Tag Archives: Business Competitiveness

Two Finals, Two Ties and a common winner

Two Finals, Two Ties, and the Common Winner

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“Fed-ex is doing great; is gonna win the finals this time [sic],” said M.

“If the match goes beyond 4 sets, then Djoko will surely lift the Wimbledon trophy,” bet I.

M, a die-hard Federer fan with whom I am having almost fortnightly consulting sessions these days, and I were discussing about the possible Wimbledon-2019 winner. We had an unusual start of the day this week, playing the ‘let’s predict the Federer-Djokovic finals winner’ game, after India crashed out of CWC-19.

Suddenly, the Federer-Djokovic finals seemed more entertaining to watch.

In the end, both of us were right.

Fed-ex indeed did do great coming close to winning the title on two occasions. Djoko indeed lifted the trophy with Federer’s massive mis-hit in the end.

There he squats down to follow his winner’s routine of nibbling on a few blades of Wimbledon grass – the sweet taste of success!

. The Championships 2019. Held at The All England Lawn Tennis Club, Wimbledon. \{year4}{month0}{day0}\. Credit: AELTC/Simon Bruty

No, I do not intend to write this post telling how predictive analytics has helped predict Djoko to be the winner against Federer in today’s match.

Except, that is what this might turn out to be!

For the starters, a Federer-Djokovic match has gone beyond the realm of simple analytics.

Why?

Till date, Federer is the only gentleman (ahem… Wimbledon effect, you see!) to have beaten Djokovic in all four Grand Slam tournaments.

Similarly, Djokovic is the only man to have beaten Federer in all the four majors.

Federer has an all-time high number of 20 Grand Slam titles under his belt, while Djokovic, with today’s win, is not too far behind with 16.

Federer has held the world No. 1 spot in the ATP rankings for a record total of 310 weeks, while Djokovic continues to do so for over 250 weeks now.

The playing surface hasn’t been a decider either; both of them have beaten each-other on all surfaces.

Federer is marginally better on 1st serve win % (which is usually > 70%), while Djokovic only slightly trumps on 2nd serve win % (hovering around 60%).

And both gentlemen have achieved a career Grand Slam, two of only eight people to have done so, ever.

With such complex statistics behind the two greats, how do we conclusively analyse, and say that Djoko has a better chance at winning 2019?

Let’s consider these facts:

Federer and Djokovic have faced head-to-head 48 times, with Djoko winning 54% of the times (or 26 games) overall.

Federer dominated Djoko in 13 matches out of 19 (with a win % of 68.5) until 2010.

Since 2011, Djoko has beaten Federer 20 out of 29 times (with a win % of 68.9).

Isn’t this amazing?

Roger ruled the Wimbledon centre court until 2010, winning it 6 times.

Djokovic dominated (well, almost) the Wimbledon since 2011, winning it 5 times.

What comes next is even more amusing.

I had written in this 2015 Veracle on Lessons from Wimbledon Centre Court, how Federer’s winning points came off 5 rallies or less. And the more rallies he played (against Djokovic), the more likely he stood to lose.

Switch to 2019, Djokovic’s winning points came from 8 rallies or more; the more rallies he forced on Federer, the more unforced errors Federer rallied.

In 2015, Federer had 35 unforced errors against Djokovic’s 16.

In 2019, Federer rallied 62 unforced errors, 10 more than Djoko.

In 2015, Federer ran 5 meters more than Djokovic, for every point scored.

In 2019, Federer covered 7 meters more distance than Djokovic, for every point scored.

The Two Finals

Then, there is an uncanny resemblance in the match stats between 2015-final and 2019-final.

And I found it fascinating to compare the score-lines from the Wimbledon finals of 2009 and 2019.

2009 Wimbledon gentlemen’s final score-line:

Federer d. Roddick 5–7, 7–6(8–6), 7–6(7–5), 3–6, 16–14

2019 Wimbledon gentlemen’s final score-line:

Djokovic d. Federer 7–6(7–5), 1–6, 7–6(7–4), 4–6, 13–12(7–3)

See the only slight twist in the two score-lines? Just flip the scores of first two sets.

So much for the analytics…

Having said that, what a final it was! The longest one in Wimbledon history – and probably one of the most entertaining ones too?!

In the other tie, England defeated New Zealand with a margin as wide as a thin blade of grass.

In sum, when it comes to such close calls, nerves win. And DATA!

Just saying…

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: Wimbledon.com

How Deliberate Strategy can be your working strategy

How Deliberate Strategy Can Be the Working Strategy!

