27 Mar 2023
In our last blog we looked at why assumptions are so important for organizations, but how do you manage assumptions effectively? In this two-part series we uncover our ten keys to effective assumption management to help you create robust processes to ensure you get the best possible set of assumptions. This will ultimately help your business’ longer-term viability. Let’s discuss the first five keys:
1. Source key drivers of plans from history and existing information
The two areas to source assumptions from are your historic and your strategic planning process. If you spend a little time thinking about the past, you will find events that impacted your plans, and this should stimulate thinking about what is in store for your business in the next few years. Statistical forecasting packages are another source, and work from historic sales data and apply the rule that if history is going to repeat itself, what is the closest statistical correlation can you model future sales on? This is called the ‘anchoring effect’, which can corral the dialogue to what is going to be different in the future from what happened in the past.
2. Write the assumptions down
In the first instance, assumptions need to be documented and organized into categories that are useful to the Integrated Business Planning process. For example, what are you assuming about the Product Portfolio Plan, the Demand Plan, the Supply Plans, the People Plans, and the Financial Plans? These assumptions need to be held and managed in a central database. It is useful to embed assumptions in the analytics, such as ‘building blocks’ for creating the forecast, or the demonstrated capacity run rates to build the supply plans, but until your organization knows which assumptions are going to significantly effect outcomes, it will be a wasted exercise to get too sophisticated too soon.
3. Quantify and time-phase them
Once your key assumptions have been written down, they need to be quantified and time-phased over the whole horizon of the plans. Time-phasing assumptions should be more granular than annual buckets. Companies that do this well have monthly buckets to support the sales horizon, e.g. six-to-12 months, then quarterly for the next 12 months, and then half-yearly or even annual buckets thereafter, to support the marketing plans.
4. Measure them for accuracy
Companies will often not measure assumptions for accuracy or, if they do, do not tend to carry out the appropriate level of analysis. If assumptions are laid out correctly, measuring accuracy should be easy. You’ll just need to agree the lag time frame and divide actuals by the estimate to gain a percentage.
5. Do the root-cause analysis (RCA) and adjust assumptions thereafter
RCA is a process that requires discipline; it is not just a superficial reason or explanation. There are several techniques that could, and should, be used depending on the type of assumption. For example, if the assumption is about the defects on a machine, it is likely that reason codes are captured for misses and a Pareto assessment can be easily quantified. Often however, reason codes are not captured or are difficult to capture. In such cases, the fall-back position is to do the ‘Five Whys’ to dig down below the superficial reason and get to the real root cause. Another option is the well demonstrated PDCA Cycle (Plan, Do, Check, Act). However, the final question to answer is, ‘Once we understand the root cause of variance, do we need to adjust the future assumptions, and if so, by how much and over what period of time?’