objectives. A business without a strategy eventually runs out of resources, falters, and fails.

Unfortunately, there are many examples of once brilliant businesses failing and going bankrupt because of having no credible strategy.

Some Examples

“that’s cute – but don’t tell anyone about it.”

That was the Kodak management’s reaction when their engineer invented the first digital camera. Yes, Kodak invented the first digital camera. However, it was predominantly a film-based business. The management did not see the need for any growth strategy nor did they invest any resources in it. They were insistent on protecting their film-based business. Even when customers started dumping film for digital cameras, Kodak refused to have any strategy to tackle the change, and eventually went bankrupt in 2012.

Similarly, Hitachi, and Macy’s had no credible digital strategy, so when the digital revolution happened, these once immensely popular brands lost their way.

Sears was a huge success running its chain of general departmental stores. However, when Walmart and Kmart made the large retail stores popular, Sears had no strategy to adapt to the change, and faltered.

How Nokia killed Nokia?

Let us take a deeper look into an example of a well-known business that hardly had a strategy when faced with a market change.

In October 1998, Nokia became the best-selling mobile phone brand on the planet. As shown in Exhibit 1, Nokia’s operating profits steadily rose (along with its share price) from 1995 to 2000. During the early years of the millennium, early smartphones started crowding the mobile market, which somewhat hit the Nokia share price. Nevertheless, the share price kept rising with the popularity of Symbian-OS.

Until 2007, Nokia’s Symbian-OS was the undisputed market leader with 60% smartphone market share (see Exhibit 2).

What happened after that is interesting!

On June 29^th, 2007, Apple launched iPhone, and in mid-2008, Google partnered with other smartphone manufacturers to capture the smartphones market via Android-OS.

This was the start of the steady decline for Nokia smartphones.

As shown in Exhibit-3, Android (in rising blue line) was grabbing the smartphones market so far dominated by Nokia (in declining yellow line). Over the next few years, Nokia witnessed one of the most painful declines in business history. While this was happening, Nokia hardly had any strategy to stem the fall (even considering the launch of Nokia N97, dubbed the iPhone killer).

Nokia just appears to be at a loss about its strategy.

The downfall and eventual demise of Nokia’s smartphone business (in 2013) lies in the fact that they did not have any strategy to counter the onslaught of newer smartphones.

This observation is echoed by Dr. Yves Doz, INSEAD Emeritus Professor of Strategic Management, in his book Ringtone: Exploring the Rise and Fall of Nokia in Mobile Phones. The reasons mentioned in the book allude to an absence of a unified growth strategy and deterioration of strategic thinking within Nokia management.

According to Dr. Doz, Nokia was in strategic stasis that was visible in symptoms such as dysfunctional organisational structure, growing bureaucracy, and management infighting.

This implies that a business cannot survive for long without a strategy.

Does this mean, then, that a business is likely to do well, as long as it is able to “keep sailing the ship in some direction?”. This will be discussed in the next Veracle on “Hope Strategy”.

Related Posts:

• How Deliberate Strategy Can Be the Working Strategy!
• Online Business Growth – The Easy or The Right Way?
• Want to succeed in your venture? Don’t start with planning

<– Does Your Business Have a Working Strategy?

Can Hope be a Real Business Strategy? –>

You can also subscribe to our blog – Veracles – to receive interesting articles and insights in email. We would love to read your perspectives and comments on that.

Do follow Veravizion on LinkedIn, Twitter or Facebook to receive easy updates.

Cover photo credit: tracy morgan on Unsplash

The previous Veracle discussed whether strategy is really indispensable for businesses. It ends with a few reflective questions for business people.

One of the questions relates to the types of strategies adopted by businesses. No, it does not refer to the cost-based, differentiation-based stuff. It refers to types of strategies at a more fundamental, and practical, level.

The question asks whether your business has a working strategy.

What is a working strategy?

We know that a strategy is a plan of action designed to achieve long-term goals.

A working strategy is a plan of action that incorporates the components essential to achieve the goals.

Before we discuss components of a working strategy, let us first understand the strategies businesses typically employ.

A close observation of businesses reveals interesting insights about the strategies they use to operate and grow.

Such strategies classify into three types.

1. Nope Strategy
2. Hope Strategy
3. Deliberate Strategy

The names given to these strategies might sound ludicrous, but the underlying phenomena are visible all around us.

The first two approaches in the list above are examples of what not to do. Yet, this is what many businesses still do.

The third approach focuses on developing a working strategy. This is the strategy successful businesses implement.

The three types of strategies are different based on the attitudes of executives running the businesses. The difference comes from two factors. First, “the need for predictability of positive outcome”, and second, “the risk propensity to commit resources to grow”.

The need for predictability of positive outcomes

The need for predictability of positive outcomes means whether the executives are keen to consciously make the growth happen, rather than leaving it to uncertainty in the face of a constantly changing business environment.

In simple words, executives’ need for predictability of positive outcomes is high when they are growth-oriented and cannot tolerate uncertainty for long. And executives’ need for predictability of positive outcomes is low when they are cost-saving oriented and are afraid to lose what they currently have.

For instance, Kodak is an example where the top management was cost-saving oriented. They were afraid to lose their film business and so, were reluctant to look beyond film for future growth areas.

The risk propensity to commit resources

The risk propensity to commit resources for growth means the willingness of business executives to expend resources – energy, money, and efforts – to consciously make the growth happen.

To illustrate, Xerox and Sony help us explain this phenomenon.

Xerox was actually the first company to invent the PC. Surprised? But, it is true.

Yet, they did not commit resources to its advancement thereby losing the market share to Apple. Smith and Alexander even wrote a book about Xerox called: “Fumbling the Future: How Xerox Invented, then Ignored, the First Personal Computer.”

On similar lines, Sony actually had the technology to launch a product even better than the iPod. But the executives were too afraid to commit resources to test out something new, eventually losing to – guess who? Apple again.

So, how do these two factors influence Nope, Hope, and Deliberate Strategies?

“Nope strategy” is one where business executives have an operational business but have no real working strategy to grow the business. The business executives are oriented towards protecting what they already have, rather than creating new areas of strategic growth.

Nokia and Kodak are two prominent examples of companies failing to Nope Strategy.

Nokia is discussed at length in the next Veracle.

In the “Hope strategy” approach, business executives are keen on the positive growth outcome but are not inclined to commit the resources required for it. The executives operate the business by doing a lot of the same things. The business has some inexplicit approach that is rooted in the belief that if a business follows the industry best practices and adopts the prevalent marketing trends, it should grow.

On probing them, one hears an implicit hope that a working strategy will somehow emerge from the many best practices followed.

Hope strategy is a bit tricky because it does not sound wrong. Here, the business outcome is unpredictable because it varies based on many environmental factors.

What about Deliberate Strategy?

“Deliberate strategy”, on the other hand, is interesting. Here, an organization devises a plan of action that includes the components of a working strategy. This is to make it work in the context of its environment. It includes defining a specific business objective that is both measurable and achievable. Thereafter, the business develops a deliberate plan that serves as a working strategy to achieve that business objective.

Apple’s growth over the last decade is evidence of how deliberate strategy succeeds. Amazon is another example of a firm growing in this manner.

At Veravizion, we believe in employing a deliberate strategy to help our clients define and achieve their business objectives. Businesses have too many resources at stake to not employ a strategy that truly works.

Circling back to working strategy…

A working strategy, then, is one that assists an organization to achieve its business objectives in a predictable manner.

Predictability is the key.

That is why deliberate strategy is important!

In the next three Veracles, we will dig deeper to understand the attributes of each type of the strategies. We will discuss these with examples to find out the strategy that works.

