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By Christian Fournier, former Head of Finance Europe at Orange Business Services
For the purpose of this article:
The first step in forecasting is to understand where we are today and how we arrived at that point from the past. This is gain through analysis and reporting.
The second step is in projecting those evolutions and deciding what the company will do about it. This involves risk assessment and taking risks through strategical and tactical choices that need implementation.
The third step is putting all those in a consistent set of tools been plan, budget or forecast.
The loop back to analysis and reporting will measure how accurate were the projections and decisions implementation and measure the variances. It will generate the need for adjustment in decisions and forecast.
This clearly involves both “internalities and externalities”, specific to the business.
I will not insist here on the internalities i.e. the traditional flows of information through accounting, order processing, business cases, marketing and production statistics, etc… In most case, this is the easy part.
I will focus on the externalities that are more difficult to identify, capture and project and are part of competitive and business intelligence. They are by nature very much specific to each industry and business situation and then it is difficult to make a checklist that will cover all cases.
First, let say that there are companies who decide (consciously or not) to ignore some or all of those externalities and just implement on an ongoing basis the changes and reactions to the changes. It drives to short-term and high-stress management with little visibility.
In most case, there is some level of competitive and business intelligence that builds in or is at least available. The issue is whether it is sufficient and accurate enough? Is it really used? and then how to improve it.
Markets analysis (i.e. potential customers profiles, their needs and evolution, their financial health), competitors, their products and services and evolution, geographic reach and globalisation and etc. should permit to assess and take decisions linked to your company products and services competitivity. This will drive prices and profitability evolution, potentially, development plans.
How much information do you get? How much do you use in your forecasting activities? Is your forecast consistent with those externalities? How do you get organised to improve your level of information and better use what you have?
These questions are obviously not addressed to FP&A only but need to involve all departments. There are probably no standard responses. This is a collective effort in which FP&A should be a key actor.
Over the general economic situation, few examples:
A good way to look at it is to review how much you are able to explain actual evolution and variances.
Is it “We forecasted a 2% revenue growth and achieved -1%”
“The market growth was projected to be 1% which we forecasted to overachieved by 1% thanks to xxx actions, the market growth turned to be -3% due to heavy price battle whereas volume was in line for the 1% growth. We achieved -1% thanks to partly avoiding the price battle but our volume market share has decreased. In such context, the actions programmed where only partly implemented some becoming irrelevant”.
Is it “Our new product X achieved only 60% of the target whereas the previous version decrease by 50% in line with forecast. The resulting decrease in revenue is 5%”
“The new product was forecasted to cannibalise the old version on a 1.1 to 1 ratio in terms of revenue resulting on a 2% revenue increase. Our competitor AAA launch a new product version earlier than ours. As a result, in the initial phase, they gained market share. This seems to stop when our new version arrived. Still, it needs to be verified in the coming months and the revenues lost will impact our yearly forecast by 5%”.
Those purposely built and simplistic examples shows what level of information is needed to reach from the first to the second explanation both at the level of the forecast and actuals. It needs both a clear statement and tracking of the scenarios and decisions made at the time of the forecast and a way to keep track of the elements used in those scenarios.
In many companies, this effort is not (sufficiently) structured. Different departments and managers, have or gain part of the information (or just have their gut feeling!), integrate it more or less consciously in their actions or when preparing forecast and actuals variances with their FP&A partners. They generally react to changes rather than plan for the changes to come. When managers or key people move or change position, part of this information is lost or worse moved to competition…
This can be largely improved through a structured process that identifies the different sensitive information needed, organise the data gathering (even if incomplete or uncertain that will be better than none), structure it in consistent scenario(s), decide on the actions necessary to adjust to those scenarios and share it among management and FP&A. These scenarios are then integrated in a consistent manner to the forecasting.
The difference between these two situations may not seem important in particular in the period of relative market and management stability. It generally provides essential in unstable periods where reactiveness and agility are the key factors of success.
Forecasting is not just a statistical projection of internalities.
Forecasting is taking internalities and externalities into consistent scenarios through risks assessment and decision making.
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