Every company would love to have explosive growth that helps ensure the health and long life of the enterprise. And they would all like to master accurate growth forecasts. But the reality is that most businesses have stable and predictable growth over time that allows them to plan and map out a course for the operation.
But there are a few that fall into the first category, experiencing a growth rate so large that it takes them by surprise. Startups are one example of high growth operations where double, triple, and even quadruple-digit growth rates may be experienced. This has also been true of food companies, delivery companies, and companies that have made or switched to making PPE during the COVID-19 crisis.
While these growth levels are often thought of as “good problems to have”, predicting the growth rate in any rational manner is challenging. This is especially true when there is no historical data, or when the historical data can’t be used or relied upon. When this happens, what can planners do? And what actions can they take to calculate high growth in a way that helps keep their data history straight and reliable for future iterations of demand and supply forecasting?
History Isn’t Everything
When planners encounter a high growth dilemma, many default to a “history only” mindset. With sales pouring in, the planning effort becomes disordered resulting in an equally chaotic flurry of spreadsheets. But history isn’t the only thing that can be used to offer up growth forecasts in the face of highly volatile demand. In fact, because past experience and results alone don’t consider other market factors driving the growth, it may not even be the best way to forecast.
The key to better high growth forecasting is to understand the variables involved other than history. These can be analyzed for direction and quickly rolled into a calculation that makes sense and can provide direction for the supply chain. With so much at stake, human beings simply can’t make the calculations and analysis necessary to disseminate all of it. To do this, best-in-class planning software can help make sense of the variables. This allows a deep drill down into the data that can be used for predictive analysis, developing a forecast for high growth when history just won’t cut it.
Here are five steps that companies can take to chart their growth forecasting course through boom times when utilizing advanced software:
1. Conduct ABC Analysis: While a company may not know the growth level that is to come, they can analyze the value of materials–and by extension the finished goods they are used in–to know what materials will have the biggest impact on inventory. If the sales orders are for product lines with expensive raw materials or low margins, forecasts can be aligned with adjusted service levels to prevent over-purchase or cash flow issues on product lines that are not as profitable. The reverse of this is true as well, with the ability to classify high-margin goods and perhaps develop a forecast to ensure that the supply chain is stable regardless of the volume. Robust planning software will allow ABC analysis to peg the right items to shore up.
2. Identify Key Metrics: Regardless of the growth rate, most companies know their key metrics. If it is a high volume and low margin producer of commodified goods, supply planning may indicate changes to the supply chain in one direction. While for low volume high margin goods, it may indicate another path. This may also apply to a company’s product mix, where some high and low margin goods are made in the same facility. Software will allow for goods to be projected by revenue, cost of goods sold and margin down to the item number to help visualize KPIs.
3. Research External Factors: Demand and supply planning is carried out using inputs other than just those within planning departments. By researching external factors and collecting inputs from across the organization, data from market research, sales, product development and other functional areas can be leveraged to bring into focus what’s driving the surge. Planning software allows for these inputs–as well as inputs from the enterprise ERP–to be considered when enhancing the accuracy of forecasts using data from those on the front line.
4. Compute Multi-Echelon Demand: As software allows transparency in demand and supply planning, the supply chain is visible to the whole network. This enables data to be aggregated and analyzed at different levels, taking into account inventory and inbound material at any level. This visibility of the system and in managing material as a “pool”. reduces the chance of stockouts as well as over purchasing.
5. Test Both Conservative and Aggressive Strategies: Traditional planning was usually an uneven blend of disconnected systems, calculators, spreadsheets and gut instinct. And producing a forecast was a long procedure. Planning software anticipates outcomes by introducing “what-if” analysis over multiple scenarios. Using a strategy ranging from conservative to aggressive can help develop a happy medium that makes sense for the level of sales coming in.
Planning doesn’t have to be chaotic, even in high growth situations. But spreadsheets and unproven intuition will need to be replaced by software that can take all the non-historical data and detect trends and demand patterns that can drive forecasting. Because this data is real-time, the system can be changed as new figures become available. Using advanced demand and supply planning software from DemandCaster can drive accurate calculations to help manage high growth using data-driven analysis when history alone is unreliable.
