Are Your Omni-Channel / E-Commerce Sales Really Profitable? Part 3

By Richard Sharpe | 05/18/2016 | 12:57 PM | Categories: Web/Tech

If you have been following this blog series, you know that we are focused on how to determine if your Omni-Channel / E-Commerce orders are really profitable. Multiple industries are struggling with this question, none more than the Retail industry, which is being turned upside down by virtual retailers. A recent Wall Street Journal article noted that consumer online purchasing has soared 10.2% over the past year, while department-store sales have declined 1.7%.

This posting is the third in the series on managing Omni-Channel / E-Commerce profitability.   We started by defining the four components of the Total Cost To Serve (TCTS) for Omni-Channel / E-Commerce orders:

  1. The cost to purchase or manufacture the products, often referred to as the product’s Standard cost
  2. The costs to position inventory to be ready for order fulfillment activities
  3. The costs to actually fulfill the Omni-Channel consumer order, and
  4. The cost of product returns

After defining these costs, we offered the straight forward profitability equation of: 

Omni-Channel Order Profit = Net Revenue – (A+B+C+D)

Today, we are going to specifically focus on the cost category C above.


The problem

Consumer expectations are moving more and more in the direction of rapid gratification. Consumers expect to find the exact product they are looking for at the best price and to quickly have it in their possession, often at no additional cost. So what is wrong with that? Well, absolutely everything if you are the company trying to get that consumer’s business. 

E-Commerce order fulfillment activities simply do not have the economies of scale of traditional supply chain operations. Generally speaking, E-Commerce orders require the picking and packaging of much smaller quantities of product and they have to be delivered to a much larger number of destination points, often for free. Adding to this perfect storm is the fact that “comparative shopping” often reduces the actual revenue derived from the sale. 


It is no wonder that many companies are asking the question: 
“Are we making money on our Omni-Channel / E-Commerce orders?”


As noted in an earlier posting, up until now the focus for many companies has been to create an Omni-Channel / E-Commerce presence in order to hold on to market share. But losing money on orders in this channel is often the result of imprecisely measuring the cost to fill the order. The shift must now be to manage the profitability of Omni-Channel / E-Commerce orders by having fact-based financial performance insights. 

The solution

The solution starts by recognizing the wisdom in the adage “one size does not fit all.” Customer buying patterns, order mix, discounts, promotions, and expedited deliveries all contribute to whether an E-Commerce sale is profitable or not. Therefore, in addition to the net revenue gained from Omni-Channel / E-Commerce orders, it is imperative to understand the true costs of each customer order-fulfillment activity. Knowing the exact profitability gained through these financial insights positions a company to change future online ordering offerings to insure profitability targets are met. 

How do you do that?  It starts with having specific and accurate facts regarding each part of the profit equation defined above. Using this information to segment consumer patterns and order related characteristics (quantities, mix, applied promotions and discounts, selling price, and applied delivery fees) is critical to clearly understand different profit contribution patterns. 

This profit intelligence can then be used to create informed strategies on how to influence the profitability of specific customer orders while continuing to build market share. Strategies such as restricting free shipping to consistently unprofitable customers or potentially providing different forms of order promotions to different segments of profitable customers can have an immediate impact on the bottom line. Yes, you may lose some customer orders, but most likely your competitor has just lost additional profits.

I would love to hear your thoughts.

All the best,


Are Your Omni-Channel / E-Commerce Sales Really Profitable? Part 2

By Richard Sharpe | 04/28/2016 | 1:29 PM | Categories: Web/Tech

Determining if you are making money through your Omni-Channel / E-Commerce sales is a complicated issue.  Today, the Consumer is clearly in control and many companies are actively seeking solutions which go beyond having an online presence and are focused on supporting smart strategies that create sustainable Omni-Channel / E-Commerce profits.

This posting is the second part of a multi-series blog focusing on Omni-Channel / E-Commerce profitability.   We started the series by defining the four components of the Total Cost To Serve (TCTS) for Omni-Channel / E-Commerce orders:

  1. The cost to purchase or manufacture the products, often referred to as the product’s Standard cost
  2. The costs to position inventory to be ready for order fulfillment activities
  3. The costs to actually fulfill the Omni-Channel consumer order, and
  4. The cost of product returns

After defining these costs we offered the straight forward profitability equation of:  Omni-Channel Order Profit = Net Revenue – (A+B+C+D)

Today, we are going to specifically focus on the cost category B above.


