Addressing Barriers to Success – Process (Moneyball anyone?)

Have you ever heard the following question when trying to solve a business issue? “What is the issue? We have always solved this problem this way!” We hear this type of response from many companies when talking about building laser focused performance strategies using analytics and big data.

The good news is that we also have found companies that have leaders that are Champions for Change. However, their biggest frustration is the resistance they encounter to a new idea or new way to solve a problem.

“That would be a huge change in the way we do business”

“We’ve never done it that way”

“We aren’t ready for this”

The same was true in the movie Moneyball portraying Billy Beane, General Manager of the Oakland Athletics (played by Brad Pitt). Billy didn’t have the payroll to compete with the big city teams like New York and Boston. What he and every team had was an abundance of data on players in the major and minor leagues. Beane challenged his staff to fill playing positions in a new way. Beane focused on player selection based on a specific type of performance analytics called Sabermetrics. Billy found value in players that other teams did not see. Do you remember the scene?

The Oakland A’s used analytics in new ways to identify young players or out of favor players who are more productive offensively and defensively. They defied conventional wisdom and built their Team using a new form of analysis and the data that was available. They go on to win their division. The poorest team in baseball with the smallest budget wins. That is a truly remarkable story.

The story doesn’t end there. As the A’s continue to win, players start to be recognized as stars. The A’s also begin to see performance issues with some of their players. So they make trades with other teams who evaluate players the same way they always did. For the emerging stars, the A’s get new talent and give up players they couldn’t afford to pay anyway. For the slipping players, they avoid the down years and rebuild the team. So the A’s end up in the hunt, winning, year after year.

What was different? Billy Beane decided he would change the decision making process of selecting players with the use of a new form of performance analytics BEFORE anyone else. He met incredible resistance because no one had ever done it that way before. He championed its use in the organization even though most of management wanted to do business the old way.

All companies are hoping to get meaningful value from their analytics and big data initiatives. Unfortunately, many lack the energy to get the full value by breaking away from established decision making processes.

Integrated Business Planning (IBP) is the practice of embracing descriptive, diagnostics, predictive and prescriptive analytics with big data to enhance or change specific business processes in order to outperform the competition.

Do you want to be the leader in your company and industry, even in the face of fierce resistance? Are you willing to be the champion early in the game? In many organizations this is exactly what it will take. Just like Billy Beane, after others catch on, the use of actionable analytics will be the norm and the competitive advantage of moving first will be lost.

The smart companies will lead from the forefront using an IBP platform tailored to their specific business needs!

One caveat. Just because you adopt the use of IBP analytics and big data does NOT mean Brad Pitt will play you in a movie. But then, maybe he would.

I would love to hear your thoughts.

All the best,

Richard

Richard Sharpe is CEO of Competitive Insights, LLC (CI), a founding officer of the American Logistics Aid Network(ALAN) and designated by DC Velocityas a Rainmaker in the industry. For the last 25 years, Richard has been passionate about driving business value through the adoption of process and technology innovations. His current focus is to support CI’s mission to enable companies to gain maximum value through specific, precise and actionable insights across the organization for smarter growth. CI delivers Enterprise Profit Insights (EPI) solutions that enable cross-functional users to increase and protect profitability. Prior to his current role, Richard was President of CAPS Logistics, the forerunner of supply chain optimization. Richard is a frequent speaker at national conferences and leading academic institutions. His current focus is to challenge executives to improve their company’s competitive position by turning enterprise wide data from a liability to an asset through the use of applied business analytics.

Addressing Barriers to Success – People

Recently I was listening to and interview on Bloomberg Business with Eric Schmidt, Executive Chairman of Google, and Civis Analytics CEO, Dan Wagner. They were talking about the power of big data and analytics. The interview was entitled “Why Data Analytics Is the Future of Everything”.

Their message was very clear. Coupling effective analytics with big data can change everything from the creation of corporate strategies to the way that people vote!

This is certainly a hot topic in the Supply Chain industry. In a recent benchmark study done by SupplyChainDigest™, 88.3% of the company participants said that the potential value that they could derive from analytics was a good or outstanding opportunity. However, 63.9% of the same participants noted their analytical capabilities were very basic or not advanced. Only 10.7% felt that their analytical capabilities had moved to an advanced level.

So what is holding back companies in developing the capabilities to actually realize significant value from analytics and big data? It boils down to the same three cornerstones or building blocks of every effective solution; the People involved, the Processes they follow and the Technology selected to enable the solution. Therefore this posting is the first of three. Today we will address People.

