The tension between finance and the commercial function will likely be familiar to you.
Your FP&A team spend their time wrestling the numbers to get the budget and forecast sorted. They view these resources as indicators of how the business is performing: how many miles are on the clock and what speed you are moving at.
Meanwhile, the drivers of the business – the commercial function – are looking for sat nav. Something to tell them how to reach their destination and how long it will take them. Once they get there, they’ll work out the speed they were going at, their mileage and how much fuel they used.
The distance between these two attitudes can quickly lead to a disconnect, with separate functions pulling information from different systems or handling the same numbers in different ways. Everyone is striving for financial insight but it’s not marrying up across the business and that costs you money.
Complex operating models
Most organisations involve multiple systems. For instance, if you provide goods to another business, it’s likely:
- You manufacture some of them yourself
- You assemble some from components
- You act as reseller for add-on products to those you manufacture.
You may also provide additional services around these goods, including maintenance support.
Manufacture is a function of machine time, people on the machines, unit costs, raw materials. It also considers scheduling – raw materials in stock to enter the manufacturing process and finished goods to be dispatched. Across the operation there are likely to be inventory management issues in two or three areas.
If you imagine this business model, there might be three or four systems managing all the operations. Or there could be a single system that is using information in different ways according to the process being considered.
Where there are multiple sources of information within the business, if FP&A don’t provide the answers the operations function wants, they’re likely to revert to a different business intelligence tool or data set and make plans outside of finance. At best, this approach creates another externally generated variable to be factored into the forecast. At worst, it leaves your FP&A team cut off from the rest of the business.
The danger of fixed assumptions
When it comes to variables for the forecast, in a complex operating model like the one above, things can get very complicated very quickly. That’s where fixed assumptions start cropping up: your spreadsheet-based system can’t handle the complexity of the variables in your operating model. It’s too hard to capture real-time performance information for each individual machine in the process so an average is taken across a certain period. Each of these fixed assumptions that creep into the forecast leads to more potential issues and clouds the possible insight you can derive from your results.
Consider the manufacturing example. Within the factory, there are variable rates of wage, machine costs and raw materials. As soon as a fixed value is created and you assume a unit cost of manufacture, the numbers going into your budget and forecast are immediately skewed.
The figures are based on a fixed value for a certain period and this data is then going to be used as a single version of the truth to drive decision making in real time. If the true value of the cost of manufacture varies at all during the period in question, a natural error margin has been factored in. As a business, you are not going to be able to make the most profitable decisions if your insight is derived from inaccurate data. There will be a cumulative impact on your bottom line.
Fluctuation behind the assumptions
When it comes to the end of your financial period and there’s a deviation from budget, whether you’ve performed better or worse than expected, you ask if that performance is down to cost, price or volume?
When you’re working off fixed values that have been assumed, what might initially appear to be an outperformance on cost could be unreliable. If the actual variations behind the value that you have assigned fluctuated, the reality behind the numbers could look very different. The business intelligence is clouded – what was the actual cost across the period?
And then we come back to the tension between business units. If similar numbers are being used from the same business intelligence sources but that data is being handled in different ways, expectations and results stop aligning. Your team might commit to a certain result and feel that they have delivered on this promise because the drivers they manage have performed as forecasted. But if you’re looking at a single output figure derived from a range of fixed assumptions, you might start questioning their results. The problem is, you’re not evaluating the results from the same metrics.
Centralisation is key
Having a centralised data set, accessible from the top down, allows your whole business to work to a core set of numbers. It gives you the ability to move all the way from top-line group performance – company performance – project performance – job costs – part costs – line items. With the power of TM1, Planning Analytics enables you to follow the numbers down in just a chain of clicks, accessing real-time values which are all tied together in a single version of the truth at component level.
Move away from wooly planning based on fixed assumptions and differing handling approaches for your data and power profitable decision making based on the realities of your business operations. Get in touch today to discover exactly how valuable Planning Analytics could be to you.