demand forecasting

 

Demand forecasting gives businesses the ability to use historical data on markets to help plan for future trends. As more data on consumers and products becomes available, the need to use this data to anticipate demand is critical for establishing a long-term model for growth.

In a sense, demand forecasting is attempting to replicate human knowledge of consumers once found in a local store. Long ago, retailers could rely on the instinct and intuition of shopkeepers. They knew their customers by name, but more importantly, they also knew buying preferences, seasonal trends, product affinities and likely future purchases.

Demand forecasting attempts to replicate that sophistication through analytics-based evaluation of available data. By examining buying behaviour and other bits of data left behind by the consumer, a retailer can mimic that knowledge on a broader scale.

Anticipating demand for the modern buyer

Today’s consumer often journeys from the digital space to physical space and back again, moving among devices, apps and displays. The buying process might start with researching a product online, continue with comparing prices from a mobile device, and finish with an in-store purchase. Or consumers may see merchandise in a store and then search on their phones to score a last-minute deal.

In a world where you can have practically any item shipped to your door, it’s important for retailers to make a connection with the buyer. A variety of buying options is a delight to consumers—and a rich source of intelligence for retailers, if you know how to capitalise on it.

This omni-channel retail environment intensifies the need for better answers to the perennial questions of retail planning. What merchandise should be stocked, in what sizes/colours, at what quantities, in which locations? How, where and when should products be displayed, priced, promoted, ordered or shipped? How can we maximise profit without eroding the quality of the shopping experience and customer satisfaction?

Demand forecasting gives you the ability to answer these questions. But the sheer number of variables involved in the omni-channel world makes demand forecasting and merchandise planning on a global scale highly complex.

In its 2017 benchmarking study, Retail Systems Research found, naturally, that some retailers do this better than others. And the ones who consistently outperformed others shared a set of thought processes, strategies and tactics.

The winners were the ones who engaged in seven productive habits:

1. They put a high value on analytics. 77 per cent of winning retailers rated analytics as ‘very important’ to their retail success, compared with 48 per cent of average or lagging retailers. They know they can’t get by without integrating more predictive capabilities into their decision-making processes, and they understand why this is so.

2. They value more rigorous forecasting. Well over two-thirds of winning retailers (74 per cent) rated demand forecasting technologies as ‘very important’ to their success, compared with 58 per cent for the others.

3. They bring analytics into the process earlier. Successful retailers know that basing future plans on prior year or season sales will create self-fulfilling prophecies. The lost opportunities of the past will be repeated in the future. Instead, they bring insights from customer analytics into the demand forecasting process upfront, not just as a sanity check at the end of the planning process.

4. They are optimistic about information. Higher-performing retailers are twice as likely to expect big things from demand forecasting. They are also nearly twice as likely to ‘highly value’ attribute-based merchandise planning systems.

5. They are ahead of the game in implementation. Winners were twice as likely to have technologies already in place for attribute-based merchandise planning and demand forecasting to help with price, promotional or assortment planning. And they are twice as likely to have integrated their planning, allocation and replenishment systems.

6. They make smarter allocation decisions. Winners know they need to put products where they are most wanted or needed, and they trust demand forecasting to help them make the best localised store assortments and fulfilment decisions for direct-to-consumer orders.

7. They blend art and science. While information is seen as a critical asset—along with tangible assets such as stores, distribution centers and inventories—62 per cent of the winners also credit their success to ‘a healthy blend of art and science’. They value decision makers’ years of experience and understand the importance of well-tuned internal operational processes.

The Retail Systems Research report closes with a checklist of dos and don’ts related to demand forecasting, customer analytics and localised assortments for retailers who want to be (or remain) winners.

“If retailers can follow these simple steps, they’ll go a long way towards optimising their merchandising life cycle and creating a more compelling buying experience for customers,” the report states. “If they don’t, they risk being consigned to the dustbin of history.”

Daniel Teachey is the managing editor at SAS.

 

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