Let’s start with the top of the organization, the Executives. Every Executive makes decisions based on the best information available at the time they must decide, even when they know the information is lacking or incomplete. Every Executive would say that they value meaningful and actionable insights that could help formulate and lend support to corporate strategies. Strategies that help drive higher profits and / or gain market share. However, here are a few questions:

Are they willing to be a first mover within their company to invest in the effort for advanced analytics (see earlier Change Agent blog) or are they waiting for others to take this initial step?
Are they communicating their support to the organization so that everyone knows that creating effective analytics is a high long-term priority for the business?
Finally, are they creating ways for the organization to celebrate the ongoing success that is being realized through this investment?

Let me share a story from the time when I was the President of CAPS Logistics. CAPS was on the forefront of creating supply chain optimization solutions and served over 16% of the Fortune 500. We were finalizing a deal with a large corporation for a national deployment of routing and scheduling software.

The CFO of a potential client organization and I were in my office finalizing a deal and the deployment plans. During the conversation, the CFO stated that he had a particular deployment approach that he wanted to use. I listened carefully and certainly wanted to make him happy and to close the deal. However, I knew this approach would not work and diplomatically told him so. Needless to say, he was not happy and said it was either his way or no deal.

Normally, one does everything they can do to satisfy the customer but in this case I could not justify his substantial investment in a plan doomed for failure. The CFO left my office with no deal being finalized. The next morning, I received a call from him asking that we meet again. Later, he shared that he respected the fact that we were so confident about the right way to do this and that he wanted to follow our plan. That result lead to 5 national deployments of the software and he became the most active executive in our customer base to find clever ways to communicate to the entire organization the strategic value of this effort. The CFO was a barrier to the organization’s success, but it was good that the CFO caved in and broke through the barrier.

People issues extend beyond the Executives. What about the people that are actually performing the analytical activities? In many cases, the most meaningful results from the application of analytics will be gained if the analysis is done by Business Users not Data Scientists (see earlier blog on business users not data scientists). To ensure that maximum value is derived from your analytics and big data initiatives, your Business Users need to:

Have a good working knowledge of the business in order to recognize opportunities that are uncovered through new insights on customers, products or channel performance.
Have received the proper training on how to integrate analytics into their problem solving skills versus self-taught, hands on training
Have confidence that the data they are using is valid so that they remain on point in answering specific questions and solving prioritized problems versus having the distraction of defending their analysis to the data nay-sayers.
Be open to working with their cross-functional counterparts to involve them in the analysis and to share analytical results to take advantage of enterprise based tactics and strategies versus “siloed” decisions.

Politics, cultural norms and / or just the reality of different personalities can also pose issues as you advance your organization’s capabilities to drive profit improvements through the use of advanced analytics. The key is to find ways to work through any of these issues in order to obtain a “win” for the organization that helps build excitement, buy in and momentum. Eric Schmidt firmly believes that coupling effective analytics with big data will change everything. If you believe in the wisdom that has driven Google’s success, these changes will lead to organizational wins that demonstrate financial performance improvements and that solidify the organization’s commitment to analytics and big data.

Everyone likes to be on a winning Team. If your people issues are addressed, you will be better positioned to continue to build financial success stories using analytics and big data.

I would love to hear your thoughts.

All the best,

Richard

You Are Going To Have a Heart Attack!

Recent research that I have read suggests that there is still a lot of confusion and questions about Integrated Business Planning (IBP) analytics. Questions like “what does predictive analytics really mean and what is its actual business value?” This is completely understandable given the amount of attention this subject is getting in the media. Let’s demystify the industry buzz using an analogy, your health!

There are multiple forms of IBP analytics: Descriptive, Diagnostic, Predictive and Prescriptive. Here are two situations that are offered to help explain the purpose and value of each one:

Doctor – you go to your Doctor because you have had a sharp pain in your left arm several times this month. We will label this situation with the abbreviation (DR).

Business – you have a problem with the profits being generated by a business unit. Sales (top line) growth is up but profits are down. We will label this situation (BU) for Business User.