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The previous two Veracles argued about the two strategies – Nope and Hope – of the three types mentioned in “Does your business have a working strategy”. In this Veracle, we talk about the third type, that actually focuses on developing a working strategy. Here we discuss “How deliberate strategy can be the working strategy for your business.”

Deliberate Strategy is employed in an organization when business-executives:

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

What is Deliberate Strategy?

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.

It is like a journey one undertakes to reach a destination.

A journey constitutes 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 deliberate strategy requires the following actions to be taken:

  1. Understand the current business context.
  2. Define business goals to be achieved.
  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 the four steps in more detail:

1. Understand the current business context.

The business-executives developing a deliberate strategy needs to build a full grasp of the current business context with respect to the business environment.

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?

The business context provides a frame of reference to define appropriate business goals. Moreover, the business context serves as the baseline to measure and compare the progress against.

2. Define business goals to be achieved.

Organizational purpose and vision are the guiding-light for business-executives defining business goals. It is necessary that business goals are clearly defined so that one can communicate them unambiguously to all layers of the organization.

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

  • Quantitative – it is measurable
  • Timebound – it has a definite time frame within which to achieve it
  • Reasonable – it is realistic, even if difficult, to achieve in the given time frame

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

A QTR-based business goal establishes the destination for a business to reach within a stipulated time.

3. Identify the route to reach the business objectives.

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

This step is 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, 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. It involves figuring out what is required to reach that state, and then coming backwards 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.

Once the business goal is defined and the business strategy is rolled-out, the organization commits to the implementation journey along the strategic route.

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

And 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.

Governments keep looking for newer ways to tax businesses, and regulators are bringing new regulations to safeguard fair competition.

Among all this, technology disrupts the way of doing business.

To reiterate the point, the business environment is continually changing.

Therefore, it is imperative to keep looking for any changes that risk execution of your bespoke strategy. 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.

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 development of deliberate strategy using a Context-Drivers-Solution-Impact cycle. This framework applies to any business across industries.

There are many companies that have employed Deliberate Strategies in the past to grow predictably. Some examples (from across the industries) are 3M, Amazon, Apple, Boeing, Google, Nike, Nordstrom, Procter & Gamble, among many others.

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

This is a classic logical fallacy.

In reality, most of these companies were virtually a nobody before they implemented deliberate strategies.

Deliberate Strategy

3M were miners. Their earlier venture, started in 1902, to mine corundum failed. 3M 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 world’s most innovative company.

More Examples…

The following example has been taken from “Built to Last”, the bestselling book by Jim Collin and Jerry Porras.

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

If Boeing had followed 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.

Taking inspiration from their purpose and vision – to be on the leading edge of aeronautics pioneering aviation – Boeing announced their goal to make a jet plane for the commercial market. No other aircraft company had proved that there was a commercial market for jet aircraft. 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. 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 Deliberate Strategy. Apple believes in “breaking the status-quo”.

The strategy helped them differentiate in the crowded smartphone market and created an enviable position for them. Moreover, Apple was the most valuable brands in the world for eight straight years.

To sum it up with key insights…

Deliberate Strategy helps an organization achieve their 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 organization by 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?

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

Can Hope be a Real Business Strategy?

Can Hope be a Real Business Strategy?

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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. So, the perplexing question here is – Can HOPE be a real business strategy?

What is a hope strategy?

Hope strategy is one where businesses do a lot of the same activities with 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.

Here, they face two options to grow:

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

The first option – develop a bespoke strategy – is about developing Deliberate Strategy for your business. Although it isn’t, this option may seem costlier, at least in the short term, as it involves investing resources in designing a new strategy from scratch. We will discuss this in the next Veracle.

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

Interestingly, many businesses tend to take the second option out of the 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.

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 shiplore, 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.

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.

Businesses following a hope strategy exhibit three characteristics:

  • Lack of clarity about self-identity
  • Frequent change in the strategic direction
  • 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. 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.

This approach causes them to lose their core identify over time.

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

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

Yahoo! started in 1994 as a one-stop shop web portal. 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.

Can Hope be a Real Business Strategy?

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).

Can Hope be a Real Business Strategy?

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. Yahoo 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
  • Yahoo 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 appears to have 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.

Can Hope be a Real Business Strategy?

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.

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

Is business strategy really indispensable?

Is business strategy really indispensable?

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Why do I need a business strategy?

