An Integrated Solution
The typical Excel spreadsheet or standalone forecasting tool results in inconsistent data and multiple versions. Businesses cannot sustain this approach if they’re to utilize the data efficiently and react in time to make any changes.
The solution lies in engaging your staff to become a part of the process. Barriers need to be lowered to create and adjust forecasts; for example by integrating the process with an existing application. They’ll then take ownership of its efficiency and, in turn, take it more seriously.
1. Make it user-friendly
Lowering the barrier to users being able to enter data is the beginning of making them actually want to use it. Not only would it be a relief to your backlogged IT department, but it would put the onus on the users themselves. This results in a higher level of ownership throughout the process.
The Cohelion Data Platform, for example, allows you to capture forecast data on any KPI. It can be entered manually, through a loading process, or using machine learning algorithms. Using these algorithms, pre-filled forecasts will be created using historic data.
Forecasting data is available for comparison against actual data, as shown here:
With both historic and forecasted data available, you’ll be able to provide a guideline for your teams.
2. Use More than Financial Data
While the bottom line is important, the individual employees may not be able to immediately relate their assignments and responsibilities to a monetary value. If stakeholders can enter data in quantities that make sense in their own department, they’ll be more likely to not only use the forecasting tool but make it accurate and relevant.
Every team has its own goals. Relegating each of them to ROI isn’t always easily translated. However, if you utilize both financial and operational data, you can develop a much clearer picture.
It also creates a more concrete and easily understood way to achieve these goals. For example, if you have a forecast of a specific number of cars you need to sell, you can assign a number to the forecast instead of a monetary value. This will then provide very different insights for each department.
Users can not only study whether forecasts are met, but they can also ‘time travel’ to study how forecasts have changed over time. This means that users can not only review their business strategy but also check to see how good the forecasts have been in the past. It may be that the first prediction was far off, but that it became more accurate after 3 months.
In this way, you can begin to look forward instead of only backward!
3. Start with the People on the Ground
Your employees know what their daily tasks are, how long it takes them, and what’s most important to the department. If you allow them to provide the numbers that they think are realistic, you can then create a true forecast. This is opposed to the common ‘Top-down” approach, whereby a CEO sets a target to increase output by 4% this year. Those targets may not be realistic and are not motivating.
We think by enacting a workflow throughout the company using a bottom-up approach to capture operational data in addition to financial, each person and each department will feel a responsibility to complete their piece. The top-down targets can still be captured, but a well-substantiated alternative is there as well.
Predict with Confidence
Forecasting is important in making business decisions, but it can be hard to manage the entire process. Many businesses are not engaging their employees and or providing tools that empower them, so their forecasting leaves plenty to be desired.
By utilizing a process that enables all layers of the company to contribute, more of your staff will be part of it and encouraged to participate. Your people have the knowledge, let them be a part of the solution to being a more data-driven company and they’ll provide you with more insights than you’ll know what to do with.
The Cohelion Data Platform combines all of these features into a single and convenient business tool that can improve forecasting processes and analysis. With predictive functions and full oversight of the entire process, it’s the smartest way to create accurate forecasts and respond to changes quickly.