The following compares how each form of analytics can be sequentially used to support your personal health as well as the profitability of your business:

Descriptive Analytics (what is the problem)

(DR) – Analysis of the test results shows that you have a 50% blockage in part of your left coronary artery
(BU) – Analytics show that for the last 4 quarters over 22% of your customers have consistently been unprofitable

Diagnostic Analytics (what caused the problem)

(DR) – The reason for this extensive blockage is a buildup of plaque in the circumflex artery that is a result of a lack of exercise and a poor diet
(BU) – These customers have been consistently unprofitable because of the discounts they receive and the cost to service their orders

Predictive Analytics (what impact will continue if the problem is not addressed)

(DR) – If you don’t exercise and change your diet, then there is a 90% chance you will have a heart attack in the next two years
(BU) – If a changes are not made to these customers’ discount structures and how we handle their expedited orders, profits will continue to plunge next quarter

Prescriptive Analytics (what solution steps need to be taken to address the problem)

(DR) – Based on current research of different scenario results, your best option is to do aerobic exercises for one hour, 3 times a week and to reduce the amount of fat in your diet by one half
(BU) – Looking at different options considering the various order mix patterns for these and other similar customers, the best strategy is to implement a revised discount structure and different guaranteed service commitments to make these customers profitable

Monitoring Analytics (what were the results of implementing these solution steps)

(DR) – The new test results indicate that your artery blockage is almost completely gone!
(BU) – This quarter’s performance shows a reduction of total unprofitable customers to a level under 7% and a quarterly earnings increase of over 9%!

Most companies do some form of analytics today and I hope that the analogies offered above bring clarity as to how you might expand your current and/or future applications to help drive performance improvements. Regardless of where your company is in the “analytics journey”, three things are very certain:

There will be an ever increasing amount of data that can be used to add value if you learn how to master that data to create “One Version of the Truth”
The sequence of how you apply your IBP Analytics is critical and will determine how you build knowledge and reduce “analysis paralysis” to drive meaningful results as quickly as possible
Your IBP analytics should be designed for cross-functional business use to maximize the value you gain from those insights

Integrating these considerations in your analytical plans will minimize the possibility of having an organizational heart attack. Your business will be stronger and healthier and your shareholders will be continually pleased with a positive growth in quarterly earnings!

I would love to hear your thoughts.

All the best,

Richard

We Have Always Done It This Way . . .

In this blog, we will address how to maximize the value of analytics and big data. A lot of attention is being given in the media to both of these topics. What is not being discussed much is the basic question:

Is your organization ready to actually embrace making decisions and setting strategies based on new operational insights and facts versus on traditional information, experience, tribal knowledge and/or opinions?

Let’s assume that your organization has invested in the ability to gain meaningful insights about your internal operation, your customers and the marketplace from analytics and big data. You are now at the Intersection of Change to integrate this information into your business decision making processes. How will your organization act? Will those insights be fully embraced, cautiously considered or mostly ignored?

Naturally we are not discounting the value of using experience and knowledge of the business in making smart decisions and setting future business strategies. However, companies now have the opportunity to embrace the insights gained from analytics and big data and use that experience to create cross-functionally developed strategies that break functionally siloed decisions! Decisions that will benefit the financial performance of the enterprise and not just specific functional operating metrics.

Let’s think objectively about your organization’s ability to facilitate change. Which of the colors below would you assign them?

My guess is that most companies, if being honest, would assign their organization a red or yellow rating. Therein lies the problem.

In order to get the most value out of your investments in analytics and big data, you must provide the leadership and commitment to address change management issues. Often, it takes the leadership and courage of one person to say, “Just because we have always done it this way, doesn’t make it the best way, or the only way…we can do better!” We call this person, the “Agent of Change.”

During the transition, the organization will push back. There are always reasons to return to the older, more comfortable way of doing business. The organizations that recognize that the wisdom of senior management will be improved and more highly prized when using analytics and big data will be the ones that gain significant competitive advantage. Those who do not have “Agents of Change” will see very little in the way of ROI from the analytics and big data investments.

Here is a great source for Change Management best practices: Harvard Business Review

Are you ready to be the “Agent of Change”?

All the best, Richard

Maximizing Your S&OP – IBP Profit Contributions

There is a lot of discussion in the market about Sales and Operations Planning (S&OP) and Integrated Business Planning (IBP). One line of thought is that companies with mature S&OP programs will naturally evolve to include enhanced IBP capabilities. I have a separate view and believe these two important business activities serve different but complimentary purposes. Regardless of where you are on this issue, the question is “How do I get the maximum value out of S&OP and IBP activities that will continue to positively impact the bottom line?”

