Sales Forecasting Through System Shocks
Foreceasting Sales as a Foundation For System Shocks
The Way Most Businesses Forecast
Most businesses, to a large degree, forecast sales using the naive forecasting method. Put simply, this was what we did this time last year, with a little bit more added on. It may be possible, although I have never been on the receiving end of it, with a little take off. Naive forecasting is the very basis of sales target settting and planning, but it is also the simplest and most prone to error. Naive forecasting may well have been the way of the world at the begining of business. Luckily though, it didn’t take long for people to begin adding their own information into the mix to begin to start to move the goalposts on sales planning. I have worked in very large global companies where the the sales planning strategy is naive forecasting, with a lot of information layered on top of it. In all honesty, this is how a lot of businesses work, and good businesses at that.
However, you can’t turn solely to these feelings with any industry shock, be it an outbreak of a virus, or something more positive effectively with just gut instinct. Sure it was obvious that England making it through to the semi finals of a world cup, along with a hot summer people, would buy more beer. However, through statistical analysis, the true upturn in sales could have been much more widely known, discussed and acted upon.
Why Naive Forecasting In a Shock Might Not Be Enough
For me to comment on what is needed, depends on a business situation and it’s appetite for risk. Why risk? I hear people say. I say risk for a simple reason. With a tighter outlook on sales forecasting, through uncertainty and industry shocks, be it positive or negative, we have a greater need to derisk areas of business and maintain control.The issues faced by big business and SME’s may, at some points, be different. Whilst at others the same. However, the takeaway here is that there are not many business should be actively risk seeking in all of their endeavours. Having a greater level of knowledge can, generally, reduce the risk that is faced by any business. I have outlined some examples of risks that can be mitigated with solid shock planning.
Having an understanding of the risk and potential impact on stock levels allows a business to order the correct quantities in advance. Don’t forget, these can be peaks, as well as troughs. For example, a pub may have to evaluate how much beer to order based on temperatures expected in the summer period, whilst this can be done with naive forecasting and a little knowledge that a heat wave is imminent. A legitimate data driven approach will give a much tighter start point, than simple naive forecasting. Allowing, if neccessary further input from the team to tighten the forecast further.
Knowing a spike or decline is set to occur gives businesses an opportunity to adapt to these changes from a labour perspective effectively. Going back to the beer analogy, knowing there will be a 46% increase in sales through a summer period, begining in 9 weeks, and that it takes a 3 week onboarding cycle. The hiring period would be around 8 weeks prior to the spike starting. Ensuring a good level of staffing where required. Conversely, should there be a decline, it may be best served to begin certain process improvement projects, or reallocate staff to other areas of the business, not over-burdoning the business with extra labour in the wrong areas. Drastically impacting productivity and conversion costs. Adversely affecting the bottom line.
Direction and Targets
By understanding what the potential peak or trough of any potential impact of such a shock will allow a business to incetivise and retarget staff accordingly. This will reset expectations and instill confidence that management are aware of what the situation is, and are planning accordingly. For situations such as COVID-19 – this could involve release of information on potential sales decline, and what is expected of employees. Allowing management to communicate effectively why decisions are being taken. What the plan is, and how it will progress with ongoing analysis.
If through conducting correct data analysis, it may become apparent that a business fortunes is directly linked to another element. This could be outside of it’s control. It may sound basic, but for ease of understanding, let’s go back to the pub. If a pub only makes profit due to soaring temperature and beer garden sales. What happens if there is an extremely cold winter. Noting just how much the reliance is on external factors allows businesses to diversify. Focussing on revenues not directly linked to that external factor.
There are other options open to businesses in such system shock situations, one such being the use of Holts-Winter forecasting methodology. Holts-Winter takes an external data source, and internalises that datas effects on sales. Holts-Winter itself takes into account seasonality, allowing the user to internalise the external dataset to the model. Through trial and error the user can determine if the external dataset is firstly relevant. Secondly, how it can relevant it is, through minimising the standard error and mean squared error. This can be used, in situations such as those we find ourselves in now, to internalise infection numbers and their relevance on sales over time. Or daily average temperatures.
Applying The Data Into An Outcome
Ulimately, the goal of any forecasting isn't to produce pretty graphs, or range outcomes based on moving datasets. Data is a guide to give direction to how a business should react to potential outcomes. At Akcela, we support businesses not only in producing such data, but implementing actions based on their findings to drive efficiency and positive outomes. Contact Akcela to find out more.
This post is a shorened thought provoker, edited from the original post found at https://akcela.co.uk/sales-forecasting-through-uncertainty/