Forecasts in the business landscape are based on historical data. Often, there are situations when data is limited or not available for forecasting. No doubt, forecasting without or with limited data can trigger several challenges. The dearth of sufficient data leads to misleading or wrong mathematical models, thereby creating impractical business forecasts. The good news is that forecasting with limited data is possible and valuable as well. There are certain steps and valuable approaches that help with forecasting with restricted data.

Considering the Present Financial Position

When one is working on regular tasks, often, the current financial position is overlooked. This is particularly true when bills are covered and the business enjoys a paycheck. Such data is not enough to anticipate the future and requires more data. Considering the present fixed data (loan, utilities, rent payments), variables (cost of goods sold and labor expense), and the number of customers, expenses and revenues are also vital.

One can begin forecasting the expenses first, as they are easy to predict and can be adjusted accordingly. Financial software is helpful as it demonstrates complete billing, which in turn helps determine the financial position for the next six months or even a year.

Utilizing Forecasting Software

There are multiple software applications available to predict business forecasts. It provides different ways to model a business by including or excluding factors and analyzing different scenarios. Forecasting software can be used to analyze elements like price points, marketing, staffing, customers, etc., and find out the ways the variables can influence the outcome. Despite limited data, forecasting is possible by assessing the best and worst scenarios. It is helpful to know the financial and operational impact of varying events taking place.

Surveying Customers

Surveying customers might not provide quantitative data, but it offers a deep understanding of the thought processes and opinions of customers about specific products and services. This is an excellent way of doing business forecasting with limited data or no data at all. The responses or feedback from customers and prospects indicate the future scenario. Surveying customers and acquiring their input generated a predictive model of future sales or ways to improve business.

Study External Factors

The lack of historical data is a common scenario in startups. This doesn’t mean forecasting is impossible, as existing industry trends and previous year data analysis are conducted. Given specific economic cycles and market conditions, such an assessment offers a picture of what occurred and might have impacted the business. Furthermore, studying external factors like international economic shifts, consumer demands, social, political, and environmental elements, etc., impacts the financial results of a business.

Conclusion

Historical data is considered a key component of business forecasting. Things that happened a few years ago or even six months ago are valuable and critical for business sales and profit predictions. But sometimes, a business doesn’t have any previous data or very limited data, making forecasting challenging. The concept of forecasting with limited data or data is often conceived as the end game for the business. The reality is that there are so many ways to forecast with restricted data.