Business Strategy Analysis

In my last post I made the case that the future of business will require more reliance on powerful, computer-based analytics that interact with (not supplant) skilled data scientists who bring both analytic and business context knowledge into the process. Modern, effective customer insight analysis requires this kind of efficient cooperation between the analyst and the analytic engine to meet the business objectives of our customer insight function.

While this cooperation between analyst and the analytic tools is critical to effectively producing useful customer insights, it is equally critical to getting those insights implemented within the business. This is especially true when attempting to apply predictive analytics to the way we manage and interact with our customers. We need a system that is designed around the people for whom the insight is produced - a system that allows the insights to support the decision-making of the people and processes that directly impact your customers.

I have been part of many predictive analytics projects over the last 5 years. Nearly all of them have successfully extracted a set of useful insights that have impacted the way companies think about or interact with their customers. However, very few of them have made an impact on the specific actions taken toward specific customers, which is necessary to experience the full power of predictive analytics. For instance, I once built a model that predicted whether or not a channel partner's revenue to the OEM was going to decrease in the following year. It was a very accurate model, and it highlighted a number of key reasons behind declining revenue. The drivers of decline were immediately seized upon by channel management, and task forces were put in place to better understand and fix them. However, no one was able to find a use for the ability of the model to identify specific partners who were likely to decline in the coming year.

There are many reasons that customer (or partner) focused predictive analytics fail to impact specific decisions made about specific customers. A majority of the reasons I've encountered can be attributed to an excessive gap between the point of insight production and the point where the insights result in actions toward specific customers. In the pioneering book on enterprise decision management - Smart (Enough) Systems - Neil Raden and James Taylor dub this phenomenon the 'insight-to-action gap.'    

In my experience, there are two critical reasons that this gap exists for customer-focused predictive analysis projects:

1. The analysis project was not focused on a specific, customer-focused decision-point. Many insight projects start with the goal to see what we can find that will predict an increase in revenue. This is not a bad thing. Sometimes we need to start this way to understand where to dig further. Just don't expect these projects to yield quick and specific action.

2. There was no forethought or buy-in to the process by which insights will be delivered to the front-line employee for action. This often happens when a customer strategy group gets access to previously unintegrated datasets about the customer and has been tasked with providing insights about a particular issue like low renewal rates. They, rightly, decide that predicting who will and will not renew is more actionable than just looking for drivers of renewal, and a predictive project is launched. I fully support this thinking except there is no definition around getting the 'actionable' insight into the hands of those who will act.

The reason both these situations yield a gap between the insight and action is illustrated in the figure above. After an insight is developed, the next defined step is developing a report and presenting it to group of managers or executives. We bring our amazing project and results, and lay it out for them to approve or disapprove of. The best case is that they approve and say, "We need to use this information to intervene and stop the predicted bad things from happening while capitalizing on the predicted good things!" Then what? Then a group of people, which may now include at least a manager of those who will take the action, is convened to create a strategy for operationalizing the insight. By the time the insight actually impacts a customer it could be months later.

Thankfully, there is a better way, and it's all about beginning with the end in mind. Start by defining the specific customer outcome you want to predict - not something broad like customer revenue, but a specific aspect like customer spend on new products. The next step involves identifying the decision or interaction point at which you will intervene. This requires involving the group who will be responsible for the intervention and designing the process/system to do it. Then we move on to identifying and integrating data, running analysis, putting the insights into action, via the pre-defined and agreed-upon process, and validating the impact. An upcoming post will discuss this process in more detail, but the most important step is knowing exactly what to predict and what you will do with that prediction when it comes. Without that, your well-crafted insights are likely to stagnate. We need to mind the gap.

A recent TED Talk by Shyam Sankar (also the subject of this recent blog post by Leslie Pagel) nicely argues that man-machine cooperation is the real story of technological development. In a 2010 article, chess grandmaster Garry Kasparov, who famously played IBM's Deep Blue in the late 1980s, relays a wonderful anecdote illustrating the power of this symbiosis between humans and computers. In 2005, a freestyle chess tournament was held where humans and computers could work together or play separately. At this point in history, a computer program running on a standard laptop could routinely beat many grandmasters. However, this freestyle tournament produced two interesting and relevant results:

1. a strong human player with a weak laptop soundly defeated even the best stand-alone chess computer, and
2. the overall winner of the tournament was not a grandmaster with a powerful computer, it was a pair of amateur chess players using three relatively weak laptops. 

According to Kasparov analysis, the team's winning edge was a superior interface between all humans and computers that effectively counteracted the superior chess knowledge and/or computational power of their opponents.

From this story both Kasparov and Sankar conclude that the decisive factor for determining the analytic capability of any human-computer combo is the friction between humans and computers. By designing a better interface that reduces the friction, you increase the analytic capabilities derived from the same human and computer at an ever-increasing, convex, rate.