The problem

The cost to position inventory to be ready to fulfill orders is made up of three main categories; the transportation costs to get the products to the order fulfillment facility (both inbound and inter-facility related), the inventory carrying costs associated with the products (both in-transit and stationary inventories), and the storage and handling costs associated with the facility.  What is different about Omni-Channel / E-Commerce inventory positioning activities?  Simply said, it is the sheer number of configurations of inventory positioning that can be used to support Omni-Channel E-Commerce activity coupled with the need to be positioned closer to an exponential number of delivery locations.

Consumers have a growing expectation that ordered products should be delivered quickly and often at no cost. Since you can’t just “teleport” products from one place to another, the laws of physics kickin.


Supply chain translation - what should our order fulfillment network look like to serve a growing Omni-Channel / E-Commerce business?  What makes the most sense regarding the number and combination of roles for the facilities that are required to support this channel (centralized distribution, local area fulfillment, sortation to support the “last mile” delivery, additional “click & collect” options)?  In addition, how do we justify the additional investments in the people, processes and technology needed to operate these facilities?  All very good questions.  Each of these considerations can have significant impact on the ongoing cost to position inventory to be used for Omni-Channel / E-Commerce orders and the profitability of this channel.

Unfortunately, for many companies the focus has been to create an Omni-Channel / E-Commerce consumer interface with not as much attention being given to effective ways to fulfill these orders profitability.  We often hear the question “Are we really making money with our Omni-Channel / E-Commerce sales?” 


The solution

Yes, determining the right answer is not easy and the answer will change over time.  However, it boils down to the same old adage “One size does not fit all”! 

There will always be good arguments that certain investments have to be made to gain (or to not loose) market share.  However, it is a fact that not all of your Omni-Channel / E-Commerce consumers are the same as it relates to their contribution to your operating profits.  Patterns in order mix, quantities, discounts and the expected delivery timeframe can all create large swings in realized profits.  Segmenting consumer patterns to clearly understand different profit contributions is one step in tackling this problem.  This of course requires having accurate cost information for all four of the TCTS categories noted above. 

Having these financial performance insights can then support the use of effective analytics to explore the best network configuration(s) and inventory positioning strategies to manage profitable Omni-Channel / E-Commerce orders.  One caution, this evaluation process should be treated as being very dynamic.  As your Omni-Channel / E-Commerce business grows, scalability considerations can significantly change the answer.

Gaining and maintaining Omni-Channel / E-Commerce profitability is a complicated issue.  Having fact based insights regarding the actual true Total Cost To Serve (TCTS) and the Omni-Channel / E-Commerce order profit must be considered table stakes!

I would love to hear your thoughts.

All the best,


Are Your Omni-Channel / E-Commerce Sales Really Profitable? Part 1

By Richard Sharpe | 03/10/2016 | 10:57 AM | Categories: Weblogs

The shift of power to the consumer is turning much of the E-Commerce world upside down.  Consumers expect to be able to easily access specific product details, including product reviews, comparative pricing and multiple options for how to obtain the product and the speed with which they can have it delivered. 

Consumer expectations are rapidly driving Omni-Channels supply chains to become “pull” systems on steroids.  For many industries, it is changing the dynamics between manufacturers and retailers with many manufacturers and distributors building an E-Commerce presence. 

Everyone is trying to figure out the Omni-Channel puzzle.  The overarching question is how to satisfy rapidly growing Omni-Channel demands in a way that generates sustainable profits?   My conversations with supply chain leaders on this topic always lead to the same question:

“Are we really making money with our Omni-Channel / E-Commerce sales?”

This question naturally needs to address the revenue and cost considerations for Omni-Channel sales.  A future blog series will address the revenue considerations.  This posting is the first of a four part series on Omni-Channel / E-Commerce costs specifically focusing on the Total Cost To Serve consumer demands. 

We will break these costs into four categories:

  1. The cost to purchase or manufacture the product, often referred to as the product’s Standard cost
  2. The costs to position inventory to be ready to be used in order fulfillment activities
  3. The costs to actually fulfill the Omni-Channel consumer order, and
  4. The cost of product returns

So naturally we have the straight forward profitability equation of:

Omni-Channel Order Profit = Net Revenue - (A+B+C+D)

It is a simple equation but not so simple to calculate on a consumer order by order basis. 

