Does Your Demand Planning Process Include a “Quantitative Sanity Range Evaluation”?

There is a process that should be part of both your demand planning and your sales and operations planning.  The concept is simple – how do you find the critical few forecasts that require attention, so that planner brainpower is expended on making a difference and not hunting for a place to make a difference?  I have heard this process called a “Forecast Reality Check” and a “Forecast Reasonability Check”.  Just to be difficult, I’ll call it a Quantitative Sanity Range Evaluation (I have my own reasons.)  It may be similar in some ways to analyzing “forecastability” or a “demand curve analysis”, but different in at least one important aspect – the “sanity range” is calculated through bootstrapping (technically, you would be bootstrapping a confidence interval, but please allow me the liberty of a less technical name – “sanity range”).  A QSRE can be applied across industries, but it’s particularly relevant in consumer products, where I have seen a version of this implemented first hand by Allan Gray, a really smart gentleman – back when I worked with him for End-to-End Analytics – just so you know I didn’t think this all up on my own!

At a minimum, QSRE must consider the following components:

  1. Every level and combination of the product and geographical hierarchies
  2. A quality quantitative forecast
  3. A sanity range out through time
  4. Metrics for measuring how well a point forecast fits within the sanity range
  5. Tabular and graphical displays that are interactive, intuitive, always available, and current.

If you are going to attempt to establish a QSRE, then I would suggest five best practices:

1.  Eliminate duplication.  When designing a QSRE process (and supporting tools), it is instructive to consider the principles of Occam’s razor as a guide:

– The principle of plurality – Plurality should not be used without necessity

– The principle of parsimony – It is pointless to do with more what can be done with less

These two principles of Occam’s razor are useful because the goal is simply to flag unreasonable forecasts that do not pass a QSRE, so that planners can focus their energy on asking critical questions only about those cases.

2. Minimize human time and effort by maximizing the power of cloud computing.  Leverage the fast, ubiquitous computing power of the cloud to deliver results that are self-explanatory and always available everywhere, providing an immediately understood context that identifies invalid forecasts. 

3. Eliminate inconsistent judgments By following #1 and #2 above, you avoid inconsistent judgments that vary from planner to planner, from product family to product family, or from region to region.

4. Reflect reality.  Calculations of upper and lower bounds of the sanity range should reflect the fact that uncertainty grows with each extension of a forecast into a future time period.  For example, the upper and lower limits of the sanity range for one period into the future should usually be narrower than the limits for two or three periods into the future.  These, in turn, should be narrower than the limits calculated for more distant future periods.  Respecting reality also means capturing seasonality and cyclical demand in addition to month-to-month variations.  A crucial aspect of respecting reality involves calculating the sanity range for future demand from what actually happened in the past so that you do not force assumptions of normality onto the sanity range (this is why bootstrapping is essential).  Among other things, this will allow you to predict the likelihood of over- and under-shipment.

5. Illustrate business performance, not just forecasting performance with sanity ranges.  The range should be applied, not only from time-period to time period, but also cumulatively across periods such as months or quarters in the fiscal year.

If you are engaged in demand planning or sales and operations planning, I welcome to know your thoughts on performing a QSRE.

Thanks again for stopping by Supply Chain Action.  As we leave the work week and recharge for the next, I leave you with the words of John Ruskin:

“When skill and love work together, expect a masterpiece.”

Have a wonderful weekend!

The Potential for Proven Analytics and Planning Tools in Healthcare Delivery

I’ve spent time in a hospital.  I was well cared for, but I didn’t like it, and I worried about the cost and how well I would be able to recover (pretty well, so far!)  Also, my daughter is a doctor (obviously takes after her mom!), so healthcare is obviously an area of high interest for me.

To say that managing a large, disaggregated system such as healthcare delivery with its multitude of individual parts, including patients, physicians, clinics, hospitals, pharmacies, rehabilitation services, home nurses, and more is a daunting task would be an understatement.

Like other service or manufacturing systems, different stakeholders have different goals, making the task even more challenging.

Patients want safe, effective care with low insurance premiums. 

Payers, usually not the patient, want low cost. 

Health care providers want improved outcomes, but also efficiency.

The Institute of Medicine has identified six quality aims for twenty-first century healthcare:  safety, effectiveness, timeliness, patient-centeredness, efficiency, and equity.  Achieving these goals in a complex system will require an holistic understanding of the needs and goals of all stakeholders and simultaneously optimizing the tradeoffs among them.

This, in turn, cannot be achieved without leveraging the tools that have been developed in other industries.  These have been well-known and are summarized in the table below.

While the bulk of the work and benefits related to these tools will lie at the organization level, such techniques can be applied directly to healthcare systems, beginning at the environmental level and working back left down to the patient, as indicated by the check marks in the table.

A few examples of specific challenges that can be addressed through systems analysis and planning solutions include the following:

1 – Optimal allocation of funding

2 – Improving patient flow through rooms and other resources

3 – Capacity management and planning

4 – Staff scheduling

5 – Forecasting, distributing and balancing inventories, both medical/surgical and pharmaceuticals

6 – Evaluation of blood supply networks

Expanding on example #5 (above), supply chain management solutions help forecast demand for services and supplies and plan to meet the demand with people, equipment and inventory.  Longer term mismatches can be minimized through sales and operations planning, while short-term challenges are addressed with inventory rebalancing, and scheduling.

Systems analysis techniques have been developed over many years and are based on a large body of knowledge.  These types of analytical approaches, while very powerful, require appropriate tools and expertise to apply them efficiently and effectively.  Many healthcare delivery organizations have invested in staff who have experience with some of these tools, including lean thinking in process design and six-sigma in supply chain management.  There are also instances where some of the techniques under “Optimizing Results” are being applied, as well as predictive modeling and artificial intelligence.  But, more remains to be done, even in the crucial, but less hyped, areas like inventory management.  Some healthcare providers may initially need to depend on resources external to their own organizations as they build their internal capabilities.

I leave you with a thought for the weekend – “Life is full of tradeoffs.  Choose wisely!”

Metrics, Symptoms and Cash Flow

Metrics can tell us if we are moving in the right or wrong direction and that, in itself, is useful.  However, metrics by themselves do not help us assess our competitive position or aid us in prioritizing our efforts to improve.

To understand our competitive position, metrics need to be benchmarked against comparable peers. Benchmarking studies are available, some of them free.  They tell us where we stand relative to others in the industry, provided the study in question has sufficient other data points from your industry (or sub-industry segment).

Many times, getting relevant benchmarks proves challenging.  But once we have the benchmarks, then what?

Does it matter if we do not perform as well as the benchmark of a particular metric?  If that metric affects revenue growth, margins, return on assets, or available capital, it may matter significantly.

But, we are left to determine how to improve the metrics and with which metrics to start.  

Consider an alternative path.  Begin with the undesirable business symptoms that keep you up at night and give you that bad feeling in the pit of your stomach.

Relate business processes to symptoms and map potential root causes within each business process to undesirable business symptoms.

Multiple root causes in multiple business processes can relate to a single symptom.  On the other hand, a single root cause may be causing multiple undesirable symptoms.  Consequently, we must quantify and prioritize the root causes.

“Finding the Value in Your Value Network” outlines a straightforward, systematic approach to prioritizing and accelerating process improvements.  I hope you will take a look at that article and let me know your thoughts.

Thanks for having a read.  Remember that “You cannot do a kindness too soon, for you never know how soon it will be too late.”

Have a wonderful weekend!

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