Related Posts:

• Strategic Transformation Part-1
• What does Digital Maturity really mean
• Are you survival-oriented or a growth-oriented executive?

<– Is business strategy really indispensable?

Can a business still win with a Nope Strategy? –>

You can also subscribe to our blog – Veracles – to receive interesting articles and insights in email. We would love to read your perspectives and comments on that.

Do follow Veravizion on LinkedIn, Twitter or Facebook to receive easy updates.

Cover photo credit: photo by ricardo frantz on Unsplash

Why do I need a business strategy?

Recently, the chief executive of a retail business asked me this question. Let us first understand what strategy is!

In simple words, strategy is a plan of action designed to achieve long-term goals.

People apply strategy in many different contexts. For instance, military, sports, and business are some areas where strategy is necessary to win.

In the military, strategy is essential to win a war. It allows armed forces to plan military operations – offensive and defensive – in order to gain battlefield advantage over enemies, and achieve goals of national (and global) security.

In sports, strategy is essential to win a game. It allows sportspersons to devise a game-plan in order to gain an on-field advantage over rival teams, and win a match.

In business, strategy is essential to be profitable and grow over the long term. It allows organizations to develop business models and design operational processes in order to gain a competitive advantage, and achieve goals of financial security.

Coming back to the question then, is business strategy really indispensable?

For a moment, let us hypothesize about situations when strategy may not be important.

What if you are the general of an army having limitless troops and tanks? Or, the coach of a sports team having boundless talent and practice hours? Or, the CEO of a business having unlimited resources?

These situations might tempt us into thinking that one can easily trump the opponent without needing a strategy if one has unlimited resources.

In reality, organizations always have limited resources.

Even if organizations have resources in huge numbers, they are always finite in quantity.

Military organizations have a finite number of soldiers, shooting weapons, and shells.

Sports teams have a finite number of players, play paraphernalia, and practice periods.

Business firms have a finite number of competencies, capacities, and capital.

So, when you have something in a limited amount, what do you do? You find ways and mechanisms to use it judiciously such that you achieve your objective before expending the resources entirely.

Strategy is that mechanism!

In short, Strategy is important because resources are always finite!

To clarify, here is an interesting way to look at it.

The right strategy assists you in allocating your finite resources in such a way that you can build a competitive advantage against your rivals of any size, and can still win.

There is a gem of insight in that last sentence in case you missed it.

Strategy is the concept that helps you use your resources wisely and effectively. It allows you to prudently allocate your resources where they can deliver the maximum possible returns.

Some Examples

There are numerous examples in the military, sports, and business where a smaller team has implemented the right strategy to beat a disproportionately larger opponent.

History books are replete with instances of battles where a very small army has defeated a large one by employing strategic maneuvers. The battle of Longewala, the battle at Rezang La, Napolean’s 1812 invasion of Russia, and the 1775 battle of Lexington and Concord in Massachusetts are few such examples.

Sports archives are awash with games won by employing a tangible strategy; such games were called the biggest upsets of the time as a strategy was a late entrant in the world of sports as compared to some of the other fields. Here are three examples:

In the final of 1950 world cup football, Uruguay beat Brazil by keeping the game simple, focused, and warlike. Brazil was the hot favourites to win the game. Uruguay team was under no pressure and their captain asked the team to play a no-holds-barred natural attacking game, which they did.

In the final of the 1983 ICC world cup, the underdogs India beat consecutive three-time finalists (and two-time champions) West Indies by playing to the team’s strength of disciplined bowling.

One of the best examples of strategy winning a sports match is the “Miracle on Ice” game during the men’s ice hockey tournament at the 1980 Winter Olympics in Lake Placid, New York. In this medal-round game, the United States team consisting exclusively of amateur players (but following military-style discipline) beat the four-time defending gold medallists the Soviet Union that consisted primarily of professional players.

Examples from Business World

The business world is full of case studies of businesses devising deliberate strategies, developing sustainable competitive advantage, and capturing significant market share on their road to business growth. Here are two examples of businesses winning on strategy:

Blockbuster was founded in 1985 as a video (VHS) rental company. Within 15 years, it had 6,500 video rental stores around the US and revenues upwards of $5 billion. Netflix began operations in 1999 and led its strategy based on people’s video-watching preferences. Netflix devised a highly customer-centric strategy that included subscription-based charges and no late fees, among other things. As a result, customers could watch a video for as long as they wanted or return it and get a new one. By end of 2010, blockbuster was bankrupt while Netflix, on the back of its deliberate customer-centric strategy, is worth more than $150 billion today.

In the late 1980s, the sales of carbonated soft drinks were at a high. It would be foolish to introduce yet another drink in the fiercely competitive market. Yet, Austrian entrepreneur Dietrich Mateschitz partnered with a Thai businessman Chaleo Yoovidhya to introduce a new drink named Red Bull. Predictably, sales were (s)low during the initial years. That’s when the co-founder defined a strategy sharply focused on a chosen market segment. To that effect, Red Bull was positioned as an energy drink for students and adventure enthusiasts. The strategy would eventually help the business increase annual sales to 6.79 billion cans in 2018. As a result, Mateschitz became the 31st richest person in the world.

These and many such examples signify that strategy is extremely important because organizations are invariably resource-constrained.

So what?

On this note, some meaningful follow-up questions to ask would be: Is any strategy good enough? Does your business have a working strategy? Are you able to explain it clearly?

Related Posts:

• Strategic Transformation Part-2
• Why your Business should go Digital?
• How Deliberate Strategy Can Be the Working Strategy!

<– Top Analytics Trends 2017 – An INFOGRAPHIC

Does Your Business Have a Working Strategy? –>

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Cover photo credit: photo by rawpixel on Unsplash.

Here are the top analytics trends 2017 for businesses based on what industry and our clients are saying.

These trends reveal a pattern similar to the one observed last year. Embedded BI facilitates the analytics of everything on demand. Moreover, application of IoT devices continues to increase rapidly. Gartner estimates that 20.8 billion connected things will be in use worldwide by 2020.

While analytics, IoT and their applications in business continue to permeate deeper, artificial intelligence (AI) and machine learning (ML) is gaining further attention.

Artificial Intelligence and Machine learning is also the number 1 among the 2017 strategic technology trends report published by Gartner.

Until a few years back, mid-size organizations hardly considered AI as a possible solution to any of their problems. However, the pressure on margins due to increasing competitiveness fueled by online players is making it imperative for all businesses, big and small, to be more efficient.

Besides analytics, IOT, and AI, there is one interesting trend that silently continues to grow and intensify because of how human beings are evolving – the urgent need for clear, relevant, and crisp visualization of data.

According to a research by scientists, human attention span is shrinking so much that even a goldfish can hold a thought for longer. The study by Microsoft says that average human attention span has fallen from 12 seconds in 2000, (or around the time the mobile revolution began), to 8.25 seconds in 2015.

While the comparison with the attention span of goldfish is debatable, the underlying insight – that humans are less attentive than ever before – hardly is. Powerful visualization of information remains the key.

Another trend catching the attention of businesses is the use of predictive analytics. In today’s uncertain business environment, companies want the ability to forecast future business performance based on the past. Predictive analytics tries to answer questions such as: What is likely to happen tomorrow? How can we make the business improve? Consequently, predictive and prescriptive analytics are among the most discussed analytics trends among the professionals.

In summary, smart businesses are recognizing the contribution of analytics (and the associated technologies) in their ongoing success. The top analytics trends 2017 continue to reflect this new reality. Unfortunately, Business analytics talent is scarce. Companies are struggling to hire (and afford) the right people that will help them realize the true benefits of analytics. This makes it ever-more critical to engage with partners that will bring on-board the right combination of computing know-how, analytical and visualization skills, and business acumen.