There is a lot of attention being given to Cost To Serve models today. The key to success is to capture as much exact and verified data (Big Data) for each cost component and to use an analytical approach (Analytics) to tie these cost components together. Critical to this effort is to ensure that the approach builds organizational confidence and consensus in the cost calculations.

To keep the length of this posting reasonable, I will not devote time on the costs in the “A” bucket since this should be the easiest part of the equation.  Every company should know the cost to purchase and/or to manufacture the products they sell.  In the next three postings, I will devote specific and detailed attention to each of the other cost components and their direct impact on profitability.

The goal is to help answer that puzzling question “Are we really making money with our Omni-Channel / E-Commerce sales?” 

I would love to hear your thoughts.

All the best,


The problem is the data

By Richard Sharpe | 02/02/2016 | 10:28 AM | Categories: Web/Tech

“Harnessing the true power of data driven insight is the holy grail of future business.  A wealth of this data comes from the supply chain.  But, while the information is there, companies are not yet capitalizing on its real value as a source of insight capable of shaping the future of the enterprise.”

—DHL Supply Chain, Lisa Harrington, Senior Research Fellow – University of Maryland,
"The Predictive Enterprise: Where Data Science Meets Supply Chain"  (January 2016) 

With all of the talk about analytics and big data, why are so many companies still struggling with the adoption of new technologies and methodologies that harness the true power of data-driven insights? 

The reasons can vary, but the common complaint that I hear centers on data: 

Our data still sits in silos and it is difficult to integrate.   

We have pulled all our data together, but people still don’t trust it.  

As a large company, we have a long way to go to be able to support advanced analytics with the current state of our data.

Does this resonate with you for your company? If so, doing nothing to move down the path to gain this Holy Grail is nonsensical.  

This problem has been solved by many forward-thinking companies using advances in cloud computing solutions and focused methodologies. They took on the challenge and solved this “secret” to gain significant operating advantages. 

Take a look at the ROI figures from a recent Gartner research report, “Deconstructing Supply Chain Analytics,” by Noha Tohamy (also referenced in the DHL paper mentioned above).


After reviewing the ROI, make an honest assessment about your organization’s capability to use the power of analytics that exist today. Consider the competitive advantage of having one source of trusted data and the full use of business-focused analytics to transform your enterprise. 

If your problem centers on the state of your data, what is more important than to eliminate that barrier? The task may be significant, but it starts by recognizing that it can be done. Seek the support of your Senior Management to create a cross-functional Team charged with defining a road map that includes an ongoing data-governance process. If needed, seek outside assistance to help with the process. You will discover that it is not so much rocket science as it is perseverance!

I would love to hear your thoughts.

All the best,


The Twelve Days of Christmas

By Richard Sharpe | 12/17/2015 | 8:38 AM | Categories: Web/Tech

One of the most well loved Christmas carols is The Twelve Days of Christmas. This popular song actually originated in England in 1780 as a rhyme.  The lyrics are based on a “cumulative” theme with each verse building on the previous one.  Are you starting to sing it?    

“On the first day of Christmas my true love gave to me____”




What does this have to do with analytics and big data? 

Nothing more than an analogy to my favorite part FIVE GOLDEN RINGS!”

Just like the song, there are five golden rings that offer real business value in applying analytics on large volumes of data.  The gold lies in effectively using different forms of analytics by recognizing that each serves a specific role in improving the financial performance of products, customers and channels. 

To achieve the most benefit, the use of analytics should also be focused using a cumulative mindset.  Starting with Descriptive Analytics, the insights and knowledge gained should be used to help build a strong foundation for the next use of analytics.  If all of the analytics are tightly integrated for business users, the following can become true gold for an organization:

  • Descriptive Analytics – what exactly happened? (precise and specific)
  • Diagnostic Analytics – why did it happen? (getting to the root cause)
  • Predictive Analytics – what would happen? (if we Do or Do Not change specific drivers)
  • Prescriptive Analytics – what are the results of specific new operating scenarios?
  • Cognitive Analytics – what insights can be gained using machine learnings or, more practically today, adding specific fact based insights from the first four rings above to Senior Management’s cumulative knowledge?

