Part 4 – Finding the ROI for an Investment in an Analytical SCM Solution published a piece of mine on this topic a few years ago, but the ideas are important, so I am recapitulating the them here.  The first post in this series introduced the topic of overcoming the challenges to calculating the return for an investment in an analytical supply chain software application.  This post deals with the third of four challenges.

Part 4 — Third Challenge — Making Sense of the Data — “We have tons of data, but it is not telling us what we need to know!”

Analyze the Data

If the data exist, you need to trace a symptom, like excess work-in-process (WIP) inventory, to the root causes such as forecast error that drove production of the wrong product.  Once that is done, then powerful, but a relatively simple analysis can be performed by collecting the data from the data warehouse, or wherever it is stored, by putting it into a spreadsheet and then creating a cumulative distribution of the symptoms by reason code (see Figure 1).

Figure 1 – Pareto Chart (Cumulative Distribution)

More commonly, however, the data cannot be readily segmented by root cause.  This is probably because the symptoms and the root causes have not been identified and linked.  Using a simple fishbone diagram (see Figure 2), a few folks who know the business processes involved can probably identify symptoms and trace them to possible root causes.  Naturally, a skilled facilitator (possibly a consultant) will help, but you can also learn by reading up on the idea and by doing it yourself.

Figure 2 – Cause and Effect (Ishikawa or fishbone) diagram with potential root causes marked with capital letter reason codes.

Once the potential root causes have been identified, then a system of recording the incidents by reason code has to be put in place.  In some cases, while occurrences will not be tied to a reason code or other explanatory data, there will be some data that can be used as an approximate surrogate to estimate the order of magnitude of the root cause.  In those cases, you can get to an answer sooner, albeit a less precise one.

As an example, forecasting may be coming from sales.  You can probably measure the accuracy pretty well by saving the forecast and then by comparing it with orders or shipments in the same period as the forecast (made at lead time).  What is harder to determine is how much better your purchasing, manufacturing and distribution would have been if forecasts were 50% more accurate, or what the bottom line benefits would have been.  But by making some observations like how often a job had to be interrupted to start another one based on a canceled order or a forecast that was wrong, you can begin to build a collection of data that will be the foundation for answering that question.  Then, by creating a cumulative distribution that shows the schedule changes by reason code, you will get an understanding of the size of this problem.  Both inventory turns and customer service will go up if you can create a plan that is more flexible, responsive and accurate by attacking the root cause.

Estimate the Benefits

You can make an assumption on how much improvement might be possible.  Then, hypothetically, reduce the schedule changes due to forecast errors by that amount.  Research average WIP and reduce that by the same factor.  Put a procedure in place to track premium shipments that are paid by your company by reason code.  Take the premium freight that is caused by bad forecasts to the bottom line.

Then, since you made an assumption that forecasts could be 50% more accurate, you will need to perform some sensitivity analysis. Vary the 50% and see what the results tell you.  The ratio of the change in the root cause to the effect on the metric you are trying to improve measures your sensitivity to that root cause.  This kind of simulation model can be created with a spreadsheet tool.


Borrowing the Pareto and Ishikawa tools from TQM practices can help you find data and create information that you did not know was there, but the speed with which this kind of analysis can be performed increases with the availability and accuracy of data.

Thanks for stopping by Supply Chain Action.  Next, I’ll share Part 5 of this article.  Until then, I leave you to also ponder these words from Leo Tolstoy, “There is no greatness where there is no simplicity, goodness and truth.”



Part 3 – Finding the ROI for an Investment in an Analytical SCM Solution published a piece of mine on this topic a few years ago, but the ideas are important, so I am recapitulating the them here.  The first post in this series introduced the topic of overcoming the challenges to calculating the return for an investment in an analytical supply chain software application.  This post deals with the second of four challenges.

Part 3 – Second Challenge – Business analysis skills are lacking – “We are looking for the vendor to tell us!”

Can the Vendor Help?

After all, since the software vendor is proposing the solution, shouldn’t the vendor know how it will affect your company?  The vendor probably does have some useful information about whether the decision to purchase will be of some benefit.  They will be able to tell you in general what business symptoms can be affected.  They may even have survey data that show how other companies in your industry, or at least in other industries, have reported benefits.  They should have anecdotal evidence of how some existing customer plans to benefit or has benefited from investing in their approach or solution.