So, here are the top analytics trends 2017 at a glance. Do read-on, review and respond.

Download PDF of Analytics top trends 2017

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Like last year, we bring to you top analytics trends 2016 for SMBs. These trends are based on what industry stalwarts and our clients are saying.

A quick comparison with last year’s trends reveals that some trends continue to evolve. Topics like Deep learning, Self-service-BI, or Cognitive computing are some latest ones being discussed. Nonetheless, others are rapidly gravitating towards some common theme.

One such theme is ‘Big Data Analytics’. More and more small and medium-sized businesses (SMBs in short) are going digital. They are embracing analytics and leveraging their data to turn insights into higher revenues, reduced costs, and overall business growth. According to analysts, the big data analytics market is expected to reach nearly $50B by 2019.

Our Trends focus on the applicability of these technologies to small and medium business (SMB) organizations. As we know, technology plays a vital role in running a business successfully. Yet, some of these emerging technologies are not immediately relevant to SMBs. While it can be helpful to develop an awareness of these technologies, very few SMBs are actually going to use them. For example, the uses of 3D printing or AI in 2016.

This year, we have identified nine top analytics trends that are most relevant to SMBs.

1. More SMBs use analytics for business benefits.

Until a few years back, big data (analytics) was more hype than reality. Google was awash with searches involving keywords centered on ‘Big Data’. However, over the last couple of years, analytics has left the hype curve to provide real value. Today, analytics is everywhere.

Earlier, SMBs were not too savvy about maintaining the data of their customers, product orders, and suppliers. This was largely because of the costs involved in the data storage without the apparent benefit of maintaining the data. However, with the data explosion through various media over the last couple of years and with the availability of custom-analytics providers, they woke to the possibility of utilizing their data for getting answers to some key questions around their businesses. As the benefits started becoming visible – in terms of exponential business growth in a few cases – SMBs started focusing on analytics and become more data-driven to improve their business results.

However, making this data meaningful and easy to understand is still a challenge for many. We think that 2016 will be the year that small-scale analytics will really take off for SMBs, as it allows them to leverage their data from disparate data sources for their business benefits.

2. Internet of Things (IoT) enters our daily lives.

This is what Nikola Tesla said in a 1926 interview with Colliers magazine:

“When wireless is perfectly applied the whole earth will be converted into a huge brain, which in fact it is, all things being particles of a real and rhythmic whole… and the instruments through which we shall be able to do this will be amazingly simple compared with our present telephone. A man will be able to carry one in his vest pocket.“

How it has become a reality less than a century later!

The Internet of Things (IoT) in its current form proliferated with the surge in low cost sensors embedded with Bluetooth wireless capability onto a small chip. And it is rapidly evolving from the realm of fascinating gizmos to real-world utility gadgets. Many leading companies such as Google, Amazon, Cisco, Dell, and TI have developed their versions of IoT products. There are already some cool IoT devices like Nest, Fitbit, and Belkin, to name just a few, that are vying for consumers’ attention in the market.

So what’s in it for SMBs?

In terms of Google trends shown in Exhibit-A, IoT today is where big data analytics was around 4-years back. Gartner forecasts that there will be 6.4 billion internet-connected things in 2016. Although the potential of IoT is huge, few SMBs consider it their ‘critical’ priority for investment at the moment. For them, it is still a nice buzzword. There is still time before every visible thing will have a sensor attached to it that will communicate with your servers in real-time. Meanwhile, SMBs are willing to watch and ride the hype-cycle.

3. Predictive analytics to address cybersecurity concerns.

As SMBs expand their technology footprint to run their business operations, the need to secure and protect data grows. Data security and privacy concerns continue to exist among small and large business organizations. However, many SMBs feel challenged and intimidated to deal with the rising complexity of cybersecurity breaches. Companies are normally content with the conventional approach of putting defensive mechanisms to ward off security risks. However, with technology advancements, the security breaches have also become more sophisticated and more risky wherever consumer data is involved.

While large organizations invest heavily into advanced (read: expensive) security mechanisms, SMBs do not have the luxury to do so. Nevertheless, they are now custom-developing predictive analytic models to proactively monitor log files and other user data sources to detect any threat perception or breach alerts. Clustering algorithms can help them identify anomalies in user login or other events which can be recorded on an ongoing basis. 2016 is likely to see an increase in the application of predictive analytics to deal with cybersecurity concerns.

4. Machine Learning algorithms foster man-machine collaboration.

We are entering the ‘smart’ era – smart people working alongside smart machines in smart cities. IDC¹ predicts that companies will spend more than $60 billion on cognitive solutions by 2025. Theoretically, machine learning algorithms based on neural network and AI have existed for a long time. However, their widespread application in everyday life is getting acceptance only now. This is made possible due to the tremendous increase in processing power that enables real-time split-second decision making.

Machine learning algorithms are currently being employed primarily in retail industry. With more people shopping across multiple channels looking for lowest prices, machine learning algorithms will become very popular in implementing dynamic pricing and devising on-the-spot offers in retail stores to retain the buyer.

For example, during this year’s holiday shopping season, leading retailers such as Amazon and Walmart were relying heavily on algorithmic pricing. Both retailers re-priced 15% of 18,000 product SKUs being tracked by a pricing intelligence solution on November 14^th alone. These algorithms will be the backbone of any and every e-commerce business striving to win and retain customers.

[Example credit: Forbes]

5. Rising smartphone and tablet penetration continues to increase consumer mobility.

According to a comScore – Morgan Stanley research, mobile users globally have surpassed desktop users at the beginning of 2014. Rising mobile adoption, among people of all ages, impacts consumer purchasing patterns in a big way. With the increasing mobility, SMBs view mobile apps as a way to reach and engage end-users. SMB Group’s 2014 SMB Mobile Solutions Study indicates 59% of SMBs view mobile solutions and services as ‘critical’ to their business.

6. Hybrid cloud options still complex for SMBs.

2015 saw cloud making deep inroads into data-centers, data warehouses, centralized storages, and servers. SMB group’s market study shows that the cloud is poised to overtake on-premises deployment in the next year in areas such as collaboration, file sharing and marketing automation.

However, SMBs are largely using public cloud and staying away from private (or hybrid) cloud options because of the lack of clarity. Microsoft, Dell, and IBM have their own cloud platforms as hybrid cloud options however they do not yet seem to provide a compelling proposition for SMBs to embrace.

7. Omni-Channel integration or cross-device challenge?

Omni-channel is not a buzzword anymore given the availability of multiple screens every customer has. People have indicated that they love to shop across channels. So, more and more brands are going omni-channel way in a bid to woo consumers and to help them buy in their preferred channels. Brands are applying strategies like location based analytics to make relevant offers when consumers are in the vicinity of their stores. Businesses (like Macy’s or Virgin) that offer a unified omni-channel experience to their customers appear to have a competitive edge over others that cannot.

However, in a March 2015 study by Signal, 51% of marketers worldwide reported that they did not have a single view of customers, and only 6% of marketers worldwide reported they had an adequate single view of customers or prospects across all devices and touchpoints.

From our perspective, this year businesses will make this decision of whether they will play the omni-channel game and how.

8. Real analytics talent is (still) scarce.

According to the 2015 MIT Sloan Management Review survey² of business executives, managers and analytics professionals, 49% of respondents, who believe analytics creates competitive advantage for their organization, say that their company lacks appropriate analytics talent. While there is no dearth of analytics CVs in the market, very few of those appear to have real data science skills. In reality, companies need data scientists who possess the rounded knowledge of computer science, algorithms, math-statistics, business, and analytical skills.

