This is a part 2 of a series, following recent part 1, Best Practices to ensure investments in S&OP software and Forecasting deliver measurable benefits – Number One.
Okay, after the hugely controversial and panic-inducing selection at Number One, no one should be at all surprised that Measurement is Number Two as a best practice of S&OP and demand forecasting investment. Business strategy is rapidly evolving to accommodate more complex and sophisticated views of how firms determine and execute their strategies. New momentum is gathering around strategies such as Multi-Echelon Inventory Optimization, (MEIO), and Segmented Supply Chains, (SSC), all of which should be managed within an S&OP framework appropriate for your value chain.
Measurement, as it pertains to those strategies, is bringing multiple pieces of the organizational puzzle together into an integrated framework that aligns your strategic initiative with the assets necessary to execute and the information critical for improved decision making. In this blog, rather than recreate what has so professionally and exhaustively been researched and published, we will provide practical feedback from our clients as to why they focused on measurement and what they measured.
Because everyone has accepted that it is a good idea and your company has just spent big dollars on a BI tool?
Or, because there are a large number of pithy quotes out there that seem to make it obvious? — Such all time classics as:
1. “In God we trust, all others bring data” – Deming I think.
2. “You can’t manage what you don’t measure” Is that Drucker or DeMarco? I always forget.
3. “You get what you measure. Measure the wrong thing and you get the wrong behaviors” This is definitely Lingle.
4. “What gets measured gets done, what gets measured and fed back gets done well, what gets rewarded gets repeated” This is Jones and if you need proof of the truth of this quote – ever train a rat in psych class or one of your own kids; in a related note please see best practice number One.
5. And my personal favorite “ The only man I know who behaves sensibly is my tailor; he takes my measurements anew each time he sees me. The rest go on with their old measurements and expect me to fit them.” Shaw
George Bernard Shaw really gets to the heart of it – in order to achieve upfront and ongoing benefits from your investment in S&OP and demand forecasting, you need to measure because everything is changing and you need to honestly and correctly look at how things really are today, (and how they are trending moving forward), not what they were last year when you were doing a plan. And in order to look at thing as they are today, you need a measurement framework that allows you to understand what is changing, the impacts on your business of those changes, and the decision criteria for addressing those changes.
But many of you may be reading this and saying hey – yeah, very clever, using Shaw to get to the truth of measurement, but I can’t use that to convince my teammates that this is a good idea, so how about something useful?
Okay then, a couple of other reasons to measure:
1. It will increase the value of your business – whether public or private. Useful measurement frameworks are indicative of well run companies. “Well run” companies that earn that designation are rewarded with higher valuations, which means better rates from lenders and higher valuations from investors. In addition, for public companies, there exists a legal reason for measuring performance, and this is called Sarbannes Oxley (SOX). The value for measuring within this context can be summarized as:It’s critical for driving performance and decision making in downstream components of the value chain. Measuring forecast error performance is important because the actual outcome – Forecast error – is specifically used in areas such as safety stock, raw material/component purchasing, production scheduling, order management, supplier performance and others.
a. Higher level SOX compliance reinforces reputation and trust for a specific company within the investing community, thereby potentially making said company eligible for inclusion in certain pension and investment portfolios, which increases demand for the stock.
b. The associated improvement in forecasting revenue and related financial measures helps support and potentially enhance the valuation of a company as reflected in the stock price.
2. It supports collaboration and learning. If professionals within your organization believe that the measurement is fair, consistent, and tied to strategic initiatives, then the focus becomes less on CYA (cover your ass…) and more on looking at what the measures are revealing, and looking for areas to learn and improve. If forecast error reports are used to understand which inputs are most useful, everyone better understands their role in driving accuracy, the impact of accuracy, and how to get better.
What to Measure:
Our clients have focused on what to measure around S&OP and demand forecasting, so that is what we will focus on here.
1. You have to measure at the lowest level of detail. Ideally in forecasting, what we have seen drive the best results is a focus on measuring the execution level of forecasting – that level that drives operational performance. The trick is how to measure the details but still make the measurement and reporting of that measurement (formats, GUI etc.) easy to use and effective at highlighting issues that need attention and action (and yes, we at DF think we have a pretty nifty solution around this).
2. You have to measure the input of the professionals involved in the S&OP and forecasting process. This includes all participants, internal and external. Practically speaking, this means managing and measuring multiple forecasts. Typically you see one from sales (and perhaps marketing), and operations certainly have their point of view. Finance adds value from a top down perspective, and there might be other internal forecasts. It then becomes part of the S&OP process to work through the different perspectives and arrive at consensus (whether authentic or dictated). In addition, we see input from customers more and more often. This is where the whole learning and collaboration point above comes in. Your customers usually are horrible at forecasting. I mean they suck, and that should be no surprise, as they focus on what is best for them. That usually means “more product is better,” especially in situations where they can return excess product or don’t pay for it until sold – (VMI type situations). Being able to measure their error, then go back to them with the impacts of their error-ridden forecasts and offer intelligent and verifiable alternatives can often help you be a value added partner.
3. You have to measure the input and impact of data. This is becoming increasingly important as more data becomes available more often and in bigger quantities. This boils down to constantly reviewing what information is driving your S&OP process and whether it adds value. Historically, shipment history has been a big drive and it will continue to play a role moving forward. But now there is a growing abundance of what we call Type 1 external data. This is data that exists within your value chain and comes from your customers and suppliers. A good example is Point of Sale data from retailers. Does this impact forecast accuracy? On what time frame? Then there is what we call Type 2 external data and this captures causal data which has been addressed many times in this forum and others. The key is what data helps and how so and what data does not help so that it can be ignored and/or not collected anymore. This is a very underutilized area of measurement.
4. You have to measure the impact on the strategic imperatives. What is the impact of a certain level of forecast error on EBITDA? Or Margin? Or working capital levels? Measurement must occur within a context, and for the businesses we are fortunate enough to partner with, that context is strategic imperative. This is the basis for justifying the investment in S&OP and forecasting.
Measurement systems are critical to both the company as well as the individuals who drive the company. They capture and disseminate strategic information and outcome measurement for the firm, and performance measurement, incentives and motivation for the individual. They can be feedback not only on the forecasting technology, but also on the process and people involved, especially on the effectiveness of the demand planning function within the company as a whole.
When done right, measurement systems, (and S&OP specifically), can become the primary means for a company to understand (coordinating what a company knows and learns) and to do (how a company alters and improves what it does).
Given that importance, we feel strongly, (as do our clients), that it is time for a new framework of measurement specific for S&OP and forecasting. In a follow up blog, we will cover our thinking about what that new framework is and how it should be done.
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