Pipeline Radar™

B-to-B pipelines are like living organisms, constantly evolving and changing. As such, they are the best leading indicators of the long-term health of the marketplace and the business, as well as the effectiveness of sales personnel and marketing programs. This is why it’s important to look for pipeline behavior patterns that foreshadow significant changes in the marketplace or provide early indications of potential strategy, execution, or employee performance problems. By more systematically tracking and graphing pipeline behavior metrics for both the sales view (salesperson, geographic organization, channel organization) and the marketing view (product, program), it simplifies things for both employees and managers. This simplification enables them to ask better questions sooner about trends and behaviors that would normally go unnoticed, and to take early action to avoid serious problems.

Unfortunately, B-to-B pipelines are made up of opinions and conjecture as well as facts. They often contain significant erroneous and misleading information, which often creates what I call “artificial pipeline inflation and deflation”. Some of this artificiality is a natural occurrence driven by a combination of the varying (conservative vs. optimistic) personalities of the salespeople and their managers, plus their natural aversion to sharing information and being managed.

In good economic times, pipelines and forecasts tend to be on the conservative side, but in a challenging business climate they tend to be overly optimistic. In today’s economy, artificial pipeline and forecast inflation has become a serious problem for many companies, especially those with complex sales cycles. Joe Galvin, Vice President of Gartner Group’s CRM practice, puts this succinctly when he says, “There’s a significant amount of fear in salespeople and sales management right now, and this fear causes a lot of them to conclude that the longer they delay bad news, the better. First of all, they don’t want to get beaten up twice, once for a low forecast and again for missing their numbers. Second, because of their nature, they always hope that some miracle will save them.

Pipeline Radar™ is a new way of looking at the two primary aspects of pipeline behavior that should be measured over time.

• External behavior, which includes the attributes of size and shape.
• Internal behavior, which includes the attributes of flow, leakage, and turbulence.

Below are a couple of simple examples of Pipeline Radar reports that can be easily be generated in Microsoft Excel™ from the data that’s already captured in a basic opportunity management system. Over the next several years, I expect most CRM vendors will incorporate richer templates and process assists into their products for more advanced forms of Pipeline Radar so that this type of reporting can be more tightly integrated into the opportunity management process.

The most basic pipeline attribute is overall size, including any confidence factor that has been applied to it. Both aspects of every marketing and sales pipeline should be tracked on a regular basis from both a revenue and number of opportunities standpoint. As the chart below shows, comparing pipelines to a standard benchmark, perhaps a corporate average, can be a powerful way to stimulate substantive discussions with both the sales and marketing professionals.

Tracking how the shape of a pipeline changes over time, both in terms of how much revenue and how many opportunities are at each stage of the funnel is not as common as tracking overall size. However, tracking the shape of a pipeline (below) can tell a lot about a salesperson’s or sales and marketing organization’s ability to generate new interest or cultivate needs in their opportunities. It also reveals where to spend additional time and effort. It’s critical, however, to remember that different salespeople work differently, so it is the change in the shape of a pipeline over time that is often more important than the actual shape itself.

Very few companies attempt to track the flow of opportunities on a regular basis, but it’s extremely simple to do and can provide enormous insights for management, marketing, and sales professionals. Tracking flow involves measuring what new opportunities came into the funnel, what opportunities leaked out the side of the funnel, what opportunities carried forward to subsequent months, which of those opportunities progressed to a new stage, and which opportunities actually closed. As shown in the three charts below, pipeline flow can be measured both in the aggregate with a mathematically calculated “flow factor”, or it can be graphed to show how the flow is actually happening and how the pipeline is changing behavior depending on the stage of the funnel.

The final pipeline behavior attribute that’s worth measuring and tracking is pipeline turbulence. Pipeline turbulence occurs when an existing opportunity changes somehow as it progresses through the different stages of the sales funnel. The changes in an opportunity involve the size and expected close date, and they can be either negative or positive. Negative turbulence is when deals get smaller (either in actual size or confidence factor) or are delayed, and positive turbulence is when they get larger or are expected to close sooner. It’s important to measure turbulence for a lot of reasons, not the least of which is that salespeople who are in trouble often use positive turbulence as a way to artificially inflate their pipeline and obfuscate the issues to avoid or delay a negative performance review. As the following two charts show, just like flow, turbulence can be measured in the aggregate through a mathematically calculated turbulence factor, or it can be analyzed in terms of the type of turbulence the pipeline is experiencing.

The good news about actively measuring pipeline behavior is that it requires no additional input from salespeople. The data is almost always readily available from a standard opportunity management system. For example, capturing just four fields of information on a regular basis, and running an automatic comparison routine to calculate and capture the changes in pipeline structure from month to month, generated all of the examples shown. Those four fields are:

1. The current date.
2. The size of the opportunity (factored and not).
3. The current stage of the funnel or sales process.
4. The expected close date.

By taking a snapshot of these four data points on a regular basis and calculating certain changes in key behavior metrics, you will produce a valuable time-series database that makes it simple to measure and track the external and internal behavior, including flow and turbulence, from month to month.