Tag Archives: Best Practices

Spotlight of the Week: Top 3 Ways to Use Right90 Comparative Analytics

Thursday, July 22nd, 2010

Why should you use Right90 Comparative Analytics — also known as the Analyze screen? The Analyze screen provides a rolled up view of your forecast by customer, product, region, or user in a table view.  While you have the option to drill down to see more details, you’re not bogged down with all those details. In addition to just viewing the forecast, here are three other popular ways to use Analyze:

  1. Use top-3-ways-comparative-analyticsyour 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.
  2. Compare top-3-ways-comparative-analyticsyour 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.
  3. Compare top-3-ways-comparative-analyticsyour forecast to actuals or shipments to monitor attainment during the quarter. In this example, we can see attainment by customer.

Whenever you get a view of the data that you’ll want to see on a regular basis, save time by creating a Favorite. If you don’t have targets or actuals in Right90, your Right90 Administrator can help facilitate getting that data so you can take full advantage of Right90 Comparative Analytics to help identify and manage exceptions in your business.

Spotlight of the Week: Copy/Paste Rows Special

Friday, July 2nd, 2010

Have you ever wanted to copy your run-rate forecast from the previous 6 months to the next 6 months? Or have you ever needed to copy forecast data from a similar product’s current quarter forecast to another product’s current quarter forecast? What if you’d just like to copy last quarter’s actuals data for a product to be the starting point for the next quarter’s forecast for that product?

All of these examples and many other requirements can be met with the Right90 “Copy/Paste Rows Special” functionality available on the Forecast screen. While a separate, more basic Copy/Paste row option enables you to quickly copy an entire row of data from one line item to another, “Copy/Paste Rows Special” gives you more advanced capabilities to copy and paste data selectively as well as for multiple lines of data. With this feature, you can:

  • Copy data from specific lines from one time range to another
  • Copy data from specific lines to different lines within a selected time range
  • Copy data from specific lines from one plan to another plan that’s at the same level of detail.

Here’s a simple example to help you get acquainted with this time saving feature. Let’s copy several months of forecast for 3 products to the same months for 3 different products. (more…)

Demand Planning’s Achilles’ Heel

Thursday, June 10th, 2010

The IBF Demand Planning & Forecasting conferences are always enlightening, including the latest event in San Francisco. While the demand planning vendors touted their latest statistical forecast algorithms and growing S&OP functionality, and customers shared stories about their new forecasting process, I kept seeing a soft spot in the demand planning process. This weak link was preventing many companies from achieving “best-in-class” demand planning performance.

Despite the ever-sophisticated demand planning algorithms, reporting and best practices, it struck me that customers still had a tremendous pain getting sales to provide a good forecast and demand planning system were not adequate. Here’s how some of the attendees described how they obtained the sales forecast:

“Sales always has the latest forecast insight and so we give sales a voice in our demand planning process by having them email us key account updates every month.”

“We take CRM opportunities from Sales and get a rough short-term forecast by taking the quantity times probability, as a weighted forecast. This gives my demand plan a reality check in case there’s a trend difference.”

“We initially planned to have the Sales team input a forecast in our demand planning system but reverted back to spreadsheets. At any rate, sales folks can be very accurate in their forecasting.”

I have heard comments just like these many times in my career. Because of my passion for forecasting and planning, I have worked at leading-edge companies like i2, Manugistics (both now JDA),  Steelwedge, and now Right90. My views have been informed by working with 50 or so companies across many industries. I have seen the demand planning processes that work with Sales effectively, but more often than not, they work not-so-well.   Demand planning systems from Demantra, JDA and SAP APO DP are complex and powerful but not designed for the busy sales team.

Companies have also used statistical forecasting solutions for the past 35 years (e.g. Autobox), yet those have not solved the problem either. Effective sales forecasting solutions are only now emerging.  This is an encouraging development, as IDF customers know the value of a sales forecast, and the value of including it in the demand planning process. After all, sales is closest to customer, and if their input wasn’t valuable, why would they have gone to all the trouble of manually including sales inputs from email and spreadsheets?

As a friend of mine says, “There’s a pony in there somewhere”. I’d like to explore how to get that pony out and on the racetrack. I’ll start by exploring the optimal process for connecting sales forecasting to demand planning and S&OP. As always, your thoughts are very welcome in this journey of discovery.

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.