Smartly Tackle Data Barriers to Use Advanced Analytics

“Harnessing the true power of data driven insights 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.”

Lisa Harrington – President, lharringtongroup.com

Companies are struggling to use data and analytics to continually find ways to reduce operating costs and protect margins. According to Gartner, “less than half of data and analytics (D&A) leaders (44%) reported that their team is effective in providing value to their organization”.

So why are so many companies still struggling with the adoption of Machine Learning / Artificial Intelligence (ML/AI) technologies to handle today’s inflationary pressures? The reasons can vary but some of the most common complaints are:

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.

Case In Point: A meeting was held with the CFO, COO and SVP of Supply Chain for a well-known apparel company. They knew that they needed to build analytical capabilities, but were skeptical because of their perception of the current state of their data. Fortunately, the SVP of Supply Chain had previous experience in working with a solutions provider in tackling this issue. He convinced the others to take a first step that would demonstrate that their data could be turned from a liability to an asset to produce meaningful insights on opportunities to reduce costs and increase profit margins.

Action: A Project Team was assembled and all sources for their supply chain and sales transactional data were identified. Data Subject Matter Experts were involved to address any data issues. Consensus was reached by the Team on how the data should be intentionally transformed to build a foundation for SKU and Customer specific cost and profit performance information. ML/AI technology was then used to further validate data quality problems and to create specific and actionable financial performance insights that could be refreshed periodically. The Project team found a potential inventory working capital reduction in excess of $10 million dollars.

Data integrity issues can be proactively addressed to ensure that operating data becomes a valuable asset. An asset that allows for visibility into actionable insights that drive trusted, fact-based decisions. The companies that take this seriously will consistently move ahead of their competition and drive additional cost reductions and profitable performance.

Please comment on this posting or email me at [email protected]

All the best,

Richard Sharpe
CEO – Competitive Insights

Quickly Find Hidden Inventory Opportunities

The most common issue still plaguing many industries is an increase in inventory and the impact on the bottom line. One company that is making progress is Guess. Check out this article on their efforts.

Guess CFO Markus Neubrand attributed the company’s growing operating margins in part to “clean inventories” and “carefully managed” costs. In today’s volatile operating environment, it is a difficult problem to solve. One critical consideration is understanding the specific and accurate cost and profit performance for each SKU in every inventory location.

The company highlighted below found hidden inventory reduction opportunities of over $400k out of a total Cost to Serve and Net Landed Profit opportunity of $2.9 million (40x return on investment).

Figure 1 Identifying Unprofitable SKUs With High Inventory Levels

Understanding the true costs and profit performance for inventory investments can provide the actionable insights needed to develop more profitable inventory deployment strategies. In one case, an international company serving over 50 countries had significant profit leakage issues. They knew they needed accurate and repeatable inventory insights on their Cost to Serve and Profitability opportunities across their international operations. In meeting this objective, the company was able to pinpoint the significant opportunities noted above.

Using traditional information in managing your inventory investments can lead to missed cost reduction and profit generation opportunities. Accurate, specific, trusted and repeatable Cost to Serve insights positions companies to out pace their competition and delight their stakeholders.

Please comment on this posting or email me at [email protected]

All the best,

Richard Sharpe
CEO – Competitive Insights

Smartly Finding Significant Cost Reduction Opportunities

In this tough operating environment, companies are often forced to use a generalized strategy on cutting costs in key areas like minimizing supplier replenishment orders

Importantly, the specific total cost-to-serve and profit performance contributions by SKU, Customer and Channel are buried and certainly not visible through the P&L. So what is at stake? Hidden opportunities to realize significant cost reductions while increasing profit margins!

Case In Point: The following table shows the segmentation of customer performance by unprofitable customers (Unprofitable column), marginally performing customers (Bottom 4% column) and very profitable customers (Top 96% column). The same analysis can be done by products, markets, regions and channels.

184 unprofitable customers represent 34% of total Net Sales but add 41% of the total Net Landed Cost to Serve. Bottom line, company profitabiliy is reduced over 50%. Highly profitable customers (491) represent 61% of total Net Sales but produce 196 of profitable performance. The distribution of Customer profit contributions is not atypical.

