In this series, we explore how the longer-term demand plan should play a more prominent role in businesses. The first two parts dealt with the key elements in setting up the demand planning and forecasting process, and this time, we will explore what the key behavioural elements are, i.e. what we do with the process and the outcomes when we get them. You can read Part 1. here: https://bit.ly/2MpyPzS and Part 2. here: https://bit.ly/2ALsebk.
Influencing behaviour and what to do with the outcomes of good process
In the first two parts of this series exploring the role of the longer-term demand plan in businesses, we described the mechanics behind what is required to achieve a robust demand-planning process. This second pair explores what to do with the process and plans once they are properly set-up.
Let’s begin with the end in mind and paint a picture of the relationship between strategy and the value of long-range demand planning and forecasting. A Harvard Business Review study of 500 companies over 50 years (some 25,000 years of data) on why growth stalls in well-established companies, initially shed little light on the cause although the symptoms were interesting. The study showed that:
- There was a last burst of energy, where sales the year before the stall, were typically buoyant, if not, the best ever.
- The decline was not a steady descent; it was a sudden drop.
- Few, if any, of the senior team saw it coming.
What emerged from the analysis was that more than 70 per cent of the reasons for the stall could be classified as strategic in nature. This dispels the notion explored in part one of this paper that getting the short-term right means the longer term will take care of itself.
Tying this into observations made by other authors, a pattern starts to emerge about strategy:
- Only five per cent of the workforce understands strategy.
- Only 25 per cent of managers have incentives linked to strategy.
- 85 per cent of executive teams spend less than one hour per month discussing and working on strategy.
- 60 per cent of organisations don’t link budgets to strategy.
The first five keys to Realising the full potential of demand planning were discussed in Parts 1&2. Before we get into the remaining five keys, there is an underlying principle we need to understand, which not only relates to demand planning but almost everything we do in business, too.
This principle is that there is only one thing we are doing in business and that is, influencing behaviour (it is important to add, ‘… with integrity’ because otherwise, it sounds so manipulative). Think of any function within a business and you will see the behavioural element, for example:
- Selling: finding customer needs and converting the sale.
- Marketing: developing a brand image and increasing consumer recall and recognition.
- Human resources: facilitating an effective working environment.
- Information technology: facilitating effective work flows.
The fact is, that unless there is a behaviour change, it doesn’t matter how good your processes are, how capable your people are, or how sophisticated your computer systems are, it will all amount to nought unless there is a different behavioural outcome. So let’s look at how this might apply to the demand planning process, with keys six to ten.
- Assumption management of the whole 24-month horizon
“During my 40 years at Gallup, I’ve observed that one of the main reasons very talented leaders fail is because their thinking failed them; not their leadership or management skills, which in many cases are just fine, but their thinking. Specifically, failed leaders in business and politics are usually wrong about a core premise that drives all their strategies. Because they are so wrong about that premise, every subsequent decision they make is bad.” Jim Clifton, chairman and CEO of Gallup.
Coming back to the Harvard article, ‘Why Growth Stalls’, these are the key elements underpinning the reasons for growth to stall:
- Assumptions about the business model are not written down
For some reason, this is one of the hardest elements of a business to change. Documenting assumptions is typically done just once a year (if at all) as part of the strategic and business planning process, and promptly forgotten until the following year. Often, they are also merely qualitative statements, that are not quantified or time phased.
When a company is struggling with this, the first thing I ask them to do is to write down the assumptions in their strategic and business plans.
The next is to word them in such a way as to be more easily quantified. For example, during one workshop, a client came up with an assumption that a key segment for sales in China would remain stable in the next three years.
Through the workshop, it was refined, so that it finally read, the volume sold in China would be 200,000 tonnes, at X price, with X COGs, until August 2019, thereafter the volume would slowly decline by one per cent per month until August 2020, seasonally adjusted.
Once we have this, we can create the sort of table shown in figure 1 and measure accuracy. Yes, measure accuracy. This way we drive continual improvements, and if it is hardwired to the outcome plan, once an assumption is changed, the plan must also change.
Dealing with the gap or bad news that a change in assumption may create, is another story, which we’ll cover later in the paper.
- The marketing model has not been updated in several years
It is imperative to make sure the market is modelled from high-level industry or category level, right down to how it interfaces with the bottom-up, detailed forecast. The key areas identified as ‘missing’ from those companies whose growth had stalled were:
- Market share assumptions had not been updated in a long time.
- Consumer testing of key attributes was done infrequently, if at all.
- Competitors were getting better at translating consumer insights into new products.
- Consumers were becoming less willing to pay a price premium for the companies’ brands.
By way of illustration, Professor James O’Toole researched the prevailing set of working assumptions that General Motors held during the 70s. These were both explicit and implicit.
At the time, General Motors was the number one car company in the world, and now, nearly 50 years on, the impact on current performance can’t be separated.
Behaviour checklist 1.
- Document assumptions.
- Quantify, time phase, and measure accuracy of assumptions over the whole demand planning horizon, e.g. 24 months.
- No number changes unless an assumption changes.
- Understand and use uncertainty
“If I was that good at forecasting, I wouldn’t be doing this – I’d be at the races every Wednesday and playing the stock market the rest of the time, and I would be very wealthy indeed.”
Or so I was told when I first starting learning about forecasting. The expectation that our demand plans are going to be ‘right’ is a misapprehension.
However, let’s look at some of the things we can predict with a fair amount of certainty.
For example, we can predict that the sun will rise at certain time, in 12 months’ time, or even 10 years’ time … and if that forecast doesn’t come true, it is not going to matter too much because none of us are going to be here anyway.
This is probably not going to be too useful in the demand planning and forecasting space, but coming down a level, I can predict Christmas, Easter, New Year and so on, easily enough. This is now starting to get to a level of granularity that most companies can deal with, and indeed need to deal with. Another level of granularity could be, the number of competitors, how many new products they’ll launch or promotions they’ll do, which is a level of detail that we can build and test assumptions around. The important point is to decide at what level to align key strategic drivers and then plan for ‘normal-cause’ variation around anticipated outcomes.
Managing uncertainty plays an important role in the integrity of the longer-term plan. The critical element is to understand the impact of a small raft of quantified assumptions (key 6. above), use those assumptions to derive our projections, and then assess the ‘normal-cause’ variations to those assumptions. This is more commonly done as an opportunities and vulnerabilities (risks) assessment.
By definition, an opportunity is not in the demand plan, but if certain assumptions come true, it could be an upside. A vulnerability, on the other hand, is something that is in the plan but if certain other assumptions come true, it may reduce the plan.
As mentioned above, in a robust demand planning environment, these opportunities and vulnerabilities should be balanced on either side of the expected outcomes, and importantly, accompanied by agreed contingency plans to facilitate swift responses if these assumptions come true.
Often companies don’t plan for the risks, which is obviously not a good thing, but when a company can’t respond quickly enough to an opportunity, it’s even more troublesome.
Behaviour checklist 2.
- Understand and plan for uncertainty.
- Don’t bank all your opportunities in the annual plan.
- Opportunities and vulnerabilities contingency plans.
This article will continue in the January-February issue of MHD Supply Chain Solutions magazine. Rod Hozack is a partner at Oliver Wight. For more information email firstname.lastname@example.org or visit www.oliverwight.com.