There are a couple of problems with the vendor’s input. First, the vendor cannot be objective. The vendor’s business is on the line.  It is probably a fierce competitor and its representatives may be under pressure to make this deal happen.  Second, directional information, surveys, and anecdotes may or may not be reasonable predictors of how your company will fare.

The current state of your business processes and how they are performing is pivotal to the potential return.

What Should You Do?

This reaction “We are looking for the vendor to tell us!”, is similar to the first challenge and reaction,“We need to know now!”  This second challenge is less driven by time than by the perception that the skill to perform the cause and effect analysis, data gathering, and statistical analysis does not reside within your company.  But, it is important for you to be able to understand, monitor and control the process, even if you use an outside consultant. Following these steps will help you do just that:

1. Identify and quantify undesirable symptoms.

2. Perform cause and effect analysis to find possible root causes.

3. Gather data by reason code (in order to prioritize root causes).

4. Quantify and analyze root causes (Pareto analysis).

5. Estimate the positive impact of your investment decision (e.g. a new supply chain management tool) on your root causes.

6. Extrapolate this to the positive impact on the undesirable symptoms.

7. Perform sensitivity analysis around your estimate in step 5 by varying the estimate and repeating step 6. This will give you a sense for the range of possible outcomes that is reasonable.

Your success at steps 1 through 7 will be most likely if you follow two additional guidelines:

1. “Time box” the analysis to a minimum of 2 weeks and a maximum of 30 days. These time frames are really only a guide to represent the order of magnitude for the minimum and maximum time frames.

2. Assign a primary internal resource for each area of analysis you undertake.

Once again, I’m grateful that you took a moment to read Supply Chain Action.  As a final thought, I remind you of the familiar words to ponder, “Luck is that point in life where opportunity and preparation meet.”


Part 2 – Finding the ROI for an Investment in an Analytical SCM Solution published a piece of mine on this topic a few years ago, but the ideas are important, so I am recapitulating the them here.  The first post in this series introduced the topic of overcoming the challenges to calculating the return for an investment in an analytical supply chain software application.  This post deals with the first of four challenges.

Part 2 – First Challenge – Limited time to perform analysis – “We need to know now!”

It is usually true that, at some point, the incremental benefit of additional information decreases as one moves along the continuum from limited information toward the goal of perfect information about the future.  However, you will reap significant benefit from knowing with some certainty what you can know in a 2-4 week period.  So, the output of some rigorous analysis should not be under valued.

If you truly do need to know something with immediacy, here are some tips for a quick, cursory approach to identifying the potential return from an investment in several aspects of analytical tools for supply chain or value network, management.

Collaborative Forecasting and Planning

If you track the accuracy of your forecasts, then you have some idea whether or not your company anticipates marketplace requirements well.  However, you must look beyond the aggregate annual revenue projection.  To understand the impact of demand planning on operations, it must be examined at a level that can be executed.  In other words, are you accurately anticipating the requirements for parts, people and processing at a fairly detailed level?  If significant forecast misses regularly occur, then working together with your major customers to plan for demand may have a notable impact on your operating costs.

Your suppliers may levy additional charges because you have passed on abrupt corrections in your demand for their products and services as a response to changes in your own demand profile.  These additional charges derive from additional setups, work-in-process inventory, and lost material incurred by the vendor on your behalf.  If the structure of your industry prohibits suppliers with less bargaining power from passing on these charges, they are still no less real a cost.  Everywhere that the value network generates unnecessary costs, a savings opportunity exists for the members of the value network.  In this case, such savings might be with reach if you extend the collaborative planning loop to include not only your customers, but also your suppliers.

Optimized Manufacturing Planning

Optimized manufacturing planning entails the use of math and analytical tools to choose the least cost combination of plant, equipment, personnel, and material that will meet planning objectives that may include one or more of the following examples:

• Maximizing inventory turns

• Maximizing on-time delivery

• Maximizing revenue

• Maximizing profit

• Maximizing throughput

Because optimized manufacturing planning provides decision support that considers multiple tradeoffs and constraints, it may not be easy to point to one indicator that demonstrates the potential for improvement through implementation of this powerful technique.  However, clues can be found in your manufacturing cost variances and in your performance against the business metrics that correspond with the objectives you want to maximize.

