Home > Retail forecasting and demand planning is a tough sell

Retail forecasting and demand planning is a tough sell

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IN my previous article, the first in this series on retail demand planning, I introduced the concepts of Top Down and Bottom Up forecasting and discussed reasons why the Top Down approach is currently more prevalent.

This second article outlines some of the demand planning challenges that are common across retail businesses. These challenges can be so daunting that they often halt demand planning evolution within a business, preventing the process advancement required to continually improve performance.

In designing demand planning strategies for retailers, it is important to identify and acknowledge the key challenges that demand planners face, rather than accepting them as a fait accompli - that is, unresolvable issues that must be lived with.

While perfect solutions do not always present themselves, advances in technology and planning processes are creating solutions to problems that were once considered insurmountable.

It is important to note that retail demand planning is challenging - more so than many other industries would realise. Retailer challenges stem from both the nature of their sales and the characteristics of a retail business.

Listed below are some of the key factors that commonly generate complexity in retail demand planning:

* High Stock Keeping Unit (SKU) counts often with a long "tail" of products

* Large numbers of stocking locations (ie stores and distribution centres)

* Stock presentation requirements in stores

* The impact of "out of stocks" on sales history data

* Frequent and numerous small volume transactions (ie customer sales)

* Shorter product life cycles

* Seasonal and/or erratic sales patterns

* Significant and frequent promotional activity.

These characteristics create a specific set of requirements that any retail demand planning solution must address.

These requirements include:

* A sophisticated (as opposed to complex) automated forecasting system requiring minimal user input to generate reliable forecasts

* The capacity to store, transfer and process large data volumes quickly

* The facility for significant amounts of 'market intelligence' to be input into the system (ie promotional planning, competitor activity)

* A range of forecast algorithms suited to the wide variety of demand patterns experienced in a retail business (ie seasonal, erratic, slow moving)

* An intelligent performance reporting framework

* A demand planning exception management approach that allows planners to identify and target (a) questionable forecasts and (b) focus on high value or critical lines.

It's a tough set of requirements to meet, but with technology improvements and more sophisticated supporting processes, progressive businesses are meeting these challenges successfully and markedly improving performance.

Given that this is where industry is headed, businesses that continue to treat the symptoms versus the causes are missing an opportunity to improve service levels whilst reducing cost to serve - an opportunity that could be exploited by a competitor.

Next month I will compare Top Down and Bottom Up demand planning in more detail and explain why each process has a definitive impact on service, inventory and cost performance.

I will take a deeper look into the lure of Top Down demand planning and reveal why it is not as simple as it first seems in Top Down - simplicity or just hidden complexity?

*Luke Tomkin is a Senior Manager with GRA .

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