Encoding The Sales Pattern To Master Demand Planning

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By Vuealta
Published: 01 May 2021

As every good economist knows, demand forms one half of the core business equation that all commerce (and much of life itself) revolves around as we seek to deliver supply in the right shape, form and function in every industry market.

As a discipline and practice, demand planning has a special place on the business manager’s family tree. A core element of overall demand management, demand planning is essentially a supply chain management process built around market analysis and forecasting.

An organization that delivers exceptional demand planning can manage its inventory, its supplier relationships and its own go-to-market systems for maximum revenue; equally, it can also align more resources to innovate and develop new products and services. This is because day-to-day operations are more predictable, more manageable and altogether more planned.

Management schooling, business tooling

Professor Emel Aktas is vocal on this entire topic in her role as Professor of Supply Chain Analytics at the UK’s Cranfield School of Management. Speaking as part of the Vuealta Supply Chain webinar series focused on Analytics for Supply Chain: Demand, Inventory and Performance Management, Professor Aktas reminded us that demand drives the entire supply chain from suppliers to manufacturing, marketing, inventory, distribution and service to customers.

As a key part of demand planning analysis, Professor Aktas has an acute knowledge of how uncertainty and variability affect an organization’s ability to understand demand patterns and get a complete picture of all actions happening inside a business value chain.

“Preparing for seasonal variations is a core process through which organizations can work to manage their demand planning processes, but there is also always the element of uncertainty that can make this process less accurate; unless we make that element of uncertainty also part of our modeling and planning, we will not have full demand planning control,” said Professor Aktas.

Encoding the sales pattern

As organizations work to encode the sales pattern of their products and master their demand planning regime, Professor Aktas says that it’s important to separate a) the variability that we can indeed predict, from b) the variability that we have to be prepared for. She also underlines the fact that uncertainty is harder to predict and gauge, the further into the future we look.

“Talking about averages without also talking about the standard variation of those average values is an incomplete approach. Being prepared for changes in demand enables a business to operate with much lower excess stock numbers and so be able to maximize profits. This allows a firm to build confidence intervals around the forecast variable (or variables) that it will form its management decisions upon,” said Professor Aktas.

Decompose to base: mean, trend, seasonality, randomness

On the journey to the touchless AI-driven future where demand planning itself forms part of an always-on, dynamic non-linear business control system, Professor Aktas explains that the smartest demand planning systems have the innate ability to deconstruct and decompose all influencing market factors.

“To decompose to base we need to understand the presence of mean, trend, seasonality and randomness and consider each factor’s relative impact upon our total demand planning and supply chain management actions,” said Professor Aktas.

Taking all these enabling technologies and practices into practice, organizations can start to formulate increasingly accurate and custom-tuned pricing models. Businesses will also be able to perform ‘history correction’ for trend-seasonal demand measurement. Trends and seasonality may often be thought of as interrelated, but they should be considered as two separate elements in the development and management of a progressive demand management algorithm.

As businesses use these techniques to run their demand planning they will learn to both encode and decompose more accurately and gain ever-greater granular insight into their place in the market.

In working practice, demand planning professionals examine internal and external factors including labor market & workforce issues, market trends and other external factors driven by national or international news and even the weather.

When an organization can gather information from the widest possible array of sources at the highest level of accuracy and in as close to real-time format as possible, then demand planning has the highest potential payoff for organizations in every vertical. The advent of highly-connected tightly-integrated cloud-based platforms has made this technology proposition more achievable today than at any time in the past.

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