Author Archives: Shelley Symonds

Customer Thought Leadership: Driving Trust in the Sales Forecast

Wednesday, May 26th, 2010

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.

Customer Thought Leadership: Sales and Marketing Collaboration

Friday, May 14th, 2010

This is the second installment in our thought leadership series from our Portland roundtable. We will cover three topics:

Sales and marketing collaboration proved to be a lively topic. Not surprisingly, the cats and dogs don’t get along much of the time. However, an actionable sales forecast can foster productive discussions that lead to better collaboration not just between sales and marketing, but between sales and other areas like operations. Our key learnings follow:

Key learning #1: Each area of the company has a different view and something to add to the party.

Our thought leaders had many different processes for getting from sales forecast to fulfillment. One company’s process was that sales generated the forecast, marketing vetted it and gave it to operations who built exactly to their forecast. Another’s was that the factory built to maximize their profit margin and then sent it to sales and marketing to sell, sell, sell, regardless of whether their customers wanted it or not. Either extreme doesn’t do a good job of linking feedback to the forecast. In the former, inventory is not optimized. In the latter example, the company could be doing 10-20% more revenue per year if marketing and sales had the  product they wanted, not just what the factory built. Both of these companies put sales forecasting systems in place to bring the various views together, as the forecast application can capture the different views of sales, marketing and operations into a common system of record, while tracking changes. This lets the organizations focus collaboration on what the data is telling them, not on whether or not the data is good. This is a much more productive discussion for these companies – focus on optimizing the unconstrained customer demand forecast with what the company can deliver.

Key learning #2: Responsibility and compensation drive behavior.

Regardless of the process, compensation drives behavior. When marketing runs the forecast, they can impact sales compensation by constraining product to make their inventory bonus, while sales doesn’t have the right products to sell. When the factory runs the process, their comp is to optimize inventory, not revenue which impacts both marketing and sales compensation. When sales runs the process, they can affect operations compensation (e.g. sales may have visibility to margin, but if they’re not comped on it like operations, they won’t optimize their forecast for margin in addition to revenue). Putting in the right compensation drivers is difficult for most companies. Many focus on one end or the other of the sales forecast to fulfillment process. As one thought leader asked another, “Your marketing forecast affects the sales team’s comp when the units are wrong. How does sales like you then?” The reply? “More when inventory is available.” All of the companies recognized that aligning compensation across all the functions is an area of opportunity to drive better behavior for their company.

Key learning #3: New product introductions are the most fun.

New product introductions (NPI) are the riskiest part of any forecast. Run rate or recurring business is much easier to forecast, and is more predictable.  But creating a forecast for an NPI is a work of art, not science. One thought leader’s company has the product team focus on the idea of what the product will look like in the context of macro level items, like input from big customers, consumer data, and competitive products. Sales, of course, has a different view. Their forecast for NPI starts with sales, then goes to marketing, and then to sourcing. This insures that input from sales on new items is definitely seen by marketing, and seen earlier. It is better to have sales call the baby ugly, and let marketing know. And many times, sales was right.

The best analogy of this session — one of our thought leaders likened a new product introduction to flying an F18 by the wire. For those of us who don’t know, when an F18 takes off from an aircraft carrier the pilot is not actually flying the plane. Pilots make too many changes to the stick and the on-board computers can’t keep up. The computer takes care of the plane’s takeoff, then the pilot takes over once airborne. For a NPI, marketing should launch the product, and then sales can fly it. Of course, operations had to build the plane first!

Customer Thought Leadership: Sales Forecast Adoption

Thursday, March 18th, 2010

Recently, Right90 hosted a thought leader roundtable in Portland, OR 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 :

  • Maximizing sales adoption
  • Sales and marketing collaboration
  • Driving trust in the sales forecast.

I’ll be covering each topic in separate blogs – there were so many great insights that were shared amongst the attendees.

First, maximizing sales adoption. This discussion focused around one of those deceptively simple and critically underestimated phases in the rollout of any new process and application. Rolling out any new application for sales people is especially challenging, but sales adoption can be greatly improved with these key learnings.

