This is the final installment from our thought leadership series from our Portland, OR roundtable attended by leading companies like Sharp Microelectronics of the Americas, LaCrosse Footwear, Merix Corporation, Planar Systems, and Trimble. Three topics that are critical to delivering a successful sales forecast were covered in the roundtable:
In this blog, I’m delighted to share the key learnings around driving trust in the sales forecast (no, this was not a short discussion!).
Key learning #1: Trust in God, but all others pay cash.
“Visibility increases trust in the forecast.” One thought leader had forecasted that the coming quarter would be the best quarter ever for his company. No one believed him, yet he was right and delivered 21% quarter over quarter growth in a down economy. The best part was that the rest of his competition had negative growth that quarter. As a result of this lack of trust, he looked at the sales forecast process across the company. His key learning? The key to increasing trust across the company was getting visibility into each group’s assumptions (what were they thinking?) and making sure the hand offs between groups were well understood. It might be great that the Sales team is forecasting a big jump in sales for that product, but did they know Marketing just killed that promotion Sales assumed was still running?
Having a complete, visible sales forecast across Sales, Product, Marketing, Finance and Operations builds trust in what the sales forecast contains. Improving the process helps companies to more quickly understand what the forecast is telling them, and then take action. As another thought leader said, “When they’re arguing adamantly or are totally quiet, I don’t trust the forecast. I trust it more when there’s dialogue.”
Key learning #2: It’s gut check time.
While forecasting is a process, it’s in large part about human behavior. What’s the human behavior driving the output? Is it emotion driven or logic driven? Interestingly, our thought leaders gave great weight to the emotional and intuitive element as they’ve seen it be as effective as a logical, mathematically derived forecast. “Some sales people have an inherent knack to know if a customer is going to buy something or not. Some of the best forecasters are in better touch with their customers’ emotions, not the logical attribute checklist.” Another chimed in that academics were picking up on this—rules of thumb most of the time came within a small percentage of, or beat, heavy-duty statistical analysis.
A company’s ability to incorporate gut and science is like a pilot transitioning from visual to instrument flying. They must believe the instruments, but initially they’ll fixate on one instrument rather than instrument scan. After a while, they learn to look at the whole instrument panel, and their eye will go to what’s wrong. Forecasting is the same, judgment includes both logic and emotions (do I feel right about this?) and is honed over time and experience.
Key learning #3: Accuracy or performance management?
Trust can be evaluated in two different areas of the sales forecast – how much do you trust the individual forecaster and how much do you trust the overall sales forecast? A lot of the trust in the individual resides in knowing what their biases are and their performance over time. It’s not so much getting people to be the most accurate, it’s knowing how to adjust for their biases. Don’t get me wrong, accuracy and “truthiness” are important! Whether it’s a sales rep, or a customer giving a forecast, you need to measure accuracy to begin building trust. But, managing to performance incorporates managing over the “long trend line”, knowing what has changed, and why. Then the various stakeholders in the company can react appropriately. It’s not so much knowing that the forecast is wrong, it’s knowing which parts of the forecast are wrong. Ultimately, the forecast is a human generated number; being able to use analytics to understand how good the humans are, and what parts of the forecast are good builds confidence in the sales forecast.
The bottom line is you want to get to a point where the company trusts its sales forecast and the sales people can trust they will get what they forecast. That means revenue.
your snapshots to compare your forecast at points in time — for example, how has the 2010 forecast changed from the beginning of the year to today? In this example, we’re looking at the variance by region.
your forecast to targets or goals so that you can keep track of how you’re doing against your objectives. In this example, we can see how each sales person is delivering against their targets.
your forecast to actuals or shipments to monitor attainment during the quarter. In this example, we can see attainment by customer.
The IBF Demand Planning & Forecasting