Barriers to Sales Team Accuracy

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According to recent research, omnichannel shopping engagements will continue to dominate the retail space (with the supporting platform market expected to have a 21.48% CAGR between 2017-2023).  The increasing complexity of customer touchpoints calls leaders to architect a seamless brand experience across both digital and physical channels; including direct e-commerce, brick and mortar, as well as worldwide networks of distributors and retailers.

Seamlessness

For some brands, this means investing heavily in direct to consumer sales for the first time, like Nike and Adidas did a few years ago.  Other brands, who began in brick-and-mortar, are turning on e-commerce, Buy Online Pickup in Store (BOPIS), and Ship from Store (SFS) options to serve a more digitally-focused customer base.  And finally, even brands native to e-tail are re-defining customer experiences at physical stores, like M.Gemi’s fit shops, where customers can find the perfect size before ordering items for delivery. Whatever the case, integrating customer data across e-commerce and in-store technologies is the main challenge for brands expanding their omnichannel sales in the coming years.

Forecast Management

Additionally, brands may see an increasingly limited ability to collaborate and validate sales forecast data, which is a key input to operational planning.  Why is this happening?

For starters, sales forecasts are notoriously inaccurate, because salespeople are not forecasters. Sales typically employ judgment-based forecasting, which calls on intuition and experience, but is not suited for discerning trends and patterns in large data sets.

Moreover, coordinating and managing a multitude of bias-prone judgment forecasts in spreadsheets can be cumbersome and take weeks or months to finalize.  Contributors across the globe may be working in silos, speaking various languages, and using different processes. Coming to a consensus on the value of projected sales may seem near impossible without the support of advanced technology designed to capture and combine crucial Sales team insight with statistical baseline forecasts generated from historical sales data.

Vanguard’s Solution

Fortunately, we’ve seen even footwear giants are using technology built exactly for this purpose – getting the forecast right despite all odds. One brand came to Vanguard Software requiring a solution that would support the input of critical insights from the Sales teams about changes in the market like new customers, retailers, channels, trends, and products. The company needed a planning system that was flexible, unified, and supported a global rollout. Vanguard delivered.

Global Footwear Company

CASE STUDY

About Vanguard Software

Vanguard Software introduced its first product for decision support analysis in 1995. Today, companies across every major industry and more than 60 countries rely on the Vanguard Predictive Planning platform. Vanguard Software is based in Cary, North Carolina.

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