: Specific and accurate Cost-to-Serve and Net Landed Profit performance knowledge is essential in managing dynamic and changing operating environments. Using generalized information in managing your operation can lead to missed cost reduction and profit protection opportunities. Accurate, specific and repeatable Cost To Serve insights will allow you to out pace your competition and delight your stakeholders.

Please comment on this posting or email me at [email protected]

All the best,

Richard Sharpe
CEO – Competitive Insights

how to eliminate data issues as a roadblock

Summary: It is rare to talk to a company that believes they have very little challenges with their data. Unfortunately, many companies use their data integrity issues as a crutch to justify why they are not getting true value from business analytics.

Case In Point: Recently, Competitive Insights (CI) facilitated a meeting with the CFO, COO and SVP of Supply Chain for a well-known apparel company. The Executives knew that to proactively address inflationary pressures to reduce costs and complexity, they needed accurate and specific Cost-to-Serve and Profit Performance insights by Product, Customer and Channel but were skeptical because of concerns about the current state of their data.

Action: Fortunately, the SVP of Supply Chain convinced the other Executives to take a first step that would demonstrate that their data could be turned from a liability to an asset and produce meaningful financial insights to reduce costs and increase profit margins. He emphasized the need to efficiently:

Obtain, validate and transform all relevant end-to-end transactional data

Ensure cross-functional buy-in to the Cost-to-Serve and Profit performance insights

Provide for monthly updates accessible in an easy and intuitive format

Problems are solved by business leaders and managers making decisions that positively impact the efficiency and financial impact of the operation. Decisions that are fact based and that are actionable.

Results: Working with CI, all relevant transactional data was identified. Consensus was reached on how the data should be intentionally validated and transformed to build accurate and specific Product (SKU) and Customer Cost to Serve and Profit information that was far more granular than provided by their P&L. The following actionable financial opportunities were identified:

Out of 142,493 Products using 875 Colors, only 53 colors provided 80% of their profits

Segmenting Products and Customers by financial performance revealed that a very small number of Products and Customers contributed 96% of their true operating margin

Significant opportunities were identified to reduce operating costs by focusing on the large number of Unprofitable and Marginal Customers buying unprofitable Products

Inventory Working Capital reduction opportunities in excess of $10 million dollars were identified

Takeaway: Data integrity issues can be proactively handled to ensure that operating data becomes a valuable asset. An asset that allows for visibility into actionable insights that drive trusted, fact-based decisions. The companies that take this seriously will consistently move ahead of their competition and drive additional cost reductions and profitable performance.

If you like this blog, please share it or comment.

All the best,

Richard Sharpe
CEO – Competitive Insights

Artificial Intelligence/Machine Learning to enhance Supply Chain Resilience and Effectiveness

Are you struggling with:

Reconciling multiple sources of supply chain data coming from a host of different systems?

Cost and profit performance insights that are not specific and accurate enough to make critical decisions?

Where to start with advances in Artificial Intelligence and Machine Learning applications that have a rapid ROI?

Georgia Tech Supply Chain & Logistics Institute (SCL) and Competitive Insights, LLC (CI) are proud to announce a new industry collaborative program offered through a recently awarded GA-AIM Grant.

Not limited to Manufacturing companies, this collaboration focuses on companies with operations in Georgia by providing subsidized and free training on the latest Artificial Intelligence (AI) & Machine Learning (ML) methodologies and technologies.

Richard Sharpe, CEO of CI, added “it is exciting to see how AI and ML developments are allowing a company’s resources to focus on strategic and operational actions versus dealing with fragmented data and the lack of one source of accurate and trusted information. We are honored to be working with SCL on this critical AI/ML initiative.”

Data Governance and Fruitcake

Big Data is something that companies are trying to define with regard to what it means to their operation and to their competitive landscape. When considering the growing number of sources of unstructured data (e.g. social media) and structured data, just defining the landscape of what you are talking about can be difficult. In this blog we have provided a framework for how to define Big Data, getting value from Big Data and now providing actionable points on how to turn a three headed monster into something that adds significant and ongoing business value.

In an earlier posting we identified the requirement to gain cross functional consensus with regard to how Big Data solutions are created to serve the intended purpose of solving a business problem(s). We also focused on why it is so important to take an enterprise wide perspective to maximize the value of the investment. In this posting, we will focus on the importance of data governance.