Organizations that hire the less than appropriately skilled analysts end up wasting more than just money without any real benefits accrued. This is the reason more than 50% of analytically challenges organizations have stated that they outsource analytical services to external consultants or organizations, according to the survey.

Smart companies are realizing that analytical talent is critical to their success and in short supply, but more than 40 percent struggle with finding the talent they need. There seems to be a growing belief among SMBs that it is best to focus on customers to grow business leaving the necessary analysis tech work to specialists.

9. Visualization will be vital to SMBs application of analytics.

Data and the insights from that data are no more relegated only to the analysts. Business owners and SMB executives want to visualize their data to understand ‘what’s really going on’ in their business. And they want to do it in minimum possible time to be able to focus on the more important aspect of applying those insights for the improvement of their business. Business analytics in the SMB space is likely to stop being just a set of bar- and pie-based charts, and will be more multi-variate and intuitive. SMBs will demand more from the analysts in terms of visualization techniques that makes it easier and faster to visualize, understand, and explore data and uncover real insights from it.

Conclusion

This is an extremely exciting time for SMBs who can now apply customized analytics as per their specific requirements to take their business to a new level in an economical way. We believe this was not an option they previously had. It will be interesting to see how SMBs embrace business analytics to leverage the opportunity and explore unlimited possibilities.

References:

1 International Data Corporation

2 Ransbotham, D. Kiron and P.K. Prentice, “The Talent Dividend: Analytics talent is driving competitive advantage at data-oriented companies,”MIT Sloan Management Review, April 2015.

3 IoT image credit: wikipedia

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Analytics in Healthcare: A Veravizion Case Study –>

Top Analytics Trends 2017 – An INFOGRAPHIC –>

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“When I went to medical school, the term 'digital' applied only to rectal exams.” - Dr. Eric Topol

Well, things have certainly changed since! The previous article – an infographic – discussed about the urgent need for businesses to achieve digital maturity in order to survive and thrive. But exactly what does digital maturity really mean for a small and medium business organization that thus far has focused primarily on serving local customers?

You might be thinking whether this question – what does digital maturity really mean – is really relevant in today’s digital age. Our implicit hypothesis is that most businesses, especially those in the developed countries, are already digital by now, and so they must know what digital maturity really means.

Well, evidence shows that the above assumption is far from true.

Consider these stats from the UK Business Digital Index 2015 report which states that almost a quarter of UK businesses still lack basic digital skills:

• Almost 35% of around 5.2 million organisations in the UK have a very low level of digital understanding and capability – they do not make use of the internet for their business and do not have any web or social media presence
• Barely 53% of the businesses have their own website
• Only 46% organizations have a medium level of digital maturity – i.e. they use basic e-commerce tools, perform some banking transactions online, and have basic social media presence.

Therefore our question is extremely relevant even today!

So what does digital maturity really mean?

To understand this, let us quickly recapitulate why businesses want (or need) to go online in the first place.

Businesses go online for a variety of reasons (read: benefits) such as expanding markets to grow business, deepening engagement with target customers, broadening product and service offerings, leveraging multi-channel capabilities, and in general staying competitive amidst the changing global business landscape.

All these reasons can be summed-up in one simple line: Business organizations, like yours, are going digital because your customers are increasingly seeing, hearing, feeling, searching, interacting, sharing, and buying stuff online.

The above sentence encapsulates the entire online activity happening today in the business world. [tweet this]

In short, your market has gone online and it would serve you better if you do, too.

So what takes you there?

Here are the 5-stages on your journey to achieving digital maturity for your business:

1. Digital Apathy
2. Digital Literacy
3. Digital Transactions
4. Digital Engagement
5. Digital Maturity

Let us look at each one a bit more closely with an illustrative pictorial example for each:

1. Digital Apathy:

This is the initial (or default) stage of any organization typically born before internet. This company mostly sells their products mainly to customers in its neighbourhood through its physical stores. There is a passive resistance (or indifference at best) in accepting digital strategy due to inertia mixed with scepticism towards going digital. There is absolutely no online or any beyond-the-shop interaction with the customers. The business owner is unmindful about going out of business in this increasingly digital world, and apparently suffers from ‘it won’t happen to me’ syndrome.

2. Digital Literacy:

There is (almost) a reluctant acceptance to the changing business scenario. The business has a (mostly passive) website that displays the products and services on offer but hardly anything beyond that. On the positive side, customers now have a gateway to your offerings and can find information about your products and services. There is a new one-way channel to update customers about new product and service offerings – a good beginning to say the least.

3. Digital Transactions:

The business finally wakes up to enormous possibilities the e-commerce world offers and introduces online transactions to sell its products online. There is a conscious effort to implement basic customer analytics to understand buying customer profile to grow revenues. The business also tends to apply e-commerce intelligence to provide leads reports to sales teams to grow further. There is an emphasis on generating and distributing user-oriented content in order to draw target customers to purchase online. Businesses may introduce their own inventory management and service fulfilment back offices to excel in their customer service to build customer loyalty. The business starts learning about rule based prioritization as they explore the benefits of implementing analytics for revenue and profitability growth.

4. Digital Engagement:

When a business establishes itself on the various social media platforms, there is a step change in the way it perceives customer interaction, customer engagement, and marketing. Old channels and methods of one-way communication are renounced in favour of digital channels which enable listening to customers’ feedback first-hand and responding in their preferred channel to facilitate effective customer engagement. One important aspect of increasing engagement is to create product touch-points across all channels vis. physical, desktop, mobile, kiosks, catalogue, direct mail, and social media. The order in these cross-channel chaos is set by the use of marketing analytics which helps to mine hidden consumer insights, understand customer purchasing journeys, optimize advertising spend, and engage with prospective customers at early st(age) to nurture them into loyal followers.

5. Digital Maturity

The focus at this stage is on innovating the existing business model and on integrating the overall strategy. Personalization is the key here! Customers have 24x7x365 access to the products and services across different digital channels but still have an Omni-channel experience. For example, a customer becomes aware of your product in one channel, say Pinterest, actively searches for it online on his office desktop, physically touches and considers buying it in-store, ends-up purchasing the stuff on their mobile, and shares his new purchase with Facebook friends. Matured businesses (like P&G and Amazon) have institutionalized integrated use of analytics services to study individual consumer behaviour through comprehensive understanding of customer interests, affinities, and actions. They are drawing intelligence trends to predict customers’ future wants and needs before customers themselves realize it. Considering the enormity of data getting generated every day, matured businesses are implementing advanced algorithms to auto-analyse data at its source for more real-time application.

Achieving digital maturity is not the end; rather a beginning of the implementation of a truly personalized digital strategy for each consumer. Businesses embracing digital strategy will eventually lead the way.

“We are in the throes of a transition where every publication has to think of their digital strategy” - Bill Gates

Cover photo credit: yourgenome.org

Related Posts:

• Buy, Build, or Get the job done?
• Strategic Transformation Part-1
• Top Analytics Trends 2017 – An INFOGRAPHIC

<– Why your Business should go Digital

Most Popular Perspectives from 2015 –>

If you liked this article then you may also like to read The Digital Transformation Imperative: Why Businesses Must Have Online Presence – AN INFOGRAPHIC.

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“81% of US consumers turn to search engines to find information on products, services, and businesses before making a purchase,” according to GE Capital Retail Bank’s second annual Major Purchase Shopper Study. The digital transformation imperative study performed by Veravizion indicates that this observation is not much different in other parts of the world.

Less than 20 years back, Google (or an online search engine in its current form) did not exist. Most commercial transactions took place at a brick-and-mortar store. People booked long distance train tickets standing in a long queue at the ticket counter, bought airline tickets from travel agents, rented DVDs in video stores, read about new fashion in a print magazine, and purchased music CDs in record stores.