While I completely agree that designing friction out of the interface is a decisive factor, I think there is one critical element behind the success of the human-computer team that both Kasparov and Sankar overlook - the rules of the game favored a cooperative strategy. The rules of freestyle chess require players to make moves much faster than regular chess. Therefore, the ability to have a computer crunch the data and provide the human player with a short list of potential moves is a critical advantage. Given more time between moves, the experience, knowledge and creativity of a chess grandmaster begins to override the speed, computational power, and efficiency of a computer chess program.

These two elements of success in chess are perfectly relevant to customer predictive analytics and customer-focused decision-making.

• First, useful predictive analytics require the smooth interaction of a skilled data scientist and a powerful, but usable, analytic workbench and process. It is not uncommon for an analyst to only spend 10%-40% of their project time actually running analysis and extracting usable insights. The rest of their time is spent transforming and merging data or getting outputs into usable/shareable formats. We need more work on reducing the friction between the analyst and the analytic tools if we are to realize the full benefit of predictive analytics. 
• Second, data scientists need to fully understand the context they are working in and the rules that apply to it so they can apply predictive analytics in the right place and using the right approach. For instance, conducting a predictive analytics project within a strategic accounts group with a small set of accounts and deeply embedded account managers is not going to produce as much return as a similar exercise in an outbound call center where fairly inexperienced sales reps are each responsible for hundreds of accounts.

The future of business will require a reliance on powerful, computer-based analytics that easily interact with (not supplant) skilled data scientists who bring both analytic and business context knowledge into the process.

If you've been alive and reading anything published in the last year, you've probably seen two terms - Big Data and The Cloud (a great name for an indie electronic synth-pop band, btw). I have to admit that every time I hear the term "Big Data" I picture a server room with network storage devices containing petabytes of data, and sometimes it looks like that secure computer room from Mission Impossible. As an aside, whenever I hear "The Cloud" I picture a brilliant blue sky with a single white fluffy cloud... containing network storage devices (wireless, of course) filled with petabytes of data.

Here's the thing, Big Data isn't always big in volume. According to concepts originally posited back in 2001 and a definition in a recent Gartner report, "Big Data are high-volume, high-velocity, and/or high-variety information assets that require new forms of processing to enable enhanced decision making, insight discovery and process optimization." The "and/or" is critical for me. In my role as a customer insight analyst focused on bringing the customer experience into business strategy, I rarely deal with data larger than a few hundred megabytes. The data aren't of particularly high velocity, either.

Where I see the primary intersection between big data and customer experience analysis is in the variety of data we use. We routinely combine data from 4, 5 or even 20 different sources representing scores of different data categories to understand the impact of customer experiences and how to effectively improve them. The second part of the Gartner definition about the data requiring new forms of processing, is also true in my experience. This combination of multiple data sources and streams has required that we think about and analyze data differently than we did 5 years ago.

So, before you think Big Data only affects those who have terabytes or petabytes of information at their fingertips, think again. Big Data affects most of us in the business analytics world, and we have to adapt to it in new and inventive ways.

In today’s economy, many businesses can’t afford to manage customer relationships the same way they always have.  They don’t want to operate in a reactive mode.  They can’t just rely on intuition to deal with customer issues or opportunities.  Instead, they need a better way to proactively manage customer behavior. 

Have you heard the comment that companies are “data rich and insight poor?”  There is so much data available that there has been lots of press regarding the need to manage the avalanche of information.  In fact, that’s a key premise of the book Drinking from the Fire Hose which encourages customer strategists to narrow things down and focus on what really matters. 

Beyond that need to focus is a desire by many companies to better predict customer behavior.  The concept of using all that data to see what’s coming – and ideally to put strategies in place to optimize relationships – is behind the move towards predictive analytics.  This is an area of statistical analysis that deals with extracting information from data and using it to predict future trends and behaviors.

This Forbes article from 2010 was on target with the point that using predictive analytics can be a game changer in terms of improving efficiency, reducing risk, and increasing profits.  

Just think about the possibilities…  What if your overall customer base was fairly stable, but only because you were losing customers just as quickly as you were acquiring them.  Wouldn’t you want to understand what was driving attrition well enough to predict who might leave so that you could develop customer retention strategies to keep them?  

Kitty Radcliff
Vice President, Consulting Services

I was recently with a business strategist from a Fortune 500 company who stated there were ultimately three reasons corporate strategies fail. Even though he was speaking of overarching corporate strategies, the three reasons align with what I have seen related to customer strategies:

1. You measure the wrong things – Good strategy is the result of careful, intelligent analysis; however, the old maxim “garbage in, garbage out” applies here. In customer strategy consulting, this can be the result of jumping on the bandwagon of the latest killer metric without a full analysis of whether or not the metric actually applies to your industry. One way to avoid this shortcoming would be to conduct a pre-program strategic assessment – this step will allow you to learn not only the key customer touchpoints, but also identify the critical needs of key stakeholders in the process. It will also help you make certain you are profiling the customers the right way and focusing on the most critical.
    