What does data governance have to do with Big Data?

Everything. Effective solutions take time and resources to build correctly. The question is do you want that investment to solve a business problem one time or to continue to support solving the business problem over time.

Problems are solved by business leaders and managers making decisions that positively impact the efficiency and financial impact of the operation. Decisions that are fact based and that are actionable.

Ok, so what does that have to do with Data Governance?

Let’s say that you have a significant business problem to solve. The information that you have in front of you is known to be consistently accurate and specific to the problem area. This is a function of the information coming from the same source, that the information has been verified by Subject Matter Experts (SMEs) and the way that it has been processed is consistent to provide the information you need. What did I just describe? Data Governance; the insurance policy for Big Data, and this insurance policy continues to provide returns as you measure the impact of those decisions over time.

Data Governance provides the rules for which you are obtaining, organizing, validating and processing the vast amounts of structured and unstructured data to gain competitive advantage. Without it, your Big Data investments are a waste of time.

If you like this blog, please share it or comment.

All the best,

Richard Sharpe
CEO – Competitive Insights

Going Deep and Wide using an Enterprise Approach for Analytics

Getting value from analytics is a headline that is constantly being offered daily in multiple publications. A lot of what is said about analytics is really just a spin on ways to sell “re-wrapped” products and services. My hope is that the information that is being offered in this blog provides meaningful suggestions that allow your company to gain significant competitive advantage from analytics.

Companies are aggressively trying to figure out what analytics means and how they can tackle the multiple obstacles they anticipate in order to gain significant value. I want to demystify the whole notion of harnessing Big Data analytics from being a seemingly impossible, daunting task to an opportunity to create an invaluable asset that drives significant financial performance improvements. In the last blog, we talked about building organizational consensus and in this blog, we will look at the importance of building on that consensus to support an enterprise wide approach to maximize the value of Big Data.

Resources

You might find the following article of interest. It also addresses the need for an enterprise-wide approach to Big Data: Moving to Enterprise Data Quality – a proactive data quality approach

The book Deep and Wide by Andy Stanley is on a completely different subject, but the title of the book provides synergy to taking an enterprise wide approach with Big Data. Let’s explore this further.

Value across the organization

To tackle the point of gaining cross-functional buy-in to your analytics approach, you need to give everyone at the party something they want. But how can you accomplish this to satisfy the specific analytical needs for Supply Chain, Sales, Marketing, Operations and Finance? Doesn’t this only increase the time and complexity associated with the effort and push it one step closer to inevitable cancelation?

The answer is no. Effective solutions do not approach Big Data analytics from a “functional silo” point of view but from an “end to end supply chain” perspective in order that the transactional data can be repurposed to serve the multiple needs of the organization. Taking a holistic approach that includes suppliers, manufacturing, storage, transportation, inventory and product returns provides an end to end level of scope that can then be used to serve multiple functional needs. This is the Wide piece of the puzzle having one source of trusted information and is a key criteria to building effective analytical solutions using Big Data.

But what about the Deep side of the solution. To be meaningful, Big Data analytics have to provide for meaningful insights that drive better organizational decisions. This requires the ability to get to very specific performance information, information that provides insights and is actionable. You might be thinking; what, detailed information about end to end operational performance accessible to multiple organizational users? You bet! The cloud now provides the processing capability to take the first step to harness Big Data analytics that drives value by increasing financial performance and competitive advantage.

I am often in meetings with a group that was not the original sponsor of the company’s Big Data analytics initiative. The conversation will go something like this:

“Yes, we think that’s the case, nothing new there. But wait, look at those details! Can that be right? How did you determine that? Can you drill into that further?

I wish we had known that specific information on that (customer, product, channel – you pick the area) yesterday.”

Avoiding approaches that perpetuate silos of Big Data in analytical solutions is a huge step in gaining high impact results. Making very specific operation details available in ways that are meaningful to each organization eliminates conflicting analysis and confusion on operating performance. Going Deep and Wide using an Enterprise Approach is key.

In fact, this goes back to getting everyone to buy in. Give everyone something to make their job easier, something to make them smarter and something that makes them more efficient and you will have turned data into an asset instead of it being a liability...

