Demand forecasting is the process of making future estimations in relation to customer demand over a specific period. Generally, demand forecasting will consider historical data and other analytical information generated through machine learning (ML) and artificial intelligence (AI) to produce accurate predictions. The right ERP system gathers data through these applications and generates precise demand forecasts. In turn, this informs existing planning and pricing decisions.
For years, traditional forecasting algorithms leaned heavily on historical data. But with rapid changes in product preferences and consumption patterns, consumer packaged goods (CPG) and retail businesses need a more robust framework that includes factors other than just historical data. The pandemic accelerated the adoption of machine learning (a component of predictive analytics) as it could read and adapt to consumer habits.
Predictive analytics is an essential retail and CPG forecasting tool. It has the power to create insights to handle seasonal assortment, inventory changes and new launches. For example, if a manufacturer launches a new product, they want to be sure not to cannibalize existing products. Predictive analytics can tell leaders to modify sizes or colors to create enough of an assortment that it will not impact current or future predicted sales of existing items.
Another way to simplify merchandise planning and buying is through artificial intelligence (AI). Global supply chain disruptions and changing consumer habits have forced businesses to increasingly rely on AI to develop intelligent algorithms, allowing retailers to optimize the many moving parts of inventory planning and dispense with manual processes.
COVID-19 impact of demand forecasting
Typically a company looks at historical data and the marketplace. Decision-makers need to know what product lines will sell more or less this year, versus last year or years prior. Before COVID-19, companies generally were not capacity constrained. They could control supply and demand as much as their ERP system allowed.
When the pandemic shut down manufacturing, shipping and nearly every other cog in the business machine, production could not keep up with demand. This outlier scenario shifted demand forecasting. As an article by Oliver Wyman stated, “The current unprecedented level of business unpredictability is the result of wildly fluctuating supply combined with huge variance and uncertainty in demand over both the short and medium term.”
The role of demand forecasting
ERP systems provide increased visibility across all operating entities and access to real time data. This is crucial in complex demand forecasting, for example, when preparing new product launches, companies need to ensure the new product does not cannibalize demand for current products. If you are a shoe manufacturer, you might look into modifying your assortment, a function that would be nearly impossible manually, with disparate systems.
Some retailers like surfboard manufacturer Firewire had to respond to soaring demand for their product when the world shut down due to COVID-19. This was unprecedented in the company’s history. Their forecasting tools helped them see what a typical sales year would be, and the lead time needed for orders. While the supply chain slowdown didn’t allow them to deliver their products as fast as customers wanted them, they were still able to scale up manufacturing because Acumatica, their ERP system, had the necessary tools to provide transparency into operations, finance and inventory.
Demand forecasting is also critical in the professional services world. Consulting firms, creative agencies and other businesses that sell services rather than products must understand the future to monetize operations and plan for labor management. Forecasting revenue in this arena might encompass understanding what billing rates should be, or how many consultants you need on a project. Further, how many different levels of consultants with different billing rates will you need?
Demand forecasting business intelligence
One of the many functions of an ERP system is to manage supply and demand through business intelligence,optimizing inventory management. Demand forecasting is a natural precursor to planning these aspects of operations. It’s essential to invest in an ERP system that delivers robust business intelligence. The right business intelligence provided by the ERP system can show you what products are taking off and may require new strategies to fulfill customer needs, synchronizing production with customer demand. Setting KPIs based on data ensures accuracy and accountability.
At Crestwood Associates, we are software agnostic. Our experienced consultants have been advising clients in a range of industries for more than 20 years. Through over 5,000 ERP implementations all over the globe, we’ve learned how to help companies like yours avoid pitfalls and achieve success.
- We have a strong and deep team to support the complexity of an ERP implementation.
- We have experts in various avenues who can help solve problems on complex projects.
- We do not outsource any aspect of the project, saving time and money.
We advise key stakeholders on which technology solutions will have the greatest impact on your business goals by reviewing your system and processes. We then quantify the goals and map out a plan for action to achieve them. Contact us today for an ERP Discover and Advise Consultation Request.