What does that have to do with analytics and big data? Well just about everything. Regardless of how you are addressing your S&OP and IBP business requirements, they both require the support of user driven analytics that utilize cross-functionally validated data. Getting this right provides tremendous synergy not only in supporting both of these critical business needs, but in growing sales, cutting costs, expanding market share and therefore increasing the profit of the enterprise.

Let’s start by looking at a simple definition for each:

Sales & Operations Planning – a single operating plan that has executive commitment that allocates critical resources to most effectively satisfy customer demands in a profitable way.

Integrated Business Planning – planning, implementation and monitoring activities that focus on the identification of specific improvement opportunities (strategic or operational) related to a product(s), customer(s), channel(s) or an operating region to continually improve financial performance and/or gain market share.

To be most effective, both S&OP and IBP require strong collaborative and cross-functional decision making processes. Decisions that are based on accurate insights regarding historical performance (descriptive and diagnostic analytics) as well as anticipated customer and business requirements (predictive and prescriptive analytics).

As I have commented in earlier postings (earlier posts here) descriptive, diagnostics, predictive and prescriptive analytics must be based on accurate and validated data. Many companies are struggling with how to turn their data from a liability into an asset. For those companies, this issue will only grow as more and more sources of data are made available to support various forms of decision making activities. If you are not proactively addressing this issue, it will significantly impact the capability of your S&OP and IBP activities to drive the value that you should expect from these business activities.

How many times have you been involved in an S&OP meeting where everyone brings in their laptop and sits down to start the meeting? The discussion focuses on the fact that there were large variances in the plan developed in the last S&OP meeting versus what actually occurred operationally. For the first half of the meeting, people offer different explanations and opinions on the variances based on their analysis using the disparate data available to them. Alternatively, everyone could have had advanced information with regard to exactly what happened and the “root cause” of why it happened. The focus at the start of the meeting would then be to discuss these facts and decide on a course of action.

To gain the most value in your S&OP and IBP activities business users must be empowered by having access to meaningful analytics that rely on one source of consistent, validated data and that support cross-functional planning, execution and monitoring activities. Get it right, and you won’t start your meetings trying to ‘convince’ others why variances happened. You will walk into your meeting understanding specific performance details. Get it right and your meetings will be based on fact based discussions leading to the adjustments that you should make to drive positive impact. Impact that is measured by ongoing contributions to financial performance, i.e. shareholder value. Value that drives competitive advantage!

I would appreciate hearing your thoughts and comments.

All the best, Richard

Sustainable Profit Growth

If you have been following this blog you know that the emphasis is to encourage companies to work smarter in their mission to drive shareholder value through a sustainable growth in profit performance.

I know that this seems like a no brainer but the reality is that companies are often trying to achieve this mission with limited visibility to the real drivers and inhibitors of profit performance. Everyone has the P&L. However, I find that most companies today cannot easily peel back that onion to have very specific and actionable insights for a specific customer or product that can make an immediate and measurable profit impact. Instead, by default, strategies are often developed using a “one size fits all” approach. The common mantras are “cut costs” and “increase sales” to increase overall margins.

However, there is a growing level of need to tackle this problem. And while it is rarely articulated, the real solution is to increase profits by truly understanding the product and customer profit “winners” and “losers” and to group or segment them in order to create specific strategies that increase their profit contributions.

Customer and product segmentation activities are a very hot topic in the industry today. What successful companies are doing differently is developing the capability to better understand how customers and products differ in their profit performance. Intelligent segmentation activities support the fundamental need for companies to work smarter, not necessarily harder, to increase their quarterly earnings and shareholder value, and quickly.

How do I approach customer and product segmentation activities? Let me offer three straight forward questions that I hope will be helpful. Empowering the organization to be able to answer these questions will lead to smart decisions to create sustainable growth in profits:

Where do I specifically make and lose money with my customer transactions and what is causing the specific profit performance spectrum (selling price, discounts, cost to serve, etc.) by individual customer, channel and region?
What specific actions can I take right now to increase the profit contributions by product and/or by customer?
Once specific actions have been implemented, are these specific strategies for a customer, product, channel, and/or region working and having a direct positive impact on their profit performance?

Product and customer segmentation activities are critical areas of focus for effective Integrated Business Planning (IBP) solutions. Developing this organizational capability provides immediate and sustainable value. Value that drives competitive advantage!

I would appreciate hearing your thoughts and comments.