Today, 70% of all the travel bookings and hotel reservations take place online.

Music CD shops selling LPs, Vinyl records, and CDs have ceased to exist.

DVD stores have virtually disappeared from the streets.

Paper magazines and print advertisements have given way to their online cousins.

‘In the present day, if your customer cannot find your business on Google, you probably don’t exist for them.’ In a relatively short span of time, this has come to be one of glaring truths that business leaders must accept. Today’s consumer seems to have too many things to do, and appears to have become impatient because of limited time at hand. She wants to get everything done at the snap of a finger.

The digital world allows them this convenience of having (almost) everything in just one-click or touch. In fact, customers are adapting to this technology-driven shopping so well that they are touching every screen – even ‘dumb terminals’ – looking for an interactive touch-screen experience. Recent research on e-commerce points to a growing trend of digitalization of businesses and even non-profit social organizations.

Many industries like flowers and footwear, where customers’ need to touch and feel the product was considered important, now have above average online penetration. The grocery and general merchandise retailer Tesco is a case in point. It was one of the chains that saw an increasing role of technology in day-to-day household shopping and launched their online operations; it is now world’s second-largest retailer by revenues. A few industries like online grocery and pet foods (remember Webvan.com and Pets.com?) had a false start because of issues with their online business models, but are now being resurrected by the likes of Amazon and FreshDirect. Slowly but surely, every industry is joining the digital bandwagon.

Consumers on their part are enjoying the omni-channel shopping experience. Omni-channel purchase means a customer buying across multiple channels – online through mobile or desktop, call centre, catalogue, direct mail, kiosks, physical stores, and social media – and having a seamless shopping experience. So a customer may discover a great product offer while browsing Facebook during breakfast, search more information about it online via desktop after reaching office, ring a few call-centres to compare prices during lunch, check the product out at a nearby physical shop on the way back home, and finally purchase it online from their home using a smartphone. Once the product arrives, they may update their friends on social media posting pictures of their new purchase. The entire shopping experience becomes conveniently embedded in their routine and is fun.

Thus, internet is playing a key role in how businesses are run today. Nevertheless, it still has some way to go. An e-commerce foundation report shows that a disproportionately high percentage of businesses, even in developed countries with high internet penetration, are yet to go digital. For example, almost one in four businesses in UK has none to low digital maturity, while the ratio is reversed in some of the developing countries in Asia-Pacific, where the rate of digital transformation is much higher.

The attached infographic presents a quick glimpse of how business landscape is rapidly changing. It implores, with substantial evidence, why business (and social) organizations must have an online presence to survive and thrive in this third millennium.

What has been your experience of going digital? We would love to hear.

The Digital Transformation Imperative

Share this Infographic On Your Site

<p><strong>Please include attribution to https://www.veravizion.com with this graphic.</strong></p><br /><br /><br /><br /><br /><br /><br /><br /><br /><br /><br /><br /><br /> <p><a href=’https://www.veravizion.com/the-digital-transformation-imperative-why-businesses-must-have-online-  presence-an-infographic/’><img src=’https://www.veravizion.com/wp-content/uploads/2015/10/INFOGRAPHIC-Why-Businesses-Must-Have-Online-  Presence.jpg’ alt=’INFOGRAPHIC – The Digital Transformation Imperative: Why Businesses Must Have Online Presence’ width=’600px’ border=’0′ /></a></p><br /><br /><br /><br /><br /><br /><br /><br /><br /><br /><br /><br /><br /> <p>
References:

• http://www.retailingtoday.com/article/study-81-research-online-making-big-purchases
• HBR, hbr.org, #The Future of Shopping
• https://en.wikipedia.org
• Featured image credit: http://unsplash.com

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<– Data Science: The next frontier for business competitiveness

What does Digital Maturity really mean –>

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“This article reposted here was originally published as the cover story in the July-2015 edition of Computer Society of India - Communications magazine. You can also read this article at its source at http://www.csi-india.org (Link path: http://www.csi-india.org->PUBLICATIONS->CSI Communications->CSIC 2015->CSIC 2015(July))."

Data Science means extraction of knowledge from data. The key word in data science is not data; it is science[1]. Science of something means study of that thing to extract knowledge about it. In most generic sense, the purpose of every data science project is to answer a question (or a set of questions) backed by hard-facts. Academicians and researchers apply scientific principles to get specific answers about a research subject. Similarly, businesses employ data science principles to improve customer engagement, devise growth strategies, optimize operations, and build competitive advantage. This article shares a perspective on what data science really is, how it impacts various industries, what benefits does it offer to organizations – both for-profit and not-for-profit, and what are the key data science trends prevalent today.

DATA SCIENCE: WHAT IT IS (AND ISN’T)

Apparently Peter Naur and John W. Tukey seem to be among the first ones to have treated data analysis within the precincts of science[2]. John W. Tukey, who coined the term ‘bit’, has mentioned it in his 1962 paper ‘The Future of Data Analysis’. In my view, while the term ‘data science’ is relatively young, its application is not. There is an early evidence[3] of 1854, of Dr. John Snow applying scientific principles of data analysis to detect the root cause of The Cholera Epidemic in London. So data science has been around for a while albeit in different forms.

While we tend to associate data science with several other terms such as artificial intelligence, machine learning, data mining, analytics, statistics, computer science, and operations research, each has its own specific meaning that is different from another. Artificial intelligence is intelligence exhibited by machines and it pertains to the creation of a software system that simulates human intelligence. Machine learning is a science that involves development of self-learning algorithms which can be used to make data-driven predictions in a similar but unfamiliar environment. Popular examples include self-driving cars and web searches. Statistics is a study of collection, organization, analysis, and interpretation of numerical information from data. Data mining is the practice of analyzing data using (machine-learning) algorithms and statistical techniques in order to solve a problem. Computer science covers computational complexity, distributed architectures such as Hadoop, data compression, optimization of data flows, and not to mention computer programming languages (such as R, Python, and Perl). Advanced analytics or Analytics is just a marketing driven terminology that applies many of the data science principles to solve complex problems faced by businesses and society. So while the differences are subtle, each one has its own application in industry and academia. Nevertheless, data science overlaps with computer science, statistics, operations research, and business intelligence in many ways and almost completely encompasses data mining and machine learning.

The subtle differences notwithstanding, data science is an independent discipline which amalgamates statistics, computing skills, and domain knowledge. At the core, data science helps in deriving valuable insights from data. The data science process involves data collection, data pre-processing and cleaning, data modelling and analysis, and insights generation which are applied within a given functional domain to make decisions. Although the process is similar to knowledge discovery and data mining (KDD), a data scientist requires computing skills and domain knowhow to arrive at context-specific decisions. The person working in data science needs to exhibit three distinct skills applied in the different phases of a data science project. As shown in EXHIBIT-A[4], an individual with data science expertise possesses (or needs to possess) a combination of mathematics and statistics knowledge, hacking skills, and substantial domain understanding. The hacking skills include familiarity (but not necessarily proficiency) with software programming but more importantly, a propensity at being able to manipulate any type of data. This is because real-world data hardly exists in a nice tabular format. It[5] is scattered in thousands of text files or on hundreds of web sites or in numerous unstructured excel sheets at best. True data scientists that possess all the three skills are not abundant; because the role entails making sense of amorphous data, deriving bespoke models, and developing algorithms to analyse a complex problem specific within a domain.

Unfortunately, simply churning out numbers or fiddling with inefficient models rarely solves a problem. This is the reason data scientist is one of the most coveted roles in industry today.

