How to Improve Performance with Better Retail Sales Forecasting
“Good forecasting requires an understanding of your customer’s behavior.” – Scott Edinger, Speaker and Executive Coach
Sales forecasting is a problem for many companies. SO Insights has been tracking measured sales forecast accuracy for many years. Its latest Sales Operations Optimization study— which compiled experiences of more than 2,000 sales organizations—found that fewer than half of forecasts performed as predicted.
Average sales forecast accuracy is now less reliable than flipping a coin. There’s little sign of improvement. Yet, executives, boards and investors cannot afford the uncertain performance that is associated with poor sales forecasting.
The problem is exacerbated by the growing number of competitors, both physical and online, that have exhibited better sales forecasting with greater predictability. With a keener grasp of the ideal customer, the retail organization could have used that knowledge to prepare to deliver on the prevised needs; and purchases that were lost might have been won.
Truth be told, sales forecasting decisions are best made based on a combination of fact and judgment. Research shows that companies with well-deﬁned dynamic sales processes outperformed their peers by 25% or more. Advanced analytics is a step in the right direction, enabling retailers to identify and evaluate previously hidden opportunities for product expansion, increasing market share and creating innovative customer experiences.
The alignment of retail operations and marketing plays a key role. Leaders who insist on evidence-backed by holistic data do far better than those relying on the old style of relying on POS sales data, store traffic reports and associate activity. While there is still value in those data sets, it is limited because it’s all based on past activity. It’s more significant to base forecasting decisions on a combination of fact and judgment. There is a need to balance dollars and cents with customer sensitivity. Start by asking these two foundational questions:
1) What is impacting the ideal customer and thus influencing their buying journey?
2) What are your chances of success with analyzing explicit “lifestyle impacts” and “emotional connections” instead of relying solely on daily or weekly sales indices?
In both, the answers ideally combine intuition supported by evidence (data).
Review your current sales forecasting guidelines. If you haven’t documented any, do so now. Incorporate both fact and judgment.
How have you been performing against forecast? Get your data analysts to understand trends going beyond year-over-year sales and indices to what is impacting sales.
If you insist on using percentages in the forecasting process, make sure they accurately reflect the historic sales indices. Most important, recognize that on a sale-by-sale, or day-by-day level, you either win the ideal customer or you don’t; focus on winning.
Want to learn more? Stay tuned for our forthcoming new eBook, Agility in Retail is Everything: 12 Action Steps to Accelerate Retail Growth.