All the best, Richard

Where’s the beef?

With all of the attention being given to analytics and big data, the question that I often hear is:

“How are companies really solving specific business problems using analytics and big data? Talk to me about the real and sustainable value that companies are finding by investing in analytics and big data capabilities.”

To coin a phrase made popular years ago by a fast food chain “Where’s the beef?”

In earlier blog postings, I explained how analytics, coupled with accurate and specific data, can be used to facilitate cross functional decision making that is based on facts, not allocations, estimates or opinions. Moving beyond “siloed’ data and decision making processes can create a real advantage in driving increased financial performance. This advantage becomes a competitive differentiation that is based on factual insights across the entire enterprise versus departmental decisions that are based on isolated operating metrics.

Navigating in today’s complex business environments requires the ability to make smarter, pinpointed decisions. The myriad of systems with segregated data often make it difficult to have the right information that is needed. Better decisions are driven by having complete visibility across the enterprise. With that visibility, very specific strategies by region, individual customers, product categories, SKU’s or channels can be tested, deployed and monitored. This avoids the trap of trying to force a 'one size fits all' policy decision based on incomplete data both before and after the decision.

So assume for a moment that your company has defined very specific profit improvement goals that are not being met. You have a cross functional team assembled. You have all of the data you need, not just from one system but from EVERY system. The data is accurate and complete. There is no organizational anxiety about its source or validity. With the proper analytics and data, you would want to simply and quickly answer the following questions:

What are the specific and detailed facts that offer insights regarding this current lack of performance? (Descriptive Analytics)

Considering the end to end operation, what caused this performance to happen, i.e. the root cause that drove this performance? (Diagnostic Analytics)

What would be the financial impact if we make these very specific cross functional changes? (Predictive Analytics)

What other options do we have that the team has not considered or that are too complicated to completely define currently? (Prescriptive Analytics)

It might be utopia for your company, but not for companies that have successfully developed Integrated Business Planning (IBP) solutions through the proper alignment of analytical and data capabilities. Having this organizational capability provides immediate and sustainable value. Value that drives competitive advantage by showing “Here’s the beef”!

I would appreciate hearing your thoughts and comments.

All the best, Richard

“Who’s” on First, “What’s” on Second, “I Don’t Know’s” on Third

Many of us remember the great comedy routine by Abbott & Costello “Who’s” on First, “What’s” on Second, “I Don’t Know’s” on Third. If not, take a look at this YouTube link for a quick laugh:

So what does this have to do with Big Data and the value that can be derived through meaningful business analytics? Well just about everything. In the Abbott & Costello routine, the names of the players on the bases are creating miscommunication and confusion. The same confusion can often be seen when companies are trying to derive meaningful insights through Big Data initiatives.

Big Data initiatives that create “One Version of the Truth” are more successful in driving strategies that are actually implemented and that have significant financial impact.

Here are three considerations to help drive One Version of the Truth to achieve success and the realization of significant financial impact through the use of analytics and Big Data:

Cross-functional participation is critical. This is especially true in defining the objective (intent of the effort), reaching agreement on how the Big Data is going to be used (repurposed), determine the sources of the data and the data validation process. Cross-functional consensus early in the process can help eliminate the analytical results being questioned and or dismissed. Without cross functional participation, you minimize your chances at finding One Version of the Truth and achieving success.

Assuming the result you are seeking is an ongoing need of the business, it is important to recognize early on that your Big Data approach must be sustainable. This means that the sources of the data, the rules on how data is going to be used and the way that validation occurs are repeatable and consistent. Not giving this the right level of priority is a sure way to lose the organization’s confidence in the ongoing results. You don’t want to create One Version of the Truth once, you need to be able to create it every time.

Big Data initiatives need to be very intentional with regard for the desired result. Hoping to find those nuggets of gold by wandering around a landscape containing masses of data is futile. One Version of the Truth eliminates turf battles and highlights not just nuggets but veins of gold.

Naturally there needs to be flexibility to make changes but ensuring that the above considerations are applied is critical.

For those that don’t agree, consider the following: how many times have you been involved in a project where the work that was done was solid but at the close of the effort someone objects to the results? Their argument is that they don’t trust the data that was used or agree with the analytics approach that was taken. Yep, one step forward, two back and then the nail in the coffin.

No one wants to be associated with a career ending project that fails. Following the three considerations above can help. Otherwise you may find yourself answering the question from others in your company “Who’s on First”?