2. You make the wrong decisions – Even if you measure the right data, there is no guarantee you will make the right decisions. Some of this is related to the data itself – in customer strategy consulting, using statistical methods that allow us to determine which areas of focus will have the greatest impact on customer loyalty will provide some insulation against focusing on the wrong areas. There is, however, another source of potential error – and that is the direction of where the market in total is heading. Every decision is framed not only by the data you observe, but also by your outlook on the competitive environment in general. To ensure you get it right, there are three recommendations I would make:

• Include competitive assessments in your loyalty measurement program – Having an idea on your position relative to the competition can help fine-tune your analysis. You can read more about benchmarking options in this series.


• Commit to ongoing measurement – This does not necessarily mean an ongoing data collection effort; rather, it is about knowing when to re-assess the customer landscape to ensure you are accounting for all the relevant issues. Most clients do this every 18 to 24 months at a minimum.


• Build macro and micro-level strategic plans – The overall strategy that emerges from the statistical analysis is best used in the context of focal areas that have the greatest impact on the greatest number of customers; however, building more micro-level, customer-based action plans will ensure you are accounting for the individual differences that exist among customers.

3. You do not take action – This is the one we tend to see the most. I once worked with a person who was prone to saying “strategy is cheap; execution is hard.” When I first heard him say this, I thought he was saying that strategy was simple; I now realize what he meant was that even though strategy can be hard, it is infinitely more difficult to execute on a plan of attack you know is correct. The phenomenon of acting in ways that are not in your best interest is less about intelligence and more about discipline. I tend to use diet and exercise as an example – I know I should exercise more and eat less, but it is far easier to do the opposite. We at Walker have designed a framework to help navigate the key disciplinary elements needed to take action – namely, organization, process, communication, and motivation.

Certainly there are many reasons strategies can fail; however, I suspect that most of the reasons would fit into this framework. Being mindful of the potential pitfalls that may exist can help you be more proactive in building a plan that will maximize your probability of success.

Mark A. Ratekin
Sr. Vice President, Consulting Services

Launching a new voice of the customer initiative is a big undertaking. Unfortunately too many companies do just that – they launch! They charge into an initiative without taking the time to develop a thoughtful plan. Given the potential impact of a company’s customer engagement strategy and the importance of doing it right, it makes sense to conduct an assessment to consider all the elements that will be critical to the launch and implementation of a results-oriented program.

The following 11 key elements are the key factors to consider in a well-executed assessment.

1. Scope – The scale of this undertaking is understood and the necessary resources have been identified.
2. Readiness – The degree of organizational readiness has been assessed and it is understood what will be necessary to create buy-in for the initiative across the organization.
3. Alignment – There is a clear line of sight on how customer insights tie to business results.
4. Listening posts –The organization has determined how they will collect and integrate the most important information for making customer-focused decisions.
5. Stakeholders – The information needs of the organization have been assessed and it is understood how customer insights will be distributed and used across a variety of functional departments and customer-facing associates.
6. Education – Programs to drive awareness, understanding, and action have been identified to bring about the necessary corporate culture for customer-focused success.
7. Communication – Communication needs have been outlined to understand how the organization will drive internal awareness, deliver actionable reports, and communicate externally with customers.
8. Technology tools – Technology tools needed to facilitate the collection, analysis, and distribution of customer insights have been identified and it is understood how these tools will integrate with existing technology systems.
9. External resources – There is an understanding of what additional resources will be necessary for methodology, research, technology, training, and additional consulting.
10.  Metrics – The key metrics for the success for the company’s customer engagement strategy have been established.
11.  Roadmap – A detailed plan or roadmap has been developed that includes a timeline of activities and a breakdown of the necessary individuals to be involved in a practical, phased program.

Patrick Gibbons
Principal/SVP
Walker

I have a new baby boy at home, and after a pretty sleepless night, this morning’s HBR “daily stat” about caffeine consumption caught my eye.  A group in the UK studied the effects of caffeine on collaboration, and found some key differences between men and women.  When it comes to collaboration on stressful tasks, they found that caffeine tends to impair men's performance but actually boosts women's ability to work under pressure. 