If you like this blog, please share it or comment.

All the best,

Richard Sharpe
CEO – Competitive Insights

How to Implement Supply Chain Value Adding Analytics – Cross-Functional Data Validation

In order for any analytical solution to be meaningful, the issue of data quality needs to be addressed. The goal is to demystify the whole notion of harnessing Big Data analytics from being a seemingly impossible, daunting task to one of creating an invaluable asset that drives significant financial performance improvements.

Case Study

While I was the President of CAPS Logistics for over 8 years, the company serviced over 16% of the Fortune 500 in various forms of supply chain decision support applications. These efforts spanned the globe from supporting the expansion efforts of a worldwide soft drink company, to the redesign of supply chain networks for multiple CPG and specialty manufacturing companies and providing different transportation solutions to one of the largest companies in the waste management industry. The technology was proven, the people were bright and the focus was to provide the best solutions possible. Unfortunately, in most cases, the implementation of these carefully engineered solutions was either slowed down or even put on hold. Why? Other departments would offer objections often citing concerns about the “quality” of data used for the analysis. Typically, the nail in the coffin would be that if they would offer that their data concerns were correct, the integrity of the solution could cause the company to miss its revenue targets. Sound familiar? The end result was that the company did not attain the competitive advantage that was possible.

Let’s take this lesson to the world we live in today

In a world of exponentially growing data associated with the operation of your enterprise the problem sited above had two issues. The “quality” concern which will be addressed in a future posting on data governance. The second issue was not having cross-functional consensus. In the projects mentioned above, efforts were made to involve other departments at every stage of the project but gaining supply chain efficiencies were not their highest priority. Therefore, these other functional groups had no real buy-in in the work effort.

If you believe that Big Data has the opportunity to drive significantly recurring financial improvements, then the table stakes are even higher with regard to early organizational buy-in. Buy-in with regard to getting everyone on the same page on how to repurpose and use Big Data to empower multiple forms of new analytical and strategy development capabilities. I am guessing that many of you are saying “yea, right for our company; this would be comparable to building Noah’s Ark.” You may be right but it is a challenge that deserves careful consideration as offered by the following quote by Benjamin Franklin:

“By failing to prepare,
you are preparing to fail.”

Success will also require having the right level of Executive sponsorship and taking advantage of the power of cloud technologies and proven methodologies. In addition, other key points need to be integrated into your approach including obtaining cross functional consensus on any data issues. If this is not a mandate, you run the serious risk that organizational questions will surface which can stop the entire effort.

So why go to the effort?

Isn’t the political risk too significant and the task too big to undertake now especially given all of the mission critical projects that are already established for the company? That might be the right answer but let’s look at it another way. Is it possible that your Board and certain members of your Executive Team are wondering if the company will be left behind when your competitors harness the value of Big Data? Value that is measured by increasing financial performance and competitive advantage. Only you know the answer to that question, but if the decision is made to take the first move advantage, be sure the process you use requires cross functional organizational consensus as a cornerstone of the solution.

If you like this blog, please share it or comment.

All the best,

Richard Sharpe
CEO – Competitive Insights

Do you truly know your profitability for every customer and shipment?

With constant supply chain disruptions and inflationary costs increases, we all are feeling the stress and frustration of managing “The Now”. Not having the time and resources to plan, implement, check and adjust for the future state is truly costing us all.

Supply Chain professionals everywhere are doing their best, yet every day we read and hear from the Boardroom to the Docks:

“The problems and profitability challenges we are experiencing are ALL due to our Supply Chain issues”

What is not often understood is that many of these issues are outside the control of the supply chain operation. Demand increases, labor challenges, increases in pay requirements, equipment availability, raw material shortages, lack of capacity, increased lead times and driver shortages all contribute to these challenges. Challenges that are causing increasing costs, complexity and capacity and therefore end to end supply chain bottlenecks. The planning and execution of shipping goods from origin to final destination has a HUGE impact on your customers’ experience and your true profitability.

This problem is not going to go away any time soon. Companies are aggressively re-evaluating the entire structure of their supply chain operations. Unfortunately, many approaches being explored are relying on the “traditional” supply chain operating principle:

“Work to satisfy ALL customer demands, on time while minimizing costs!”