I would appreciate hearing your thoughts and comments.

All the best, Richard

Roadkill – How To Avoid Being Crushed By Data

Imagine that you are having a dream that is quickly turning into a nightmare. You find yourself standing in the middle of a newly constructed super highway. You are amazed at the vast number of lanes on both sides of this man made structure. You have been told that you are there to find out how drivers are performing on these lanes with accurate measurements and to report back meaningful insights. To do this, you are to utilize your computer, camera and a smart phone.

As you stand there trying to get your bearings, you notice the following:

the volume of the cars moving in each direction is significantly increasing over time
cars are entering from a variety of new entry points
the speed of the cars is exponentially increasing to a point that what you are seeing is turning into a blur

You feel helpless using the tools that you have been given and cannot see how to possibly do your job. In fact, you realize that if you are not careful, you could become so confused that you could put yourself in harms way and become a roadkill casualty!

Sound silly? I am sure it does but replace the road lanes with data streams coming from a growing number of sources and at an ever increasing rate of speed. Add the pressure of a rapidly changing commercial environment and the need to gain meaningful insights to stay ahead of the competition or to be left behind in the commercial dust. It is not too much of a stretch of the imagination.

Recently, I watched an interview of Thomas Malone, from the MIT Sloan School of Management on DCV-TV. The interview concerned his prediction 25 years ago on the emerging role of e-commerce.

Mr. Malone made several interesting observations about how successful organizations will operate and win using ever increasing amounts of data:

by harnessing the power a collaborative approach between man & machine where both contribute and learn from the work of the other (“collective intelligence”)
by creating an environment to empower the individual to use data and computing power to solve critical business needs (e.g. Google and eBay)

These are directly applicable to any company’s strategy in getting the full benefit of the ever increasing volume and speed of data and to obtain a competitive advantage over your competition.

Let’s build on Mr. Malone’s thoughts and go back to our analogy of not being “roadkill” on your data super highway. How many of the following are true for your organization?

You have cross-functional consensus on the value of measuring specific areas of performance
You have a technology platform provides one “One Version of the Truth” of information captured from ever increasing sources and volumes of data
You have created a user environment that empowers individuals to continually gain insights by applying their creative skills in addition to taking advantage of advanced computing correlations and learnings (“collective intelligence”)
You have recognized that your approach must be scalable and repeatable for sustained value
You periodically highlight to the organization the value that has been gained by the effort

The world today is full of examples where relatively young companies are outpacing traditional competitors in multiple industries by changing the game of how to win market share.

I read recently that certain state Department of Transportation organizations are experimenting with recycling roadkill into compost as a cost savings initiative (click here for article).

Companies that take on the challenge of mastering their data and empowering individuals with various forms of intelligent analytics will not need to worry about being someone else’s compost. For everyone else, there are no guarantees. Like Mr. Malone said, just look at Google and eBay!

I would appreciate hearing your thoughts and comments.

All the best, Richard

Show Me The Money – Building Organizational Momentum

Show Me The Money - Building Organizational Momentum

Continuing the theme of Big Data initiatives need to be very intentional, we now turn our attention on how to build momentum by focusing on examples of how companies are financially benefiting from their successful efforts with Big Data. Specifically, let’s talk about three areas that are getting a lot of attention in many companies.

Product Segmentation – having accurate insights with regardto how a particular product is performing with regard to contribution to profit can be eye opening. Forget the expected “bell-shaped” distribution curve and expect to see more of a skewed left hand spike (left is negative or marginal behavior) and a prolonged tail of the curve to the right. Couple this with where the product falls in its product life cycle and you have the tools necessary to drive actionable steps to dramatically impact financial performance. This has been demonstrated in multiple industry with astonishing results. You may be saying, “Yes but we have to have product x to sell product y”. That may be true but what if the customer is “cherry picking” and you actually have an opportunity to identify where that paradigm just doesn’t hold water. Getting to these forms of actionable insights builds excitement and momentum for your Big Data efforts.

Customer Segmentation – talking about skewed bell shape curves, how about having over 50+ % of you customers performing marginally or continually being unprofitable. Want to fire them? Well possibly a better strategy would be to understand why they are unprofitable vs a minority of similar type customers who are contributing to the bottom line. A better strategy for some customers may be to determine how to get the marginal customers to emulate the behavior of the well performing ones. Moving away from a “one size fits all” customer strategy can offer significant increases in profit contributions.