This is a light-hearted topic, but it does speak to the power of segmentation.  In our daily lives as Voice of the Customer advocates, we can find some interesting and useful applications of the data we work with when we break it apart and look for different behaviors, needs and tendencies across our customer segments.  Last year, my team worked with a client to develop a set of common customer ‘personas’ using segmentation analysis.  In VOC work for large B2B companies, we often only focus on 'A Priori' segments – those that we already know and use in daily business operation, such as region, channel, etc.  In this case, the objective was to take a more empirical approach and let the data tell us how customers tended to group together based on their profiles and their needs.  Many different demographic, firmographic, preference-based, and performance-based metrics were fed into the analysis. 

The outcome was the identification of 4 unique 'customer personas' that were common in this customer base.  We were able to understand the variables that characterized each ‘persona’, the relative size of each within the population, differences in their loyalty, differences in their needs and interests related to training, and how best to communicate with each customer group. 

Great outcomes for the client and their customer strategies... and a little good news about my daily caffeine habit, too.

Krista Roseberry
Vice President, Consulting Services
Walker

• Combining the unstructured data with the structured data, such as financial information, operational metrics, and customer survey responses allows an organization to prioritize the areas that drive customer behaviors. Without it, a company might be tempted to act on the loudest voice, which might not influence future purchase decisions.
• Most business decisions require evidence and validation before resources are allocated. Leveraging all sources of customer information builds confidence that the organization is dedicating resources wisely.
• The words customers use to describe a company, product, problem, or positive experience adds context and can be helpful in developing customer communications.

This is the sixth and final part of a multi-part series on the trends we are observing among the 1to1 Customer Champions with respect to their efforts to build a customer-focused culture.

Over the course of this blog series, I have examined the themes that we can observe by examining the 2010 1to1 Customer Champions. In the course of the series, we discussed the importance of:

1)      Executive sponsorship/support

2)      Linkage to business outcomes

3)      Taking action on learnings from customer feedback

4)      Engaging employees across the entire enterprise

5)      Using the new (or improving tools) at our disposal to fully leverage customer feedback

Why is being customer-focused so important? At the risk of repeating themes that you will see across all the Walker blogs, we know from our own research and research from academia that:

• Customer-focused companies tend to have a greater share of loyal customers; these customers tend to spend more, purchase more widely across your product/service portfolio, and are more resistant to competitive alternatives;
• Customer-focused companies use the feedback to determine a plan of attack that yields optimal results – that is, it minimizes the cost of implementation while maximizing the financial impact it will have on the organization;

The result includes three outcomes that create a virtuous cycle that benefits both customers and the company in total:

1)      These firms tend to enjoy greater financial success than their less-customer-focused peers.

2)      As a result of the greater financial success, these firms’ executives are more likely to be “true believers,” which means they will not only continue to invest in customer-centric strategies, but also “walk the talk.”

3)      Customers benefit from the level of focus placed on them by the company, and they reward this with greater spend levels and/or lower likelihood of defection.

How can companies ensure that they are perceived to be Customer-Focused companies? Here are some suggestions based on our work with clients:

a)      Develop a rigorous feedback gathering method – Use proven sampling techniques to ensure that feedback is being gathered in a fashion representative of your customer population.

b)      Have a plan for follow-up – Commit to doing something with the information; if you cannot commit, then do not waste your customers’ time.

c)       Look for immediate service recovery opportunities – Scour the real-time results for clues to where services or products are not living up to customer expectations and create a closed-loop process (including set time-bound service level agreements) for your front-line associates to follow-up.

d)      Use driver analysis to prioritize effectively – Using a structured feedback approach offers the opportunity to create models that provide insight on where to focus – skipping this step (or focusing solely on raw performance scores) may result in suboptimal improvement efforts.

e)      Integrate internal metrics into your analytic plan – Linking behavioral metrics (such as financial data or other performance metrics) will not only bring clarity to what you need to do (particularly important for associates who are not customer-facing), but also how to track your success.

f)       Utilize customer feedback in account planning – As sales teams are preparing forecasts, be sure to integrate customer feedback as another data source to consider when looking at which products and services to promote with a specific customer. Walker’s Value Mapping process can be an effective means of providing broad strategies for segmenting accounts that can have great utility in the account-planning process.

g)      Communicate what you are doing – The trap that some companies fall into is that they are Customer-Focused Companies that are perceived by their customers as being Lip-Service Companies. The solution? It sounds too simple, but it is true – do not forget to communicate what you learned in the process (and what you are doing about it). This can take a variety of approaches, ranging from a broad-based communication to all customers from the CEO to more tailored messaging to a specific customer account.

It is not easy to become a customer-focused company – if it were, everyone would do it, which would diminish (if not eliminate) its value as a competitive differentiator. If you keep in mind the five themes we see among the 1to1 Customer Champions and leverage the recommendations put forward in this entry, your firm will greatly increase its odds of being a successful, customer-focused, and financially rewarded company.

I hope this series has been of value to you – I would love to hear your own success stories.