Data science is being applied in many industries. Some of the uses in various industries include weather forecasting, intuitive search in online search technology, customer engagement in retail and consumer products and services, fraud detection in banking and credit cards, prediction of sources of energy in Oil and Gas, evidence based medicines in healthcare, and sentiment analysis from social network feeds. Some fields that are routinely implementing analytics services are eCommerce, retail, consumer products and services, financial services, insurance, pharmaceuticals, manufacturing, telecommunications, and high-tech.

HUNTING PEARLY INSIGHTS IN THE OCEAN OF DATA WITH DATA SCIENCE

More and more businesses are embracing data science and analytics in multiple organizational functions. There are mainly three most common ways in which data science is deployed depending on the size of an organization. Large corporations usually deploy their own in-house analytics departments by recruiting data analysts. Business leaders in large corporations typically have humongous quantities of data to sift through in order to make decisions that are important for their business growth. While having an in-house analytics team may not always be an ideal way for institutionalizing data science, even for large corporations, they seem to be driven by large amount of resources at their disposal. Secondly, some companies prefer to buy a COTS (Commercial-Off-The-Shelf) product to cater to some standard requirement. Thirdly, many mid-to-large sized companies prefer to employ customized data science or analytics services to solve their specific data analysis and business operational requirement. This option seems ideal for businesses looking for the flexibility to hire precise services for their bespoke needs.

While the data science projects in most for-profit organizations are getting more and more complex, the fundamental purpose underlying these projects remain the same – to achieve sustainable growth and improve profitability for their businesses. To that effect, the companies put data science into action to gain meaningful insights into their customers, operational processes, supply chain and logistics, product and/or service usage, financial aspects, and future business performance. Conventionally, data science has mostly been applied for market research and market segmentation. However, businesses have a lot more at stake with every business decision as competition has become more and more intense. Gone are the days when business decisions used to be taken on gut-feeling. In today’s globalized world, every major business decision needs to be data-driven. Data science assists organizations and individuals in making fact-based decisions that they can take and defend confidently. That is why it has become essential for organizations, business or otherwise, to deploy data science projects in every division responsible for making any kind of decisions. Some of the types of data science and analytics projects include customer focused analytics through clustering, recommendation engines, root cause analysis, automated rule engines, conjoint analysis to quantify perceived value of features offered, process simulations for operational analysis, predictive modeling for business forecasting, and clustering analysis to identify anomalies, just to name a few.

BENEFITS FROM IMPLEMENTING DATA SCIENCE INITIATIVES

There are some fantastic examples of business organizations gaining huge benefits by systematically and strategically deploying analytics initiatives that involve data science and ethnographic research. Procter & Gamble has institutionalized the data and design thinking approach to such as extent that it is now ingrained into their DNA. The result is that P&G boasts of more than 20 billion-dollar brands in their product kitty. Amazon, a technology company and not just an eRetailer, is really surviving and thriving by understanding customer preferences through the implementation of numerous algorithms. It has helped them to grow quickly from selling just books online in 1996 to target-selling twenty million products in countless other categories. There are many examples of smaller companies that streamlined their processes and implemented analytics based strategies to grow and enter into the big league. Data science initiatives within companies have rendered meaningful insights to drive their firm’s customer experience. These companies have utilized the insights to define their business growth strategies and pursue a culture of data-driven decision making. The benefits include getting pointers to new growth areas, generating ideas to introduce innovative new products, decreasing cost bases and improving productivity to boost profitability, identifying risks of obsolete technologies in their processes, detecting bottlenecks in supply chain, and streamlining inefficient operations.

Even as data science is rapidly changing the business world, it is also spreading its influence on other sectors such as academic research, governments, and social organizations. While the data deluge has increased the complexity for these sectors to analyze the data in a timely manner, it has also opened a plethora of opportunities for them.

Academic institutions in regions such as US, UK, and some countries in Asia are facing sustainability issues due to severe cuts in funding and grants. They are able to apply data science within their own institutional spheres to identify their respective competitive advantage and attract the right students to strengthen their reputation further. Similarly, medical research institutions are now able to work on projects like genome research, DNA sequencing, and stem-cell research for treatment of fatal diseases such as cancer and AIDS. Economists are able to analyze the publicly available data to determine relationships between income levels, education, health, and quality of life.

Governments and public sector organizations are concerned about issues such as monitoring and prevention of terrorist activities, early-detection and control of pandemics, and uniform aid distribution among the poorer countries, which they are able to tackle by sponsoring appropriate data science initiatives.

TACKLING CHALLENGES ALONG THE WAY

Data privacy and security concern has been one of the main reasons keeping some businesses from adopting data science. Moreover companies are facing real challenges in terms of bad quality of data, data inconsistencies, unreliable third party data, and information security. Nonetheless, all roads to meaningful business insights lead through data, whether it is organizational or public. Businesses need to put in place appropriate mechanisms to share data in a controlled manner with analysts and service providers in order to generate hidden insights that can be utilized for business benefits. Data breaches and data thefts remain a valid concern too. Past incidents, albeit few and sporadic, of customer confidential information getting stolen have deterred some from initiating analytics projects. However, business organizations are coming around to the fact that they are fast losing their competitive advantage to rivals due to staying away from analytics. Increasing number of organizations is taking up analytics to secure and grow their businesses as they do not want to be left behind any more. Organizations will increasingly recognize that it is not possible to operate in a 100 percent secured environment. Once organizations acknowledge that, they can begin to apply more-sophisticated risk assessment and mitigation tools. They will look to embed security at multiple levels viz. application-level, execution-level, storage-level, and even contract level. Interestingly, analytics itself is proving to be a great mechanism for security breach prevention.

KEY TRENDS AND THE ROAD AHEAD

In some of the western countries, data science has been thoroughly internalized within large corporations. Even the smaller businesses there employ analytics services to achieve specific business objectives. In India, while the (few) big corporations seem to be deploying such initiatives, most other organizations are still in the nascent stage. One survey of SME business owners cited that most common reasons for the slow pace of embracing [data science] are lack of awareness about the value offered by analytics, dearth of skilled resources, apprehension about technological complexity, cost and ROI concerns, and data security risks.

Notwithstanding the current adoption level, businesses are realizing that they may be taking a big risk not considering data science and analytics as a potent competitive strategy. There is a tremendous rise of personal data originating from social-media, sensor-originated data from wearables, and the Internet of Things (IoT) with the recent surge in the use of smartphones. More and more human actions are generating Exabytes of data today. To get a sense of the amount of data being generated, let’s just say that we will need around 50 billion trees made into paper to print 1 Exabyte of data. That’s roughly 9 huge stacks of papers, each touching Mars from Earth. This enormous amount of data will be of no use if not analyzed and utilized appropriately.

These trends are pushing businesses to re-think their business and growth strategies. There is an increased focus on teaching data science based courses by colleges and universities worldwide. Companies are realizing that the business environment has become uncertain with the fast pace of technological and demographical changes. As a result, many organizations are allocating higher budgets for deploying customized analytics for their businesses to deepen customer understanding, engage customers through multiple channels, identify new sources of revenue, improve productivity and profitability, streamline business processes, and build competitive advantage. Going forward, use of customized analytics will become pervasive. More and more organizations will develop their unique value propositions around the valuable insights they gain about their existing and prospective customers.

Implementing data science initiatives to build competitive advantage is a matter of leading and not following the pack. In an industry competing for the finite market share, early-adopters of data science best practices will be the eventual winners.

References:

[1] http://simplystatistics.org/

[2] Forbes: ‘A Very Short History Of Data Science’

[3] Edward Tufte: ‘Visual Explanations’

[4] Source: http://drewconway.com/zia/2013/3/26/the-data-science-venn-diagram

[5] ‘It’ refers to ‘the data’. In the modern world, the term ‘data’ is used in both singular and plural sense as per the context. Technically speaking, singular of data is datum.