Operational Realignments – no, we are not talking about a large, time consuming optimization project that will be difficult to accurate monitor the realized ROI due to unforeseen changes in the future. In fact, it is just the opposite. Identifying very specific and target changes using Big Data can yield impressive results and have the organization want to do more hunting for operation improvements. A recent example was the changing of certain inventory stocking decisions tied to customer demand yielded not only higher service levels but cut millions of dollars of cost out of the operation.

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The following compares how each form of analytics can be sequentially used to support your personal health as well as the profitability of your business:

Descriptive Analytics (what is the problem)

Diagnostic Analytics (what caused the problem)

Predictive Analytics (what impact will continue if the problem is not addressed)

Prescriptive Analytics (what solution steps need to be taken to address the problem)

Monitoring Analytics (what were the results of implementing these solution steps)

Maximizing Your S&OP – IBP Profit Contributions

Let’s start by looking at a simple definition for each:

I would appreciate hearing your thoughts and comments.

All the best, Richard

Sustainable Profit Growth

If you have been following this blog you know that the emphasis is to encourage companies to work smarter in their mission to drive shareholder value through a sustainable growth in profit performance.

How do I approach customer and product segmentation activities? Let me offer three straight forward questions that I hope will be helpful. Empowering the organization to be able to answer these questions will lead to smart decisions to create sustainable growth in profits:

Product and customer segmentation activities are critical areas of focus for effective Integrated Business Planning (IBP) solutions. Developing this organizational capability provides immediate and sustainable value. Value that drives competitive advantage!

I would appreciate hearing your thoughts and comments.

All the best, Richard

Where’s the beef?

With all of the attention being given to analytics and big data, the question that I often hear is:

“How are companies really solving specific business problems using analytics and big data? Talk to me about the real and sustainable value that companies are finding by investing in analytics and big data capabilities.”

To coin a phrase made popular years ago by a fast food chain “Where’s the beef?”

I would appreciate hearing your thoughts and comments.

All the best, Richard

“Who’s” on First, “What’s” on Second, “I Don’t Know’s” on Third

Many of us remember the great comedy routine by Abbott & Costello “Who’s” on First, “What’s” on Second, “I Don’t Know’s” on Third. If not, take a look at this YouTube link for a quick laugh:

Big Data initiatives that create “One Version of the Truth” are more successful in driving strategies that are actually implemented and that have significant financial impact.

Here are three considerations to help drive One Version of the Truth to achieve success and the realization of significant financial impact through the use of analytics and Big Data:

Naturally there needs to be flexibility to make changes but ensuring that the above considerations are applied is critical.

No one wants to be associated with a career ending project that fails. Following the three considerations above can help. Otherwise you may find yourself answering the question from others in your company “Who’s on First”?

I would appreciate hearing your thoughts and comments.

All the best, Richard

Roadkill – How To Avoid Being Crushed By Data

As you stand there trying to get your bearings, you notice the following:

You feel helpless using the tools that you have been given and cannot see how to possibly do your job. In fact, you realize that if you are not careful, you could become so confused that you could put yourself in harms way and become a roadkill casualty!

Recently, I watched an interview of Thomas Malone, from the MIT Sloan School of Management on DCV-TV. The interview concerned his prediction 25 years ago on the emerging role of e-commerce.

Mr. Malone made several interesting observations about how successful organizations will operate and win using ever increasing amounts of data:

These are directly applicable to any company’s strategy in getting the full benefit of the ever increasing volume and speed of data and to obtain a competitive advantage over your competition.

Let’s build on Mr. Malone’s thoughts and go back to our analogy of not being “roadkill” on your data super highway. How many of the following are true for your organization?

The world today is full of examples where relatively young companies are outpacing traditional competitors in multiple industries by changing the game of how to win market share.

I read recently that certain state Department of Transportation organizations are experimenting with recycling roadkill into compost as a cost savings initiative (click here for article).

Companies that take on the challenge of mastering their data and empowering individuals with various forms of intelligent analytics will not need to worry about being someone else’s compost. For everyone else, there are no guarantees. Like Mr. Malone said, just look at Google and eBay!

I would appreciate hearing your thoughts and comments.

All the best, Richard

Show Me The Money - Building Organizational Momentum

The above are just a small sample of how companies are driving increased momentum for their quest of improving financial performance using Big Data.

We would appreciate hearing your thoughts and comments.

All the best, Richard