Recently, this question was asked of me by the chief executive of a retail business that sells moderately well. To answer this question, let us first understand what strategy is!

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

Strategy is applied in many different contexts. Military, sports, and business are some areas where strategy is necessary to win.

In 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 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 competitive advantage, and achieve goals of financial security.

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

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

What if you are the general of an army having limitless troops and tanks? What if you are the coach of a sports team having boundless talent and practice hours? What if you are 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 may have resources in huge numbers, but they are always finite in quantity.

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

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

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

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

Strategy is that mechanism!

Strategy is important because resources are always finite!

There 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 competitive advantage against your rivals of any size, and can still win.

There is a gem of an 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 maximum possible returns.

Some Examples

There are numerous examples in 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 manoeuvres. 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 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. Because Brazil were 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 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 Soviet Union that consisted primarily of professional players.

Examples from Business World

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. 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 and 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 making Mateschitz 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?

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 rawpixel on Unsplash.

Most Popular Perspectives from 2015

Most Popular Perspectives from 2015

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It’s New Year again – Happy New Year 2016!

Thanks for your overwhelming response to our insights shared with you over the last year.  We are excited to announce the most popular perspectives from 2015 published at Veravizion/Perspectives. These are our biggest stories of 2015 in case you missed them.

One of the wonderful aspects about sharing our insights is appreciating the incredible business acumen, diversity, and depth of thinking of our readers. Our articles, which we call our perspectives, are written after carrying out thorough research on every topic. Our belief is that these articles will push you into thinking about how the (business) world is transforming before our eyes, and how some long-standing business principles may not necessarily hold true today.

As the year is over, take a quick glance at how the world is getting used to being data-driven. Enjoy these stories and let us know about your top content in the comments. In the next one, we will see how the analytics world is likely to unfold in 2016.

Most Popular Perspectives from 2015

Story# 13 Lessons Every Executive Must Learn From Wimbledon Centre Court For Business Success

Most Popular perspectives from 2015 - Lessons from Wimbledon

Sports has always had many lessons to share for business success; and everyone and their grandpa knows this. Nevertheless, its relevance has never been as great as it is in today’s analytics age.

This article illustrates this phenomenon by drawing lessons for business success from 2015 Wimbledon final between Djokovich and Federer.

 

 

Story# 2Data Science: The Next Frontier For Business Competitiveness

Most Popular Perspectives from 2015

This article on Data Science by Veravizion 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)).“

 

 

Story# 3The Digital Transformation Imperative: Why Businesses Must Have Online Presence – An INFOGRAPHIC

Most Popular perspectives from 2015

INFOGRAPHIC: click to enlarge

The business world is fast going online, so what’s the big deal? The big deal is in grasping the fact that it may replace your business if you do not become a part of the change, soon.

The infographic in this article gives a glimpse of how fast the consumer purchasing trends are changing from physical to digital, and what you can do about it.

 

 

Story# 4How Do You Achieve Strategic Transformation For Enduring Growth Of Your Company? – Part-I

Most Popular perspectives from 2015

Historically, leaders of cities, communities, and organizations have been embracing strategic initiatives to ensure long term sustenance and growth of their respective ecosystems. Many a times, these initiatives were ‘intentionally’ directed at bringing about long term transformation of their systems. But do such initiatives specifically aimed at strategic transformation always result in the lasting growth of the entity? We discuss it in this article.

 

Story# 5What Does Digital Maturity Really Mean?

Most Popular perspectives from 2015

This is the last article in the Digital Business series in which we illustrate how small and medium businesses can transform themselves from mere-physical to also-digital, and be more competitive. We do this by taking a visual example of a fictitious light business of our lovable businessman Bobstick.

 

 

 

We hope you enjoy these stories!

 

 

Strategic transformation photo credit: businessinsider

You can also subscribe to our blog – Our Perspectives – 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, Facebook, or Google+ to receive easy updates.

 

What Does Digital Maturity Really Mean

What Does Digital Maturity Really Mean?

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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.

 

What Does Digital Maturity Really Mean?

 

  1. 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.

What Does Digital Maturity Really Mean?

 

  1. 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.

What Does Digital Maturity Really Mean?

 

  1. 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.

 

What Does Digital Maturity Really Mean?

 

 

  1. 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.

 

What Does Digital Maturity Really Mean?

 

 

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

 

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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Data Science

Data Science: The Next Frontier for Business Competitiveness

Veravizion No Comments
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.

Data Science Venn Diagram

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.


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


 

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