Supply Chain Digitization – A Reality Check

By Richard Sharpe | 07/27/2016 | 10:17 AM | Categories: Web/Tech


Today, I am going to switch gears to focus on the hot industry topic “The Digitization of the Supply Chain”.  This subject is getting a lot of attention in the media especially as it relates to the Internet of Things (IoT).  According to Gartner, by 2020 there will be 21 trillion devices streaming information empowered by the IoT.  Information on everything from the current performance of a part within a machine to the current location of my dog. 

I get the industry buzz about the digitization of the supply chain.  But I have to ask myself the question; “Other than specific performance/event notifications, will companies really gain the true business value that is possible from this exponential growth in data?

Today, corporate enterprises have no shortage of data.  Data from their ERP, supply chain, finance and sales related systems, just to name a few.  Data that is often siloed and often hoarded by functional organizations.  Even with the ongoing investments that companies have made to access, visualize and manipulate their data, I often hear the statement “we still cannot get the insights we need from the information in our systems.  We aren’t realizing the return on investment we had hoped for and expected”.

In June of this year I ran the Analytics and Big Data Track for the Chief Supply Chain Officer Forum hosted by EyeForTransport.  It was a great day and a half spanning subjects from Data Governance, supporting enhanced S&OP processes and strategic initiatives all through the proper use of analytics and data.  The consensus from the discussions was clear.  To get real value from data you must have VACA:

  • Having processes in place to ensure the VALIDATION and quality of the data
  • Being able to have timely ACCESS to the data
  • Gaining CONCENSUS that the right data that is being used to solve a problem
  • Applying the appropriate ANALYTICS on the data to drive actionable insights that improve the performance of the business

Sounds pretty obvious, right?

However, if we are being honest, how many companies can say they have mastered VACA for the enterprise data they have today?  If not, then how is adding additional finite pieces of data that comes with the digitization of their supply chain going to help? 

I think a reality check is required.  Clearly, nothing is going to slow down the exponential growth of data and the digitization of supply chains.  There will be a continuation of great success stories such as the ability to catch the failure of a critical component of a machine before it actually fails.  However, to gain maximum value, companies need to prioritize and act on their VACA capabilities. 

The smart place to begin is with the data that already exists within the enterprise.  The smart money is to extract the value from this information before starting to add significant volumes of IoT data.

Without effectively addressing VACA requirements, the digitization of the supply chain will increase the data related headaches that most companies are wrestling with today.  With VACA proven and in place, the lessons and experience gained can then be applied to the new data that will come from future supply chain digitization investments. 

I would love to hear your thoughts.

P.S. - get this right and you can take a VACAtion! 

All the best,


Are Your Omni-Channel / E-Commerce Sales Really Profitable? Part 4

By Richard Sharpe | 06/28/2016 | 7:38 AM | Categories: Web/Tech

This is the final posting of this series focused on Omni-Channel / E-Commerce profitability.  The focus of this posting is on the impact of product returns. 

We have defined the four components of the Total Cost To Serve (TCTS) for Omni-Channel / E-Commerce orders to be:

  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 D above.

The problem

When consumers buy a product sight unseen, there is often a level of uncertainty about whether the product will be what they actually want. Retailers often offer free returns for customer satisfaction, an offer that consumers use to their fullest advantage. But how does that affect the overall profitability for the retailer?  Seem simple?  The answer is often not so obvious.

Let’s start with the revenue part of the equation.  A returned product turns a positive into a negative because the actual revenue received for the transaction has been returned to the consumer.  The loss associated with the order also has to account for all of the costs associated with the returns process.  These returned product costs can be more significant than most people realize.  Let’s break down product return costs in more detail.

Original Order Fulfillment Costs (sunk costs) – since the product(s) are being returned, the original order fulfillment costs are now not being covered by the revenues associated with the order.  Therefore, these are now sunk costs that need to be absorbed.

Inventory Carrying Costs – the length of time that a consumers holds the product can have a significant impact on inventory carrying costs.  When an initial order is filled, the typical inventory replenishment process applies which can mean that new replacement inventories have been ordered.  Therefore, in reality the seller of the product now has working capital tied up in inventory sitting at the consumer’s location, inventory in-transit as it is being shipped back to the seller’s receiving locations as well as new replenishment inventory.  This can significantly increase the levels of working capital tied up in product inventories.  Forecasting returns can help but most companies end up replenishing inventory to ensure there are no lost sales, given their lack of confidence in their data.

Return Transportation Costs – this category of cost is dependent upon whether the consumer pays the shipping fee to return the product.  If not, then return transportation costs can add significant increases to profit losses.

Secondary Handling Costs – assuming the returned product is placed back into storage or on the shelf, there are costs associated with the receiving, inspecting and put-a-way activities for the returned product.

Disposal Costs – if the product is not going to be placed back in general inventory and it is to be discarded or destroyed, then there may be a disposition cost associated with the returned product.  

All of these costs are demonstrated in the visual below and can have a significant impact on the profitability of an Omni-Channel / E-Commerce channel.


The solution

So how do retailers selling in the Omni-Channel / E-Commerce tackle this issue?  The solution starts by again recognizing the wisdom in the adage “one size does not fit all”.  Treating all customer product returns the same way is simply a formula for failure. 

The solution starts by segmenting Omni-Channel / E-Commerce customers by understanding their overall net profit contributions over time.  This requires having specific and accurate facts regarding exact profit performance for Omni-Channel / E-Commerce customers including the frequency and impact of their product returns.   

This form of segmentation enables the creation of tailored product return policies that help manage the negative impact on profitability.  Informed policies regarding how products are returned, if there are shipping fees, if charges apply for returned products or if there are defined time windows for products to be returned. 

Of course this may drive some customers to shop with another retailer.  But that may not be such a bad thing from a competitive advantage perspective!

I would love to hear your thoughts.

All the best,


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"

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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