Role of IT in demand forecasting
July 15, 2008 by Raj Sheelvant
Forecasting has become more and more complex lately. Customers are less loyal to the brand and global competition has become fiercer, making it difficult to predict sales. Adding to the problem: Products, sales and distribution channels all have proliferated, and the life spans of products have gotten shorter. As a result, some companies are being forced to adopt new ways to improve forecasting and planning. And a common theme links them all: collaboration, according to the WSJ article Thinking about tomorrow – Seven tips for making forecasting more effective.
The article notes that cutting-edge companies take collaboration further, integrating operations with vendors and suppliers in ways that give each party access to data that helps keep the supply-chain flowing and inventories lean. Once such links are established, a manufacturer, for example, no longer has to guess at a vendor’s inventory or future promotional plans, hence forecasts — and sales — improve.
Here are the seven tips from the article to make forecasting more effective
- Get Senior Executives Involved
- Explain the Mutual Benefits
- Clearly Define Goals and Agreements
- Use the Best Technology
- Focus Where Revenue and Profits Are Greatest
- Link Incentives to Companywide Goals
- Aim for Continuous Improvement
Of the seven important tips, I will focus on the 4th – Use the Best Technology. The role of IT in making a successful forecasting is very critical. According to the article:
Companies should use state-of-the-art technology and standardized data if they’re going to get the most out of collaborative forecasting.
There needs to be a central database where different parties can easily store and view the latest sales, inventory and purchasing data. Historical data are important, too, to gauge forecast accuracy over time.
All such information should use language and formats that are easy to understand and use, and products themselves should be tagged with standardized labels, like universal product codes, so there is maximum transparency for everyone involved, including vendors and suppliers.
Demand planners need a system that gathers data from different departments and sources. They also need strong calculating tools that can run a lot of what-if simulations, such as what would happen to sales if the company lowers or raises the price, decreases or increases the advertising budget, introduces new products, enters a new market, or exits the old one.
Supply planners have similar data-gathering and calculation needs. For instance, if a product is expected to be short in supply, should the company put on an extra shift or outsource? Or if supply is expected to exceed demand, should it halt production or build inventory for future use?”
The article although points to the fact that the future of forecasting depends on the use of advanced technologies, does not talk about existing collaborative and interactive technologies and capabilities that can be exploited. Though the non IT executives are aware of advantages of ‘collaboration’ in improving the forecasting process they are not aware of Web 2.0 capabilities that can be exploited to improve the forecasting. The article also does not talk about another existing technology: Business Intelligence. There are several Business Intelligence capabilities around the data that can be integrated to intelligently ‘feedforward’ relevant existing data into the next iteration of forecasting thus increasing accuracy.
This clearly indicates existing technological knowledge gap exists for the business strategist and non technical executives and is a great opportunity for the IT executives to bridge those gap. Several existing collaborative and business intelligence tools can streamline collaboration across the entire supply-chain. These collaborative Web 2.0 technologies can not only greatly minimize the bullwhip effect but can make the entire supply-chain agile for the demand changes. IT enabled collaboration and business intelligence capability is critical in tackling the increasing complexity and IT executives need to quickly integrate those technologies in the forecasting business process.
Popularity: 31% [?]
Related posts:
Comments (1)
Raj – Enjoy reading your blog.
I wanted to comment on two points that you mentioned:
“There needs to be a central database where different parties can easily store and view the latest sales, inventory and purchasing data. Historical data are important, too, to gauge forecast accuracy over time.”
When you study the value chain of the suppliers, company, and the company’s vendors and customers, it is possible to improve cost or productivity and forecast better. If these initiatives are solely driven by the company and the suppliers or vendors do not see any cost improvements then it can get any momentum. In a matured industry, however, I would suppose that the suppliers are closely aligned with various customers and a standardized processes and central databases or data communication can be set up.
“There are several Business Intelligence capabilities around the data that can be integrated to intelligently ‘feedforward’ relevant existing data into the next iteration of forecasting thus increasing accuracy.”
This is a very good area and I guess that is going to gain a lot of interest in the business community. The use of dashboards and communication between various parties is going to improve not just forecast but many other value-added and cost improvement factors.