Inventory Planning and Optimization

Look at your financial reports and make a judgment as to whether your balance sheet or your income statement will be positively affected by the decision.  For example, examine inventory levels relative to your revenue.  Calculate inventory turns by dividing revenue by the annual ending (or better yet, trailing 12-month average) inventory.  Compare your turns with your competitors.  If that information is not available, you can use a general industry measure that is more readily available.  The higher the turns, the more working capital you can invest elsewhere and/or the less total interest you pay the bank for the working capital that you borrow.

Gauge your company’s interest expense.  If turns are low and interest expense seems high, then you probably have some significant room for improvement in the way that you make decisions about acquiring and producing inventory.

Does your company keep a financial reserve account against inventory assets (a contra account)?  Does the proportion of your inventory that may have to be written down at the end of the year indicate that your company is making enough of the right decisions around purchasing, distribution and manufacturing?  If the reserve account seems high, that underscores the importance of having the right inventory at the right time in the right place.  It means that obsolescence is becoming an issue because your planning process is not keeping pace with the volatility of supply and/or demand.

Synchronized Planning and Scheduling

Does your company pay the freight for the product or do your customers pay it?  Perhaps it varies by customer.  It may be that you are paying a significant amount of premium freight in order to meet customers’ demand.  If the premium freight you have paid each month for the last several months is anything but negligible, there may be an opportunity to eliminate most of that expense through tools that facilitate synchronized planning and fast planning cycles.

Take a walk through the plant.  Do you see a lot of inventory that is partially completed?  Are there piles of work-in-process inventory that are not being rapidly used up, either on the shop floor, or in the warehouse?  That is an indication of a planning problem.  It may be that the distribution, purchasing and scheduling requirements are not synchronized.  Or, perhaps there are bottlenecks that the plant manager cannot deal with systematically because he does not have the right tools.  There could also be significant setup times that can be eliminated with more sophisticated planning algorithms.

Accurate Order Promising

Tally up the amount of charge backs you have received from customers in the last 12 months for late delivery.  If you are consistently getting charge backs for late deliveries or short orders, that is another area of cost savings that should be available to you. Accurate order promising that considers your real capabilities might eliminate a portion of those charges.

The sales force may also have a feel for orders that they lose because they cannot accurately commit to customers in real-time.  An integrated software application that provides that capability might yield a competitive advantage.

Transportation Planning

There may be savings available through transportation planning.  If you have any significant level of less-than-truckload shipments, you may be paying too much for freight.  The challenge of determining the least cost route when many alternative groupings of multiple stops into routes must be considered requires the rapid use of advanced algorithms in order to achieve an optimal, or near optimal result.

If most of your shipments are to consumers, almost every pair of order lines that ship separately to a customer within a given 24-hour period is an opportunity for improvement through co-packing.

Statistical Process Control

Another place to look is in the area of returns.  Unless you are an electronic retailer or a mail order house, returns should not be a significant cost of doing business.  How are they trending?  Talk to manufacturing, distribution, customer service, or all three and you will get an understanding of how often things come back and why. You may find an indication of a quality problem in manufacturing, packaging or distribution processes (shipping and handling, or possibly sorting).

That’s Part 2 — the longest part, so I promise the others will be shorter.

Thanks again for stopping by. I’m not sure who said this, but I will leave you to ponder it this week:  “Don’t be troubled if the temptation to give advice is irresistible; the ability to ignore it is universal.”


Part 1 – Finding the ROI for an Investment in an Analytical SCM Solution published a piece of mine on this topic a few years ago, but the ideas are important, so I am recapitulating the them here.

Part 1 — Introduction

The competitive environment for every industry grows increasingly intense. Fast, reasonably accurate information about the impact of a software investment decision grows more critical.  Many decision-makers look for an exact forecast of return on investment (ROI) from the purchase of a supply chain management application.  At least four very real challenges make such perfect information elusive.  Too commonly, executives meet these challenges with responses that are not carefully considered. You have heard these challenges and their reactionary refrains before:

1. Limited time exists to perform analysis – “We need to know now!”

2. Business analysis skills are lacking – “We are looking for the vendor to tell us!”

3. The data to perform the analysis are almost always not available in the corporate databases – “We have tons of data, but it is not telling us what we need to know!”