In a recent article for BusinessWeek, Mark Johnson discusses mergers and acquisitions and how to increase the probability of success. Johnson points out the familiar statistic that 80% of acquisitions fail to create value for the acquiring company; the reason, Johnson hypothesizes, is that firms fail to realize what they are buying. In Johnson’s words:

“When one company buys another, what it's really purchasing is the target company's business model—its customer value proposition, its profit formula, its resources, and its processes.”[i]

Johnson outlines that two types of acquisitions can occur:

1)      Acquisition of resources – The acquiring firm is essentially purchasing technology, capabilities, etc., that are then integrated into the acquiring firm’s existing business model. Cisco Systems (a Walker client) is noted as following this path.
 

2)      Acquisition of a business model – The acquiring firm is purchasing the business model of the target; in this case, the acquisition is generally kept separate from the acquiring firm. Resources (capital, for example) of the acquirer are leveraged to help jettison the growth of the purchased firm. Best Buy’s purchase of Geek Squad is given as an example.

This premise is interesting and makes sense; we would offer some additional observations to add to the analysis:

1)      What about customers? Critical to understanding the aspects of the business model as addressed by Johnson (i.e., customer value proposition, profit formula, resources, processes) is how customers fit into that model. For example:

a.      How loyal are the customers to the organization? We have found customer loyalty (that is, the likelihood for the customer to continue to purchase coupled with the level of commitment of the customer toward the firm) to be a strong predictor of future business success. Understanding the extent to which customers are loyal to the acquisition target is key to understanding the long-term viability of the firm’s profit model (and, therefore, the valuation of the firm at large).
 

b.      What revenue flight risks exist within the organization? Suppose you are interested in acquiring a firm that has an excellent product; if the firm has had some service issues of late that has caused some level of degradation of customer loyalty, should you proceed with the purchase? There is no one-size-fits-all answer. For example - if the product is unique (that is, few competitive alternatives exist), customers are likely trapped in the short run, which means that the purchasing firm will likely have to invest aggressively from the onset; moreover, this approach carries risk – if a new entrant comes into the market, there could be great revenue flight. At a minimum, this could have a significant impact on the price of the acquisition.

If, on the other hand, plenty of competitive alternatives exist, it may make more sense to not complete the acquisition. Regardless of the outcome, the acquiring firm cannot make an informed decision without knowing the level of loyalty among the customer base and how the firm’s revenue aligns with the loyalty profiles.

c.       How distinct are the customers relative to the acquiring firm’s customer base? Is the product or service provided by the acquired firm designed to offer new offerings to your existing customers, bring distinct (and new) customer segments to the firm, or some combination of the two? Consider the Walker Growth Matrix:

Simply put, this matrix decomposes four growth strategies into customer type and product/service offering components. This matrix can be helpful in identifying what type of growth we can expect the acquired company to provide.

Understanding this can help in the valuation of the acquisition, as it tells us how much wholly new revenue vs. incremental revenue to expect. In order to reliably estimate this, you need to understand your current customers as well as what needs (met and unmet) exist among the target firm’s customer base.

 

2)      How complementary are the cultures? Johnson does make that case that understanding the culture is key to understanding the extent to which the two businesses can be effectively integrated – for example, an entrepreneurial culture will likely be suffocated if the acquiring firm is more structured/disciplined (the difference between being “disciplined” and “staid” is often in the eyes of the beholder).

 

Understanding the culture, combined with an understanding of the loyalty of the employee base of the acquired firm, will help to determine whether to fully integrate the acquired company or to keep it as a stand-alone entity. In addition, understanding the employee loyalty will also provide insight as to the likelihood that the firm will be able to continue to generate success – if the firm has been successful but the employee loyalty is low, then there is a heightened likelihood that the best days may be behind it due to the probability of post-acquisition employee defections. While that isn’t necessarily a reason to not consummate the deal, it again would likely have some influence on the tangible value of the firm. Do you see a theme emerging here?

 

Tying all this together, the advice we would offer on the topic of mergers and acquisitions to customer-focused firms is fairly straightforward:

 

1)      Don’t lose your sense of self – If you are a customer-focused firm, seek to acquire like-minded companies. While it is possible to successfully acquire a firm that is not customer-focused, the effort to achieve successful integration will be immense, and failure could have adverse impact on how customer-focused your current customers perceive your organization.
 

2)      Remember what you are buying – If the customer base of the target is a key aspect of the acquisition (and it absolutely is unless you are acquiring a specific technology that has not yet been introduced to the market), then take the time and make the necessary investment to optimally understand how loyal those customers are.
 

3)      To integrate or not? – Examining the culture of the acquired firm (including the loyalty of its employees) can provide effective cues to whether or not an absorption acquisition model should be preferred over a stand-alone entity model.
 