Santa may not be real but the results obtained through effective analytics are!  So please excuse this Holiday theme but just chalk it up to someone who is very grateful for the many blessings that I have received over the course of my career. 

I wish each and every one of you a wonderful Holiday and I look forward to an exciting New Year filled with success stories of business value being realized through analytics and big data.

All the best,


Addressing Barriers to Success – Technology

By Richard Sharpe | 11/24/2015 | 4:59 AM | Categories: Web/Tech

This is the third posting of a series addressing the barriers to success in gaining sustainable value from analytics and big data.  The series centers around the primary pillars for having an effective solution: people, process and technology.  This posting is on technology.

There are a variety of reasons that technology can be a handicap when trying to apply analytics to provide meaningful business insights.  I have witnessed numerous examples for a variety of companies over the years.  But today we are going to focus on four areas that are pervasive today:


Lack of organizational confidence in the data:  when I was running CAPS Logistics we served over 16% of the Fortune 500 companies by supporting their network optimization and transportation and routing & scheduling needs.  Unfortunately, about half of the improvement opportunities identified through the use of technology would not be fully implemented because someone in the organization would take exception to the data that was used for the analysis.  Talk about a lack of ROI

Takeaway: To get value from analytics and big data, you must invest in a process to ensure that all organizational objections related to the data are addressed.


Analytical results that are not intuitive:  to be most effective, analytical applications must be designed for business users, not data scientists.  This means that the analytics are focused on a business problem defined by the business user and that the results are intuitive and meaningful for that user. 

Takeaway: Needing someone else to run the analytics or to interpret the outcome of the analysis places a real handicap to value.


Difficult to repeat:  we are all aware of the speed of change in the world we live in today.  The days are gone when a company can rely on the outcome of specific analytical work to remain valid for an extended period of time.  Today, the mode of operation is to refine plans by making incremental (“course corrections”) changes versus a large analytical study done every two years.

Takeaway: Analytics must be easily performed on an ongoing basis and must have the flexibility to be changed based on early efforts and insights.


Hard to measure financial impact:  to maintain senior level support of your analytics and big data initiatives, they have to deliver value.   Naturally, there are some initiatives that have intangible benefits but typical senior-level sponsorship is based on a plan demonstrating that the investment will provide measurable financial improvements.   

Unfortunately, many people don’t take the time to carefully consider how they are going to measure financial results until they are well into the initiative.  Do not fall into that trap.  First consider how you are going to baseline current performance.  Once defined, tie the anticipated areas of improvement back to the baseline for defensible measurements. 

Takeaway: Careful planning on how you will demonstrate value needs to be part of any analytics and big data initiative.    


The effective use of analytics and big data can drive significant competitive advantage.  Companies that undertake their initiatives by placing the proper amount of priority on people, process and technology will be the winners. 

I would love to hear your thoughts.

All the best,


Addressing Barriers to Success – Process (Moneyball anyone?)

By Richard Sharpe | 10/29/2015 | 6:00 AM | Categories: Web/Tech

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,



Other posts in this series:

"Addressing Barriers to Success—People"
"Addressing Barriers to Success—Technology"

Addressing Barriers to Success - People

By Richard Sharpe | 09/30/2015 | 7:41 AM | Categories: Web/Tech

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,



Other posts in this series:

"Addressing Barriers to Success – Process (Moneyball anyone?)"
"Addressing Barriers to Success—Technology"

You Are Going To Have a Heart Attack!

By Richard Sharpe | 08/27/2015 | 8:25 AM | Categories: Weblogs

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:

  1. 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”

  2. 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

  3. 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,


We Have Always Done It This Way . . .

By Richard Sharpe | 07/30/2015 | 9:57 AM | Categories: Weblogs

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?

Blog017_b_WeHaveAlwaysDoneItThisWay Blog017_c_WeHaveAlwaysDoneItThisWayBlog017_d_WeHaveAlwaysDoneItThisWay
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 

The opinions expressed herein are those solely of the participants, and do not necessarily represent the views of Agile Business Media, LLC., its properties or its employees.

About Richard Sharpe

Richard Sharpe

Richard Sharpe is CEO of Competitive Insights, LLC (CI), a founding officer of the American Logistics Aid Network (ALAN) and designated by DC Velocity as 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.


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