4. It is always difficult to predict the future . . . as in forecasting, certain laws about a prediction of ROI will forever hold true . . .

  • the prediction will always be wrong
  • the prediction will always change for as long as the analysis continues
  • someone is going to be held accountable for the wrong, changing prediction

“Just give us the bottom line!”

After a quick look at these issues, one might question the effort to undertake the analysis to predict an ROI, as well as the validity of the outcome.  Perfect, or even complete, information may not be feasible, but if a few basic principles are followed, some analytical work can provide an understanding of the potential for bottom line impact.  It can also yield insight into the root causes of undesirable symptoms from which your business may be suffering.

The reactions of some decision-makers to each of the four challenges that are listed above provide a convenient outline for exploring a more thoughtful and strategic approach to evaluating a potential investment in supply chain management software.  I’ll explore each of these in successive, upcoming posts as follows:

Part 1 – “We need to know now!”

Part 2 – “We are looking for the vendor to tell us!”

Part 3 — “We have tons of data, but we it is not telling us what we need to know!”

Part 4 – “Just give us the bottom line!”

Part 5 — Where to start

Thanks for stopping by Supply Chain Action.  I leave you with a few words from Benjamin Franklin, “Be at war with your vices, at peace with your neighbors, and let every new year find you a better man [person].”


Answering Questions that Your ERP and APS Can’t

I have worked for some large software companies.  I loved many aspects of those experiences.  But, do you want to know the toughest part of those jobs?  It was meeting someone from one of their customers and getting a reaction like, “Oh, you are the enemy!”  Yes, that’s literally what one actually woman said to me verbatim. 

Now, of course, she did not stop to consider all the things that were much easier for her company to do and to keep straight with an integrated, enterprise suite of software applications from accounting through manufacturing to procurement

What flashed to her mind were the things that she and her colleagues could not do with the software.  That’s the way it is with software.  The first things we notice are what we can’t do, not what we can now do that was impossible before.

What we cannot do with our enterprise software systems, however, is a real problem.  To make matters worse, your knowledge workers can easily out-think a software application vendor’s development cycle.  There are some fairly legitimate reasons for this, of course, but the fact remains that ERP and APS vendors have no shot at supporting the need for ongoing innovation on the part of you and your colleagues who must make constantly make faster, better decisions.

Of course, that explains the popularity of Microsoft desktop applications like Excel and Access.

In the meantime, business managers who are not paid to be statisticians, data scientists, algorithm engineers, or programming experts struggle to build and constantly recreate the tools they need to do their work.

They are paid to ask important questions and find alternative answers, but the limitations of their enterprise resource planning (ERP) and advanced planning systems (APS) systems keep them wrestling just to find and format data in order to answer the really challenging analytical and/or strategic questions.

While it is possible to hire (internally or externally) the talent that combines deep business domain knowledge with data analysis, decision-modeling and programming expertise to build customized, spreadsheets in Microsoft Excel™, faster, more comprehensive and ubiquitous cloud solutions are emerging.  What’s needed in this approach is the following:

  1. A hyper-fast, super-secure, cloud of transaction level data where like data sources are blended, dissimilar data sources are correlated, and most of the hundreds of basic calculations are performed.  This needs to be a single repository for all data of any type from any source.
  2. A diagnostic layer where the calculations are related to each other in a cause and effect relationship
  3. A continuous stream of decision-support models (e.g. econometric forecasts, optimization models, simulation, etc.)

If you ever need to make better decisions than your competition (Duh!), then this kind of framework may speed your time to value and result in a more secure, scalable, and collaborative solution than desktop tools or point software solutions can provide.   

Such a platform would allow you to see what is happening in business context, why it is happening, and a recommendation for your next best action.    

It also provides a way to build decision “apps” for your business.  You know what apps on your phone have done for you.  Imagine what apps for your enterprise could do . . . and all the data is already there or could be there, regardless of data type or source.

I will leave you with these words from William Pollard, “Learning and innovation go hand-in-hand.  The arrogance of success is to think that what you did yesterday will be sufficient for tomorrow.  (

Have a wonderful weekend!

A New Look at IT

In the context of information technology, terms like SCM, CRM, PLM, etc. seem rather passé today.  They fail as meaningful arbiters (they always have been rather arbitrary) of focus for information technology vendors and their customers.  I may be overstating the case to make a point, but, in fact, many of the three-letter acronyms are much less important than they used to seem, even if they are not actually completely irrelevant.  So if the acronyms devised by analysts, consultants and software vendors are not meaningful, then what is?