4)      Loop back after the acquisition – Regardless of which integration model you pursue, don’t forget to loop back after a reasonable period of time to see how customers and employees are feeling about the success of the acquisition. Use this information to quickly address any problem areas and to reinforce the importance that both customers and employees play in the long-term success of the firm.

Considering these aspects, in conjunction with the excellent guidance provided by Mark Johnson, will help increase your overall probability of a successful acquisition.

Mark A. Ratekin
Senior Vice President, Consulting Services & Resource Management

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[i] Johnson, M. W. (2010, May 26). How to Succeed at M&A. Retrieved June 7, 2010, from Bloomberg Businessweek: http://www.businessweek.com/innovate/content/may2010/id20100525_156769.htm?link_position=link16

 

• Greater market turbulence (the speed at which customers and customer preferences are changing) increases the effect of customer orientation on business performance.
• Greater technological turbulence (the speed of technological change) decreases the effect of customer orientation on business performance.
• More competitive markets see a stronger effect of customer orientation on business performance.
• Stronger macroeconomic performance decreases the effect of customer orientation on business performance. When the economy is weak (i.e., a recession) is the best time to increase your customer orientation.
• Regional and cultural differences have an impact on the effect of customer orientation with "Western" cultures having a stronger effect of customer orientation and "Eastern" having a weaker effect.
• The size of the economy in your home market has impact on the effect of customer orientation with larger economies having a stronger effect of customer orientation on business performance.
• Finally, mature markets demonstrate a stronger effect of customer orientation on business performance.

1. Re-centering on customer centricity
2. A broader orientation for being customer-focused
3. Characteristics of a customer-focused company
4. The focus of customer-focused companies
5. The moderation of customer focus

As we head into Final Four weekend it got me thinking about the keys to winning basketball games. Being from Indianapolis, I couldn’t help but reflect on the Butler victories in my analysis. Here are a few factors I think make the difference between winning and losing.

1.       A strong defense

2.       Capitalizing on turnovers

3.       Balanced scoring

No team has scored 60 points against Butler in the NCAA tournament. You can win games with good defense. Against Syracuse, as it was with Murray State in the second round the difference was turnovers and Butler’s ability to score points off of those turnovers. Balanced scoring is another Butler strength. Five different players have led the team in scoring in the last 10 games, including defensive specialist Ronald Nored’s 15 against Murray State.

Ready for the transition from basketball to business? Here we go. I think these three lessons in basketball success relate well to consistently growing revenue year over year. Here is the thinking.

One way to grow revenue is to keep what you currently have. It’s hard to fill a leaky bucket. Keeping customers is like playing good defense. Defending your market position and the relationships you’ve worked hard to develop with your customers.

Another way to grow revenue is to take share from your competitors. Capitalizing on competitor’s vulnerabilities is one way to take share. Not too much of a stretch from capitalizing on turnovers in a basketball game, right?

How many championship caliber teams have only one player that can score? And how many companies consistently grow revenues by banking everything on one growth strategy? Not many. Luckily for Apple they didn’t bet everything on Apple TV. Companies that consistently grow revenues do so with a diversified portfolio of growth strategies. 

That’s enough analysis on the keys to victory. Time to play the game. Go Butler!

Noah Grayson
Walker

1. Intelligence generation. The ability of firms to gather and understand customer preferences and needs along with the market forces affecting their needs and preferences now and in the future. All key functions in the company need to be involved in generating market intelligence. Market factors like the competitive landscape, the pace of technological change, and general economic conditions are of equal importance as customer intelligence.
2. Intelligence dissemination. Market intelligence needs to be communicated, disseminated, and sometimes even sold to all relevant departments and individuals in the organization. This dissemination is symmetrical - flowing to and from all relevant departments.
3. Responsiveness. This is the key action step. Unless an organization is capable of changing processes, products and services based on good market intelligence, it will never realize the rewards of being a market oriented company.

1. Re-centering on customer centricity
2. A broader orientation for being customer-focused
3. Characteristics of a customer-focused company
4. The focus of customer-focused companies
5. The moderation of customer focus

A recent Harvard Business Review article suggests a new management paradigm is developing. In “The Age of Customer Capitalism,” Roger Martin provides a brief history of management theory; simply put, Martin calls out two periods of managerial capitalism to date:

1)      Management Capitalism This period, which started in the early 1930’s, created the notion of professional management, prompted by the work of Adolf A. Berle and Gardiner C. Means, whose book The Modern Corporation and Private Property made the case for management that was separate from ownership of the firm. This work ushered in a period in which management became a valued discipline by creating processes and roles that help to fuel the economic growth of firms. It could be said that by creating the division of labor between owners (who are, ostensibly, more entrepreneurially-oriented and therefore more focused on the vision of the firm) and management (who are more oriented toward building systems and infrastructure that facilitates the realization of the vision), firms leveraged the unique skills of individuals in a way that was not only scalable, but also increased the probability of firm success.

