Demand forecasting encompasses various perspectives among practitioners. While some perceive it as utilizing historical and present sales data to estimate future customer demand, this perspective may overlook the ability to forecast demand for new products. On the other hand, economic forecasters may implicitly assume that demand forecasting solely pertains to overall consumer demand, disregarding the specific concerns faced by businesses seeking to predict demand from their individual customers.
Why Is Demand Forecasting Important for Businesses?
Businesses recognize the significance of demand forecasting as it allows them to anticipate expected demand levels for their products or services, enabling proactive preparations. While forecasts don’t need to be flawless to be valuable, even reasonably accurate predictions can provide substantial assistance. Having an understanding of whether demand will significantly decrease, increase, or remain steady offers businesses the opportunity to plan ahead, whether it involves cost-cutting measures, expanding production capacities, or maintaining current strategies.
Effective inventory planning heavily relies on reliable demand forecasts. Insufficient inventory can lead to customer dissatisfaction, and revenue loss, and potentially harm future business prospects. Conversely, excessive inventory incurs costs in terms of storage, logistics, and the risk of unsold items, resulting in substantial investment losses. Therefore, achieving the right inventory balance is an indispensable aspect of a robust demand forecast.
Benefits of Demand Forecasting
Utilizing demand forecasting effectively can yield several advantageous outcomes for businesses, although not all benefits may be experienced by every company. Nonetheless, organizations that employ demand forecasting proficiently can expect to reap multiple returns on their investments.
Demand forecasting that effectively distinguishes between temporary spikes and sustained trends helps companies determine whether to seek financing through borrowing or attracting investors to support their growth. Furthermore, robust demand forecasts can serve as persuasive evidence to lenders and investors, bolstering their confidence in providing financial support.
Inventory Planning
Demand forecasting can generate significant advantages for companies engaged in inventory management across various types, including traditional consumer packaged goods, perishable items like fresh fruit, experiential offerings such as rounds of golf, and even services. It extends to consulting firms as well, where demand forecasting aids in making crucial decisions regarding resource allocation and assessing the need for additional hires.
Better Decisions
Effective demand forecasting provides business leaders with valuable insights for making critical decisions. It guides them in determining whether to discontinue a product, introduce a new version, or maintain the current course. It also assists in identifying potential new product opportunities and evaluating the feasibility of entering different geographic markets. These decisions, along with many others, can be informed by reliable demand forecasting at both micro and macro levels.
What Are the Major Demand Forecasting Challenges?
Demand forecasting in the retail industry is challenging due to both the nature of the business and the techniques employed to predict sales. Let’s explore the factors that contribute to these difficulties.
- The Dynamic Nature of Retail
Retail is known for its lack of consistency, as various factors constantly affect demand, making sales forecasts based on previous years unreliable. Let’s examine some of the factors that undergo continuous change, rendering year-to-year comparisons less accurate.
- Shifts in the product mix
- Locations and channels move or close.
- Alterations made by rivals
- Geodemographic shifts
- Calendar and promotional strategy modifications
- Variations throughout the season
- Price changes by the vendors
A change in any of these or other pertinent variables has a cascading impact on the business, from demand at the SKU level to the supply chain.
A rational approximation is required for inventory planning based on sales history. Sadly, approximations frequently result in lost sales, significant markdowns, and unrealized potential.
- Identifying and Accounting for Relevant Factors
Even worse than the fact that there are so many variables influencing supply and demand is the reality that none of them exists independently. To accurately predict demand, a forecast must take into account every relevant variable for each SKU at each distinct location. This explains why retailers who switched to demand forecasting from sales forecasting have been so successful.
This is the most challenging difficulty in demand forecasting to overcome for two main reasons.
- It is quite challenging to isolate every factor affecting demand.
Some variables which directly impact sales demand are seasonality, promotions, price elasticity, weather, product cannibalization, affinity, geo-demographics diversity, competitive data, vendor costs and agreements, inventory availability and so on.
- The complexity of computing demand increases exponentially with each added variable.
A retailer that sells through various channels and has 100,000 SKUs must deal with millions of data points. Analysts must manually sort, arrange, and calculate all that data for traditional spreadsheet-based forecasting. Without the aid of retail technology like advanced analytics, this strategy is impossible to expand because it is time-consuming, expensive, and error-prone.
- Fragmented Demand Forecasting Strategy
Due to the digital revolution, there are now omnichannel retailers who manage both brick-and-mortar stores and online sales. as well as a variety of other outlets.
This size of business management frequently results in a “divide and conquer” approach that isolates channels and departments. Working within a disorganized framework presents obstacles to inefficiency:
- Every procedure takes time.
- Ineffective communication and low visibility.
- Inadvertent mistakes and lost opportunities.
- Continuous manual intervention makes scaling difficult.
- Planning at the category level.
- Failure to take into account all relevant factors.
Cohesiveness is essential for an omnichannel retailer to succeed. Retailers can estimate demand with the highest degree of accuracy thanks to optimization, which is made possible by a unified approach to business operations throughout the whole product lifecycle.
This is crucial for fulfilling consumer expectations and ensuring a seamless customer experience.
About the Company
Fountain9 has developed Kronoscope, an advanced AI-powered demand planning software tailored specifically for retail businesses. This innovative solution offers highly precise demand forecasting capabilities across multiple channels, operating at a detailed level. By considering a comprehensive range of nine factors, including seasonality, historical sales data, consumer behavior, commodity indices, and even adverse weather events, Kronoscope ensures an accurate estimation of demand.
A notable feature of Kronoscope is its ability to generate precise demand forecasts for individual stock-keeping units (SKUs). This level of specificity empowers retail organizations to promptly meet customer requirements without relying on excessive inventory levels. By accurately estimating demand for each SKU, businesses can optimize their inventory management, reducing the risk of stockouts or overstocking.