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Website link: https://www.veravizion.com/data-science-the-next-frontier-for-business-competitiveness/

“This article reposted here was originally published as the cover story in the July-2015 edition of Computer Society of India – Communications magazine. You can also read this article at its source at http://www.csi-india.org (Link path: http://www.csi-india.org->PUBLICATIONS->CSI Communications->CSIC 2015->CSIC 2015(July)).”

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<– 3 Lessons Every Executive must Learn from Wimbledon Centre Court

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Last Sunday, the men’s singles final at Wimbledon between Djokovic and Federer was an enthralling match. Federer had hoped to become the first man to win Wimbledon a record eighth time; and Djokovic seemed to have something to prove after his recent defeat at the French Open.

The mixed doubles final, also played later that afternoon, was relatively a one-sided affair. The Paes-Hingis pair staged a clinical performance to clinch the title by decimating their opponents within 40 minutes.

During the matches, the English commentator attributed Djokovic’s win to his skill, determination, power, and accuracy, and alluded to Federer as the ’33 year old tired opponent’. Interestingly, the same commentator (or it may have been another one) ascribed Paes–Hingis’ comprehensive win to their experience, homework, and coordination.

But why did Federer really lose, despite his stellar experience of ten Wimbledon appearances and near-perfect game? And how did the ageing pair of Paes (at 42 years) and Hingis (almost at 35 years) register such a convincing victory against a much younger team? So, what does it take to succeed at the highest level in sports? And what lessons, if any, can businesses take from Wimbledon?

The Centre Court at Wimbledon provides three crucial lessons for businesses to succeed:

1. Do your homework thoroughly. Federer’s serve is the key to his game; he tends to serve deep and aggressively goes for the kill on the return of the serve. During the semi-final clash with Andy Murray, Federer’s winning points came off 5 rallies or less (on an average); whereas Murray’s winning shots came from at least 8 rallies. Federer outplayed Murray winning more than 80% of points off his first serves.

While Djokovic’s own serves were lethal, he must have studied his opponent well and had perfected his returns too. He forced Federer to play more rallies by returning his serves into areas where Federer could not attack back. The longer the rallies continued, the farther Federer had to run, and the more he became prone to making unforced errors thereby strengthening Djokovic’s chances at converting them into winners. Djokovic’s most winning points came off rallies that lasted 8 or more shots.

EXHIBIT-A shows Federer committed unusually higher number of errors and had lower serving percentages against Djokovic as compared to those against Murray.

Similarly, companies operating in the marketplace must thoroughly understand their competitors. Companies must first comprehend how their serves (like introduction of new product, feature, or category) are going to be hit back by their competitors, and then plan their strategies based on those insights. If the retaliation is weak, the market leader wins the market share; whereas if the competitor does tit for tat, then the market leader is forced to choose between carrying on the duel (with further investments) and conceding the share to the competitor. While this is true in all industries, it is most evident in oligopolistic industries like FMCG, where there usually are two dominant players. For example, similar duel happened between P&G, which introduced Crest fluoride toothpaste in 1955, and Colgate-Palmolive, which had launched the world’s first commercial toothpaste.

2. Execute well. Djokovic executed his plan [to play long precision shots] perfectly. Many of his winning shots were executed so accurately that they scraped the outsides of the baseline and the sidelines.

In the mixed doubles final, Peya and Babos showed lack of coordination early in the game by crossing each other’s paths and getting mixed-up in returning shots. On the contrary, Paes and Hingis displayed an absurdly good performance by hitting powerful returns and playing deep cross-volleys at the nets. EXHIBIT-B displays their high serving percentages (in the 80s) and zero errors, which reveals a clean and flawless execution.

In business context, perfect execution of strategies is a pre-requisite to achieving long term success. There are innumerable examples of brilliant businesses going dud due to botched executions. Kodak, despite inventing the core technology in the digital cameras, failed to execute the strategy and went bankrupt. Few other examples of companies that fell due to failed executions are Atari, Research in Motion, and Woolworths.

3. Play to Win. The two finals played at the Centre Court made this third lesson very evident. In men’s singles, Djokovic lost the second set in tie-breaker because he seemed content to passively return Federer’s serve playing from outside the baseline. He just didn’t appear to be playing to win and that cost him the set.

However, the brief rain gave him an opportunity to clear his mind and bring back his focus on winning. In the third set, there was almost a different – calmer and more focused – Djokovic playing within the baseline only to win.

Likewise in the mixed doubles, Hingis and Paes were so focused on winning that they were actually enjoying the game right from the word go. Every rally and every return was confidently played by them to win the point (and eventually the title).

This is how great businesses compete too – to win! They take bold steps and confident actions in planning and executing their strategies. They strive very hard to grasp the real needs of their customers. They go all out in devising solutions that they know will address the real needs of their customers. They leave no stone unturned to market their offerings. For example, Steve Jobs was so badly persistent on winning that he stretched himself and his team members to no measures.

Djokovic summarized this point well when he said in the post-match conference,

“I am gonna [sic] have to win, he’s not gonna lose.”

References:
www.wimbledon.com
John A. Quelch, Jacquie Labatt-Randle: Colgate Max Fresh – Global Brand Roll-Out.

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<– Strategic Transformation Part-2

Data Science: The next frontier for business competitiveness (External: CSI) –>

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Thanks for your overwhelming response to the ‘achieve strategic transformation for enduring growth – part-I‘ of this two-part series. In the part-I of this article, we agreed with Mark that strategic transformation is indeed the key to enduring growth. However, we differed on the way to achieve transformation.

So how do you achieve strategic transformation for enduring growth of your business?

In part-I, we asserted that the secret to achieving strategic transformation is to be fiercely customer-centric.

In this part, let us discuss how you can transform your business and grow it further keeping customer-centricity at the core of your business strategy.

When you become passionately customer-centric, you make your customers’ delight the overarching goal of your organization. ‘Customer delight’ becomes the Shinbashira – the central pillar – on which your organization stands. You listen to your customers and place your customers (and consumers) at the centre of everything you offer. You direct your resources toward satisfying (and exceeding) the needs and wants of your consumers. As their needs change, the solution you offer changes, and the business strategy behind delivering those solutions changes too. You become so agile in responding to your customer’s changing tastes that you barely notice the incremental changes taking place in your organization. This continuous change becomes second nature to your organization.

And when you look back over a period of time, you realize that you have moved so significantly from your original business situation that there is hardly anything common between the old face and the new face of your organization. It is like the organization undergoing morphing.

This is when you have achieved transformation, without consciously embarking on doing that.

You don’t TAKE disruptive actions for strategic transformation; you take well-conceived actions with specific goals that BRING ABOUT ‘disruptive transformation’. There is a difference!

But this is a very simplified view of an organization going through transformation.

What actually happens (or has to happen) on ground is far more complex and far too deliberate.

Let us see how.

Our analysis of the top-100 brands revealed that when organizations commit themselves to becoming customer-centric, they tend to take these five steps so as to focus on creating maximum value for their customers:

• They meticulously track usage of their products and services to figure out their customer’s usage patterns. This may involve analysing usage data from customers and in some cases their customer’s customers, who are using products that incorporate your product.

• They strive to understand their customers thoroughly to comprehend the real reasons behind their customers’ purchases and apply that knowhow to identify real profitable customers. They perform detailed analysis of the customers’ data to generate deep insights into their purchasing behaviour and to spot any changes in them.

• They incorporate their customers’ feedback into R&D to continually improve their products and services in line with the changing consumer expectations. Once in a while, this may result in conceptualizing an innovative product not yet in the market.

• They put in place mechanisms to refine their operational strategies and organizational processes to address the changing priorities.