2)      Shareholder Value Capitalism The second period emerged in the mid-1970’s, when Michael C. Jensen and William H. Meckling  suggested in their article “Theory of the Firm: Managerial Behavior, Agency Costs and Ownership Structure” that managers focused on their own financial well-being at the expense of the firm (and, therefore, shareholders). This work (along with other management-critical treatises such as The Peter Principle: Why Things Always Go Wrong, which posited that managers in a firm advance to their level of incompetence) created a skeptical view of management; Jensen and Meckling suggested that a better focus for the firm would be shareholder value maximization.

Professor Martin suggests that shareholder value capitalism is also a flawed theory, and provides some compelling evidence that the shareholder value paradigm did not pay off for shareholders (in short – between 1933 and 1976, when management capitalism was king, the S&P earned compounded annual returns of 7.6%; between 1977 and 2008, during which shareholder value capitalism has been in vogue, the S&P created compounded annual returns of 5.9%). Further, Martin argues that shareholder return cannot increase in perpetuity.

So, what is a firm to do? Martin suggests that the answer is Customer Value Capitalism – that is, the path to shareholder value creation comes by maximizing what we at Walker call customer loyalty. In Professor Martin’s words:

“…companies should seek to maximize customer satisfaction while ensuring that shareholders earn an acceptable risk-adjusted return on their equity.”[1]

Why can’t the firm focus on both customer value as well as shareholder value? Professor Martin provides two arguments. First, from the perspective of optimization theory, you can only maximize one variable while controlling for all other variables. While this is technically correct, the second reason cited is more compelling – shareholder value reflects the value stockholders place on the company’s future earnings, and it is impossible to any firm to continuously raise –and deliver on – expectations. If we assume that customers are the source of all future earnings, then logic would suggest that maximizing customer value would be the best way in which to maximize shareholder return in the long run.

Do the data bear this out? Professor Martin provides some anecdotal examples in support of customer capitalism; we can add several more from our work with clients (many of which we have previously discussed in this blog - see this entry and this entry for more information):

1)      We continue to see a statistical connection between what customers say they will do and what they actually do;

2)      We have witnessed the correlation between a customer’s loyalty and his/her revenue growth rate, profitability, willingness to buy across a firm’s multiple categories, etc.

3)      The Walker Index, a composite of Walker’s publicly-traded customers, continues to outpace the broader market indices in total (see this entry for more discussion on the Walker Index);

In addition, the academic literature provides analysis consistent with what we see in our client work.

However, the notion of Customer Capitalism is another example of easy strategy that is extremely hard to execute. In my next blog, I’ll look at some of things firms should be mindful of – and prepared to do – if they aspire to adopt the strategy of Customer Capitalism. In the meantime, what do you think – what has worked in your firm (or what have you witnessed as a best practice among firms, brands, or products that you use)?

Mark A. Ratekin
Sr. Vice President, Consulting Services & Resource Management

• We will understand where we have financial security (and risk) in our customer base.
• We will understand who our most valuable customers are.
• We will understand what potential revenue gains exist among our current customers.

• Changing economic conditions;
• Regulatory changes in your market;
• Competitive forces – new entrants, exiting competitors, supplier influences, resource constraints, etc.
• Changing consumer tastes; We recommend taking a fresh look at your program every couple of years to see how things are changing in your environment (and we need to revamp in the program to keep it fresh, relevant, and impactful).

• How do we define an account – one person or many people? One customer organization or entities within that organization?
• Should our sample mirror our revenue composition? If so, do we weight results, control the sample, or both?
• Do we have access to (and can identify) all relevant customer contacts? Should we differentiate by decision role, for example?

What is the primary difference between your company and the global market leader in your industry?  If you are, in fact, the global market leader in your industry, what separates you from all those that are gunning for you?  I’m sure there are a variety of thoughts and opinions and debatable responses to these stated questions, but one thing will hold true regardless, if you aren’t linking the voice of your customer into your primary business objectives, you are not one of those on top.  What separates those companies from the rest of the pack?

They get it. 

They understand the basic fundamentals and the complex execution & analysis needed to become global powerhouses, industry leaders, organizations that exemplify greatness.

In my line of work, I meet regularly with corporations that create, support and sell products and services that, many times, you and I are very familiar with as consumers, some of their products/services are used by us, our employer, our family, friends, competitors, colleagues, etc. on a daily basis.  These are usually companies with customer-focused leadership, impressive market share and very clear customer related growth objectives in mind.  The companies I speak with usually realize there is an issue, a serious issue that is impacting the overall shareholder value of their organization and at the end of the day; they separate themselves from each other by those who execute and those who don’t see the sense of urgency around the matter.