We may get to the answer to that question by way of answering another question, “What can we say about the state of information technology in business today?

Here are some answers:

  1. Every company is in the information business, no matter what they manufacture, sell, distribute or do.
  2. Information and data are quite different (although I’m not ready to agree that knowledge is different from information or that “knowledge management” is any more useful a category than SCM or CRM).
  3. Almost all (I don’t know of an exception) manufacturing companies of any significant size have a formal sales and operations planning process (S&OP) in place or are working to implement one.  This is a well-defined process that holds little mystery anymore.  Its importance has been recognized precisely because SCM, CRM, PLM and other XXM’s have all failed to deliver their promised benefits.   As a result, companies are re-focusing on making high level decisions based on information, collected any way they can get it.  The ready availability of the information to support S&OP, along with the cultural challenges stemming from myopic reward systems, are what make doing S&OP a lot harder than it might appear.
  4. Once decisions are made or validated regarding how to run the business for the next 18 months or so, those decisions are often disconnected from the day-to-day decisions and execution of the business.  It’s a bit like connecting one end of an electrical cable to a powerful generator, but having nowhere else to go with the other end, even though lots of other people need the power being generated (in this case through executive decisions about the direction and priorities of the business).

The key thing to do with information is to connect the rest of the company to the executive direction coming out of the S&OP or some other executive decision process.

One does not have to be exceptionally bright to intuit that a bunch of software focused in different directions off of the enterprise resource planning (ERP) backbone will not meet that challenge ( e.g. SCM, CRM, PLM, etc.).

So, then, what will meet the challenge?  How can a company precisely create the information it needs from the huge amount of data stored in its servers, being analyzed in spreadsheets, and summarized in presentations?

Conceptually, it’s pretty simple.  A person who is junior and subordinate to the executive decisions taken in the S&OP process needs to know how well he or she is performing against his or her goals and how those goals impact the value of the company.  Similarly, executives need to know how the value of the company is being affected by various functions . . . not only so that they can “light a fire” under the feet of the slackers (sometimes a necessary part of the proper response), but also so that they can provide the leadership and clarity necessary to empower the lagging function.  Commonly, that information is just simply not there.  Proponents of the “balanced scorecard” were onto something, but the information has not been available to support it because the software written to provide balanced scorecards was disconnected from the data generated and used by those doing the work of running the business.

The data, however, exists, along with the information technology to put it together.  Every transaction is trapped electronically in some computer system.  It is being summarized and analyzed in spreadsheets.  We know how to calculate the metrics by which each function (and most people in each function) are governed.  We also know how to calculate the impact of metrics like manufacturing lead time on service level and the impact of service level on revenue and margin, as well as the impact of revenue and margin on economic value added or some measure of enterprise value.

In practical terms, if I am running a press, I should be able to see at any point in time how my productivity and quality, together with pricing and sales, are affecting return on assets, or at least the asset that I am working on.  It will often be the case that many small deviations in my work will not affect the larger, aggregated metrics of corporate value, but the very association forces everyone to think in terms of how their task fits into the overall mission.  Of course, compensation needs to be similarly aligned.  Paying one person to make as many pieces as possible, regardless of how many are needed by customers renders such information useless.

For years, application software vendors and their representatives have preached that companies should get their business off of spreadsheets.  (I think I’m also guilty here.)

That is a little like telling your body to stop digesting food.  The digestive process is all your body has for getting nutrients from food.  Similarly, for many employees, spreadsheets are the main way that they create information out of data.

Perhaps it is about time we stopped asking how we can get off of the spreadsheets and how we can get the business to really run on the innovation and analysis that spreadsheets allow knowledge workers to perform.

Maybe, that is where information technology should be focused.  Maybe, we need to evolve our thinking to realize that the spreadsheet is not the enemy.  Maybe, spreadsheets are a part of the solution that we just need to figure out how to leverage. 

There are some new, small software companies that are on the leading edge in using Excel as the user interface to enterprise systems.  Companies like Oracle and SAP have acquired companies that do some of this.

Is that the end or only the beginning?

%d bloggers like this: