The Danish physicist Niels Bohr once said, “Prediction is very difficult, particularly if it’s about the future.” This esteemed Nobel laureate understood this premise long before we had the ability to make predictions with technological advancements. If Mr Bohr were around today, and possessed at least a basic understanding of modern computing, he might not have viewed prediction-making as inherently problematic.
How to Use ERP to Predict the Future
Advances in technology have made forecasting the future a more reliable endeavour than ever before. In the business world a standout example is ERP software. Enterprises of all shapes and sizes with ERP now possess the power to make forecasts with an incredible degree of accuracy. In fact, if you’re the owner of an ERP system and are not taking advantage of its forecasting capabilities, you’re almost certainly not using your ERP solution to its full potential.
If you’re a wholesaler, manufacturer or distributor, proper use of your ERP’s forecasting functionality will lead to better managerial decision-making. The more well-informed your business decisions and strategies are, the brighter your business’s future will be.
This is because the typical modern ERP system solution relies on a centralised database. The database stores huge volumes of data from various business functions. By connecting all core business units together (eg finance, sales, inventory, warehousing) in the one unifying platform users can share data, collaborate effectively and base business decisions on information that is centralised, comprehensive and easily accessible.
Prior to the advent of today’s powerful ERP system, an organisation’s business data was typically scattered throughout different software applications. The lack of integration meant that it was virtually impossible to gain a 360 degree view of a company’s performance. Now it’s a different story altogether.
Today, ERP‑driven business forecasting leverages historical data to predict how the business will perform in the future. Data from each relevant business unit feeds into the forecasting mix, giving you a broad view.
But it doesn’t end there. In addition to historical data already contained within your ERP solution, you can also add various sets of external data to improve forecast accuracy. Examples might include anticipated future customer demand trends, expected new government policy impacts and other changing conditions that can be expected to play a role in future business performance.
So what types of forecasting might it be worthwhile to carry out? Let’s look at three of the primary ones.
In the manufacturing, wholesale and distribution sector there is often an inherent tension between the sales, warehouse and finance units of a business.
- Sales managers need adequate inventory levels so that they can meet sales targets and keep customers satisfied.
- Logistics managers need their sales colleagues to accurately forecast demand so that they can ensure that there’s always enough available inventory.
- And finance managers need to keep excess stock to a minimum in order to avoid cashflow problems.
A good ERP system will take the guesswork of inventory forecasting by telling you what you need in stock, when you need it and in what quantities. You can calculate your future requirements based on data to do with customers, vendor lead times, geographies, product types and seasonality (eg Christmas). When you can fine-tune your forecasting so that supply consistently meets demand without tangling yourself up in surplus stock, you’ve hit upon a formula for enhanced business success.
ERP provides complete visibility of a business’s financial operations, tracking every single dollar that the business earns and spends. Budgets and forecasts can be created by combining historical data with expected changes in customer demand, market conditions and other factors that will likely impact future cashflow and overall financial performance. For example – price changes, capital equipment investments and changes to the labour force.
What we’re talking about here is the application of both the quantitative and qualitative methods of forecasting. Quantitative forecasting uses solid, objective data of the type that is housed within your ERP system. By accessing and analysing that data, past sales and finance information can be used to predict future trends and outcomes. Qualitative forecasting is more subjective and applies the manager’s expertise with the market, the business and the industry it operates in to predict future developments. Used in combination, these two approaches will produce the highest likelihood of accuracy in sales and finance forecasting.
Your business has a big project coming up. How long will it take from start to finish? How much will it cost? What resources will you need to get it done? It’s at times like these that you require a planning and scheduling strategy that is accurate, flexible and which takes into consideration every aspect of the task.
Using historical data within your ERP along with your specialist expertise, you will be able to plan with confidence. Setting realistic expectations as to how the job will go while laying the groundwork for its successful completion.
The Takeaway
It is beyond dispute that no business is ever stagnant; every organisation ebbs and flows and is compelled to adjust to ever-changing conditions as they occur. It is well recognised that ERP provides an outstanding toolset for helping businesses pivot in response to shifting landscapes. And that’s all well and good as far as the present goes. To help ensure future prosperity your best bet is to exploit the ERP-driven business forecasting tools that are available today.
Every business owner should be sighing with relief that the days of relying on Excel spreadsheets, miscellaneous manually-produced reports and finger‑in‑the‑wind guesswork to predict future business outcomes are over. While ERP will never – in fact, can never – be perfect as a business forecasting tool (no ERP system would have been able to predict the coronavirus pandemic and its disruptive impact on the business world, for example), it does largely deliver on what it promises. And the more data you have, the greater its ability to support reliable forecasting.
If you enjoyed this blog, please read about How to Minimise Product Returns.
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