That leads to the general point of this blog – How can organizations NOT put a sense of urgency around analyzing the voice of their customer and expect to achieve the greatness that so few corporations ever make it to?  I’m talking about the elite group that all others strive to be like.  I wonder if it is related to…

• We can’t get out of our own way
• We have issues with execution
• We change our strategies like the weather
• We are too big and bureaucratic to move with any nimbleness and effectiveness

I challenge you to share your perspective on what causes this “bottleneck” in the good to great process.  I have no expectation of these thoughts changing anyone’s perspective and my guess is that most will read this and think “Man, I’m glad that’s not us!” But know that if you made it to this point in the blog, one of three things has just occurred:

1. You realize that you are fortunate enough to be part of one of these elite organizations that has a true understanding of the impact of your customer on your business.
2. You have just left the denial stage and reached the resentment/anger stage
3. You just just escaped the monotony of your life for 60 seconds.

Are your customers saying, “They get it," when they speak about your company? If not, you should probably get to that sometime tomorrow.

Thoughts?





Michael Good
Vice President
Walker Information

This is the second posting in a four-part series on business insights.

My first posting in this series introduced the reader to a recent article on extracting business insights from data, presented their definition of an insight, and laid out some of my thoughts on the importance of business insights. As a reminder, this series of posts will not be summarizing the entire article (you should read it for yourself) but will extract and expand upon specific points I find most interesting or compelling.

Let me restate the definition of an insight here as a starting point for part two of this series.

A thought, fact, combination of facts, data and/or analysis of data that induces meaning and furthers understanding of a situation or issue that has the potential of benefiting the business or re-directing the thinking about that situation or issue which then in turn has the potential of benefiting the business.

Embedded in this definition is the assumption of two different types of insights.

1. Insights that support a specific decision or provide additional understanding of a specific situation or issue and will directly benefit the business.
2. Insights that enhance market understanding or strategy definition without directly impacting a specific decision.

I’m a baseball fan (as hard as it may be these days). I played a lot of baseball when I was younger and now just watch from a safe distance. Baseball players are a funny breed. Superstitions, nicknames and pranks are all part of the clubhouse culture. To this day, I still have to put my right shoe on first…not sure why, it’s just one of the sports gifts to me.

One of the other things intertwined with baseball, even more so today, is the use of data in the decisions that are made during games. As a pitcher, I used to hate getting close to the 100 pitch mark because I knew the coaches’ questions would start coming: How do you feel? Are you getting tired?

They knew exactly when I’d start wearing down. The signs to look for – pitches getting up, breaking ball not as sharp. I always thought they pulled me because of what was happening in the moment, their feel for the game, years of experience. Not unlike great account managers who can read people and feel their way through situations. It’s just a natural gift, right? But the real answers came from hours of preparation and analysis. These guys had collected and analyzed data on every opposing batter – batting averages versus right or left-handed pitching, ability to hit pitches in every part of the strike zone, ability to hit with runners in scoring position. You name it. They had analyzed every piece of available data to better predict when things might go terribly wrong for me. And much to my disappointment, they were usually right.

As strategic account managers, we utilize publicly available information on our customers to help us isolate a business challenge, determine their future strategies, or uncover industry key success factors. But wouldn’t it be valuable to have even deeper insights on how our key contacts were likely to respond to new offerings, understand how they view us relative to our competitors, and know what they truly value and are willing to pay for? Collecting information on the customer perspective and effectively analyzing it can help us understand what pitch we need to throw to get the third out.

Noah Grayson
Senior Vice President, Strategic Accounts
Walker Information

Sometimes it helps to have a framework.

Frameworks are useful when you are trying to sort out a problem or figure out an issue. Say you’re trying to develop a business strategy. A common place to start is to do a SWOT analysis to assess your Strengths, Weaknesses, Opportunities, and Threats. This is just one popular framework to help make sense of things.

Let’s apply it to customer loyalty initiatives…

For any voice of the customer program to be productive it must prompt action and generate results. For that to happen, employees must be engaged. Below is a framework we use that helps figure out what needs to happen to get employees engaged and supporting customer relationship strategies.

• Awareness – are people even aware of your customer listening program? If they don’t even know it exists, you can be darned sure it is not going to generate much action.
• Understanding – do people get it? They may know about the program, but they may not know what you’re trying to achieve, how it works, and what they are supposed to do.
• Belief – do they really believe in it? Do they feel the feedback from customers is credible? Stakeholders need to be convinced that the customer insights are valid and that the program will make a difference.
• Action – Once your people are aware of your voice of the customer program, understand their role, believe in the information, they are much more likely to take action to build customer loyalty and increase customer retention. 

We call it the Hierarchy of Engagement. This framework helps figure out what must be done at each level to engage your stakeholders to prompt action and deliver results.