Key learning #1: Sales forecasting is fundamental to improving revenue and maximizing sales.

Make the sales forecast not only easy to create but also easy to consume. This will drive a more effective dialog between sales, products/marketing, and operations. This dialogue becomes a discussion about how the data can be leveraged by these groups to drive the various aspects of the business rather than a dialogue focused on who has the right data. Adoption of the forecast across the company is just as important as within sales. Nothing fosters adoption faster than seeing the results of your efforts delivering value back to you.

Key learning #2:  User adoption revolves around people’s motivations.

Many companies view the forecast as an incredible time sink that takes the sales team away from selling and is widely ignored by the rest of the organization. A highly motivating situation. How can you combat that?

First, motivate your sales people by showing them it’s easier than what they were doing before (remove the pain). You may not want to go cold turkey on them and pull their familiar forecast spreadsheet, but one of the thought leaders did. They found that when their sales team actually tried the new way, they realized the new application was much better. Why? Because it allowed them to forecast faster, and then provided them with improved visibility “around the curves”. The forecast became the tool that prevented them from slamming into walls at the end of the quarter. Less hassle, better insights will always motivate people.

Key learning #3: Show them you care.

We heard stories of sales people randomly changing their Excel-based forecast just to see if anyone was watching. Sadly, at many companies, no one is. But, if you give feedback on the forecast consistently and directly to the sales team, they will adopt the behavior you want. One of our VPs of Sales occasionally sends out emails to the sales reps making changes in their forecast asking questions about their updates. Combine this level of executive attention with an easy to use application for forecasting, and the sales team pays attention.

Key learning #4: A little competition goes a long way.

Carrot or stick? With sales people, competition and a carrot can really move the needle. For example, set up a competition between the forecast sales produces vs. marketing’s. Or, between sales teams in different regions or countries. For extra credit, set up a competition between operations and sales. Winning any of these competitions really means the company wins by getting an actionable forecast.

Next, key learnings around sales and marketing collaboration.

Commenting Policy

Wednesday, February 17th, 2010

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Super Sexy Enterprise Apps

Monday, January 18th, 2010

Well, I’m blushing.

In my 20 years in the high tech world, I’ve never heard an enterprise application described as “super sexy.”

For this, I have to thank James Ward, a Technical Evangelist at Adobe who saw Right90 Trust Analytics™ app at Dreamforce and thought it was one of the best, see his Adobe Flex blog for the recording of the app here. James, thanks for bragging rights I never thought I’d be able to claim!

Once I got beyond the fun of it all, I thought about how the adoption of enterprise applications is greatly influenced by the user experience. Over and over, the biggest inhibitor to the success of a enterprise application deployment has been user adoption. Think of the phrase “shelf-ware” that described business’ purchase of enterprise apps that just sat on the shelf and were never deployed.

If users don’t adopt the application, no data gets entered, no analysis can take place, and no insights that can benefit the business are derived. It’s a simple hierarchy that drives a business’ success. CEOs can mandate the use of an application, but that use will still be spotty unless the users like the application and get more benefit from using it than not.

When I reflect on who our audience is for our applications, I’m very proud to have our app called “super sexy”. The users of our applications—sales reps and sales management primarily—are some of the toughest folks to please. (We all know they love their CRM systems and log in every morning like they do with their email.) If we can increase user adoption by providing them with an application that is a pleasure to use and delivers great value through the insights that are presented, I know that our customers will be successful. Sales forecasting has been a tough problem to solve for large companies, and I hope that applications like ours will inspire them to move out of the “do nothing abyss” and move forward to finally fix the chronic sales forecasting problem.

My thanks to James Ward for giving us some extra exposure; my thanks to our CTO, Dean Skelton, who is the brains behind this application; and finally to Elaine Cleary, our Customer Success Manager who so ably and beautifully demo’d our new application.  In addition to our applications, Elaine is one of the reasons that our customers have achieved success, she helps to guide their use and adoption of our applications. She also provides a weekly spotlight blog that can be accessed here.