That mindset has to change if we are to eliminate constraints, reduce stress, frustration and maintain or even increase profitability. For most companies, a small number of customers and products drive the majority of the operating profit, while many customers and products (SKU’s) drain those very same profits directly from the bottom line. So, the question becomes:

“How do we know what time and resources are being assigned to customer shipments that are actually significantly reducing our profit?”

A sustainable solution (not so traditional for companies) is to use profit performance to address capacity, complexity and cost issues. Using your transactional data for deep dive profit analytics provides true visibility to answer the above question while empowering your team to focus on customers and products that provide the biggest bang for the buck.

The Coca-Cola Company eliminated over 200 SKU’s they traditionally produced including TAB!

UPS knows by each customer and shipment their profitability level. Do you?

To help you get started here is a step by step approach for the critical actions in assigning resources for customer and products based on their profit contributions:

Recognize that your supply chain resources should be prioritized based on profit performance and competitive advantage and ensure there is cross-functional and senior level buy-in.

Adopt a Cost-to-Serve approach to truly understand the costs and profits associated with servicing not just select customers, but ALL customers.

Build a profit performance profile for ALL customers and ALL products by segmenting by performance. The results will help drive actionable insights and organizational support! This is what it can look like:

Critical Shipment Priority: the customers and products that deliver 96% of your profit

Subsequent Shipment Priority: that deliver customers and products equal 4% of your profit

Delayed/No Shipment Priority: unprofitable customers buying unprofitable products (BTW-you won’t find these using standard cost accounting!)

Continue to build cross-functional buy-in on the Shipment Priority Plan using profit analytics as the “One True Version of the Truth” and ensure continued Executive support.

Execute the Plan and measure the profit protected on an ongoing basis.

If you like this blog, please share it or comment.

All the best,

Richard Sharpe
CEO – Competitive Insights

How to Turn S&OP into a Super Charged Profit Booster

Why Add Profit into S&OP

Whether formal or not, every organization has a Sales & Operations Planning (S&OP) program in place. S&OP is important for creating the story-of-the-business, the operational details in satisfying demand of specific units of products. “What worked” for S&OP is stretched to the limits today because of supply chain risk disruptions that resulted in significant resource constraints, capacity shortages and inflationary cost increases. These problems manifest themselves as significant internal stress and as conflict between sales, supply chain operations and procurement.

This is driving the need for S&OP to:

“Create a proactive story-of-the-business in terms of back logs, delayed service levels and sacrificed customer satisfaction”

Why doesn’t the current S&OP process of “what worked” mitigate or eliminate today’s supply chain problems? It’s simple, they are not incorporating profits into the calculation. Profits allow companies to attack resources constraints, expand capacity and reduce the impact of inflation.

“For example, if the shipment plan is constrained (as is generally the case), the Pre-S&OP Meeting and subsequent Executive S&OP meeting will call for decisions on who will get served and by when, rather than just letting systems (such as ERP) or processes (such as a FIFO) determine the answer,” said Henley. “Knowing profit by SKU, profit by customer, and profit-by-SKU-by-customer provides unmatched decision criteria as the organization ponders the next 12 months or more.”

How to incorporate Profit into S&OP

Create a proactive story-of-the-business that is fully supported and owned by the most senior executives

Create a story-of-the-business that is not based solely on historical considerations. These historical considerations often lead to missed financial objectives and growing shareholder pressures. It must be based on a foundation of increasing profitable performance.

Use of precise analytics for decisions on “Who, What and Why” that provide actionable visibility on profit contributions by Channel, Customer and Product performance.

Use profit measurement that go beyond standard cost accounting measurements. Net Landed Revenue (includes discounts, promotions), Net Landed Cost to Serve (includes Supply Chain costs from supplier to customer) and Net Landed Profits provide the missing ingredient. (click here for video on Supply Chain financials)

The COVID pandemic is the biggest challenge of our times. Some organizations will stick to the same story-of-the business. Some will innovate to profit. Will your company take its S&OP decisions to the next level?

If you like this blog, please share it or comment.

All the best,

Richard Sharpe
CEO – Competitive Insights

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