Metapraxis writes on design and business analysis
In times of change and uncertainty, there can be a temptation for executives to discard those practices and processes in business management which assume business continuity. While such techniques are aimed at reducing uncertainty on the assumption of "business as usual", that is something that many sectors of the economy no longer enjoy, even at the best of times. However, a focus on continuity and assurance is just as useful in difficult circumstances as it is during easier times.
Confidence, both internally and externally, has a big part to play in driving business success. But confidence can only come from knowledge, and routine gathering of insight on the performance of the business. Such practices include targeting and monitoring the performance of the business using monthly budgets, quarterly reforecasts and annual plans. But the conventional means of applying these are not sufficient for modern business management. In order to drive an effective strategic response, managers must modify their approach to creating and using them.
One area where this may be particularly true is in the use of visualization, as poor visualization can be hugely misleading. An example of this might be a simple line graph – choice of scales on the y axis can make the difference between a gradual trend and a cataclysmic change. A less obvious, but no less important instance is the comparison of budget, forecast and actuals. In the chart below, it’s clear that sales have fallen short of budget, but the difference appears small, is getting smaller, and perhaps has even been closed in the most recent month.
However, if we calculate a cumulative variance, and represent that as a continuous trend, rather than a serious of monthly reports, the underlying situation is made clearer:
In this case, the management forecast suggests that the current shortfall will be made up by the year end, but this can only be done by closing and delivering the sales in the weighted pipeline, and the additional work to win. This should prompt the identification of actions to make sure that the actual results to the end of the year meet the results that are currently forecast.
This data transformation may seem simple – elementary, even – but it is surprisingly uncommon, particularly in large organisations, where budget, forecast and results information may involve collecting data from many separate systems. However, making the investment necessary to bring these together is worthwhile, as it offers real clarity on the health of a business’s finances. It is one example of a slightly unconventional approach that can yield very large improvements in the quality of insight.
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