• Most importantly, they use the feedback to calibrate their future roadmap and formulate the long-term growth strategy for their business.

These actions, when deployed effectively, enable these companies to embrace one or more of the three growth strategies: Market Expansion, Product/Industry Expansion, and Operational Improvement.

Let us briefly look at each of them.

1. MARKET EXPANSION – Business growth by entering into new market(s):

When you are customer-centric, you strive to know the face of your most profitable customers and the benefits for which they are buying from you. Your growth objective is to identify more of such customers globally who may benefit from your offering. This insight assists you to explore new customer bases in newer markets. The way this objective is achieved varies from company to company. Some companies merge with or acquire other businesses having presence in the target market, and leverage that presence to market their products. Others may form joint-ventures on the agreement to share technology and markets. Yet others may plan to grow organically by entering a new market on their own.

Coca-Cola, MTV, Starbucks, Nestlé, Heineken, and scores of other companies have successfully located their target customer segments across the world. They achieved international expansion over an extended period of time transforming their businesses from being local entities to becoming global market-leaders.

2. PRODUCT OR INDUSTRY EXPANSION – Business growth by introducing better products and services:

As your customers’ preferences change, the products or services they employ to do their job (need to) change too. When you are constantly tracking this change, you get innovative ideas for improving your existing product lines and introducing new ones. A good grasp on customers’ needs in new areas can propel you to launch new product categories that didn’t exist previously.

Procter & Gamble has developed this expertise in consumer research through ethnographic methods; they claim to co-create new products or new line of existing products by closely observing how their consumers use the existing products.

Amazon is an excellent example of growth through product or category expansion. Pursuing the vision of becoming ‘earth’s most customer-centric company’, Amazon is single-mindedly striving to make customer’s (online) shopping experience easy, comfortable, and pleasant. In fact, they are in the process of disrupting the entire book publishing industry by planning to publish and sell every future book online. The established book-publishers lost touch with the changing consumer need of ‘reading books anytime-anywhere without having to spend time buying it physically’, and now their survival itself is threatened by the digital publishing industry; whereas the likes of Amazon, with relentless focus on the consumers, are thriving.

3. OPERATIONAL IMPROVEMENT – Growth by developing unique competitive advantage:

This strategy involves creating differentiation in your business model and/or operations. Companies are leveraging their organizational data by applying the latest analytics techniques to mine insights. These insights are utilized to devise new distribution channels, optimize logistics and supply chain management, improve operations by deploying superior technology, and streamline existing processes. Relentlessly pursuing these strategies eventually renders them distinctive advantage over their competition, and helps them grow in the marketplace.

FedEx addressed the customer need of next-day courier deliveries and launched ‘FedEx Express’.

eBay provided easy B2C and C2C sales services to consumers via its (online) eCommerce platform.

Michael Dell grew his company by sensing an opportunity among PC-savvy consumers who enjoyed the convenience of customizing their PC and buying it online to be delivered in days. Thus Dell has developed an innovative business model of ordering PC online which enabled them to lower their PC prices to impossibly low levels.

These strategies have the potential to propel your organization into a bigger growth curve.

And the key to doing this is to understand your customers as thoroughly as you can!

In this world of disruptive innovations, business owners and CEOs must focus all their efforts in deeply understanding their customers. When you become ardently customer-centric, you set yourself up for strategic transformation that is key to enduring growth of your business.

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<– Strategic Transformation Part-1

3 Lessons Every Executive must Learn from Wimbledon Centre Court –>

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In the April edition of Stanford Business Insights, Mark Leslie states that successful enterprises have a ‘Cycle of Life’ which lives through five phases: Product or Service Development during Start-up, Market Entry, Growth, Maturity, and Decline. He says that during the decline phase, revenue slows down and flattens out, margins stabilize at lower levels, operational expenses rise to unsustainable heights, and company spirals into negative growth marked by layoffs, high burn rates, and eventual bankruptcy or liquidation. Mark says that the key to enduring growth, to manage this eventuality, is strategic transformation.

We agree!

When companies are growing for decades, deliberately or not, they tend to undergo some form of transformation, irrespective of how they are growing.

Mark further adds that there’s a moment along the corporate Arc of Life between growth and maturity – a point he calls ‘the sweet spot for optionality’ – when companies should take initiative to steer into uncharted waters (a new line of products, a new business category, a new industry?). In other words, opportunity-driven leaders should attempt to transform the business rather than risk growth by continuing along the well-marked path through operational excellence.

On these two points, we do not agree!

1. We do not concur that continuing along the path of operational excellence does not fetch growth.
2. We are not of the opinion that the way to strategic transformation is to just change your path to uncharted waters.

Let us explain why:

Regarding the first point, let us hypothesize for a moment that operational excellence does not fetch long term growth. Then how do we explain the growths of the likes of GM and Wal-Mart in the past? After-all Alfred P. Sloan, Jr. and Sam Walton are known to have led their companies on the back of operational improvements.

Moreover, prominent brands like Toyota, McDonald’s, Zara, and Subway have grown primarily through laser-sharp focus on operational efficiencies. Toyota has continually enhanced its assembly-line operations leveraging its legendary Toyota Production System. McDonald’s has continued serving its fast foods with the promise of ‘fast and convenient’ service. Zara has reduced its shopfloor-to-store cycle time of its fashion garments to just five weeks compared to industry average of six months.

We thought that studying the growth strategies of the top-100 brands, which have been growing for decades, would point to the key behind enduring growth of businesses. It will help us prove or disprove the hypothesis.

A quick analysis, as shown in EXHIBIT-A, revealed that more than two-third of the top-100 brands achieved enduring growth through strategic transformation. Interestingly, almost one-third of the top-brands have attained steady growth primarily through operational improvements.

EXHIBIT-B illustrates that there is no obvious correlation between a company’s lifespan and the revenues it earns, with respect to their growth strategies. However, it also establishes that transformation-driven companies seem to out-live and out-earn the operationally-driven companies, especially over the longer term.

So the above two analyses disprove the hypothesis that companies cannot grow with operational excellence; and it also buttresses the theory that strategic transformation is the key to enduring growth.

The second point in a way suggests that business leaders see the sweet spot of optionality as an opportunity to hurtle their company to the next level by changing their course into uncharted waters. But it sounds a bit ambiguous and fuzzy in terms of identifying the sweet spot of optionality almost to the point of being too simplistic.

This is because when you DO transformations for the SAKE of transformation, then you achieve just that – a transformation, without any real benefits from it.

You cannot just APPLY transformation in business as easily as you apply a Fourier or a Laplace transform in engineering mathematics. (Bad analogy I know, but you get the point).

Strategic transformation is a result, and not a set of random actions.

Transformation is an effect, and not a goal.

Transformation HAPPENS over time when you take well-conceived actions, persistently, with single-minded focus on a specific goal.

In our analysis, surprisingly (or unsurprisingly) there was one common theme (or goal) observed across all these 100 leading brands. That theme is Customer-Centricity. Amazon wants to be Earth’s most customer-centric company. Apple demonstrates its customer-centricity in the intuitive products it designs. Gillette develops a different type of razor for each customer segment that has a different shaving habit. Oracle invests strategically into technology that customers are likely to embrace in the future, as it did with its E-Business Suite. There are as many examples of customer centricity as the market-leaders around.

In sum, the point is this: The secret to achieving strategic transformation for enduring growth of your company is to be fiercely customer-centric. When you are passionately customer-focussed in your business, the customer will show you the way to achieving strategic transformation.

In part-II, we will discuss how exactly do you transform your business with customer-centricity as your main strategy.

(Cover photo credit: theatlantic)

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<– GYJD: Belief Reinforced

Strategic Transformation Part-2 –>

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