One topic we frequently discuss with management teams revolves around how to improve sales forecasting to build higher confidence levels into top line budgets. For companies that have never had a seasoned sales leader at the helm, this can come across as a challenging endeavor. As a result, companies may become complacent with mediocre sales forecasting tactics and methodologies which in turn can impair a business’ long-term viability. In the world of SaaS, the impact of missing a forecast is magnified because of the recurring revenue business model. A simple example to illustrate this point: if a sales team falls short of its bookings target by $100K, and assuming a 10% average annual customer churn rate (which implies a customer lifetime of 10 years), the company is missing out on $1 million of potential future revenues! Yet somehow these serious implications from failing to hit plan tend to get overlooked.
In light of the importance of accurate sales forecasting, companies should get in the habit of orienting themselves around leading indicators as opposed to lagging indicators. As the name suggests, leading indicators are metrics or KPIs that provide a sales team with an informed view of where total bookings or sales will come in at the end of a forecast period (here we will assume the forecast period is a calendar quarter). On the other hand, lagging indicators are backwards looking in nature and measure historical performance once the quarter has already concluded.
Many early stage companies mistakenly over-index on lagging indicators at the expense of giving adequate consideration to leading indicators. The primary benefit of leading indicators is that they enable sales teams to keep their finger on the pulse and avoid any major negative surprises at the end of the quarter. The specific leading indicators that should be incorporated into a dashboard will vary from business to business, but some common ones (which all tie into sales pipeline management) include leads created, lead-to-opportunity conversion rate, introductory meetings held, demos provided, and proposals sent.
For each stage in a company’s pipeline, it is critical to understand how quickly an average lead progresses from one stage to the next (i.e., intro meeting to demo provided) all the way through close. This will vary quarter to quarter but over time the numbers should trend towards a consistent level. Therefore, it is paramount to start tracking these metrics early on. This concept of movement within a pipeline, sometimes referred to as pipeline velocity, can be used to pressure test a forecast. For example, if it takes a company 5 months on average to close a deal from the time a lead or prospect is initially created in the CRM, then opportunities in those early stages should not be factored into the forecast for the current quarter. While this basic principle may seem intuitive, it can often be inadvertently disregarded.
At the start of every quarter, we see many companies singularly focused on their pipeline coverage. They will aggregate the total unweighted pipeline and compare it to their quarterly bookings target. A coverage ratio of 4x would indicate that the total value of opportunities in the pipeline is equal to four times the bookings forecast. The general idea is that the higher the coverage, the better. However, relying on pipeline coverage in isolation can lead to inflated expectations. How can that be? Going back to the prior example of a company with a 5 month average sales cycle, if the lion’s share of opportunities are in the very early stages of the pipeline, then it is unreasonable to assume they will close within the quarter. In other words, bookings within the quarter will come only from the more qualified opportunities in the pipeline. Even for companies with a relatively short sales cycle, the same principles can be applied; namely a company with an average sales cycle of 2 months should exclude early stage leads from the current quarter’s forecast if the end of the quarter is less than 2 months away.
The chart below helps illustrate how deals may progress within a quarter:
As shown, there are three possible outcomes for leads in a pipeline at the start of a quarter. Either the leads are i) closed won within the quarter, ii) pushed into the following quarter, or iii) closed out as lost opportunities. If the figures above hold true over time, then the conclusion would be that a 5x coverage ratio is required to ensure the company is trending towards hitting its quarterly sales forecast (i.e., $4M of pipeline divided by $800K closed within the quarter on average). As a result, the company should target at least $5M of pipeline on the first day of the quarter, otherwise achieving the $1M forecast is at risk.
Tying in the earlier point around leveraging a company’s average sales cycle for more precise forecasting, the $4M total pipeline from the chart should be bifurcated into earlier stage versus later stage deals. Doing so allows for a more refined coverage ratio to be calculated by filtering out the earlier stage deals that will require more time to close. This additional fine tuning will decrease the required coverage ratio but set a higher bar in terms of what can be included in the numerator of the calculation. Looking at pipeline coverage through this alternate lens should improve overall forecasting accuracy because it eliminates noise from the less qualified opportunities that have yet to be fully vetted by the sales team.
One additional point that cannot be stressed enough is the importance of discipline when forecasts are missed as a direct result of deals dragging out (i.e., the $2M light blue bar in the chart). If not careful, companies can get caught up in the bad habit of downplaying the miss. They tend to rationalize the situation with some argument to the effect of: “The sales miss is ok because the opportunities that would have pushed us past our bookings target remain in play and simply rolled over into the current quarter.” Beyond the obvious implications around managing cash flow, arguably the bigger issue is that sales teams are a finite resource. Deals that failed to close in the prior quarter will inevitably continue to command an account executive’s time who would otherwise be focused on closing new opportunities. This dynamic can have a cascading effect from one quarter to the next and, as a result, drive an increasingly larger total bookings shortfall as the year progresses. To circumvent this potential trap, any bookings deficit from one quarter should be added to the following quarter’s forecast. Another benefit of this approach is that it prevents sales teams from becoming complacent. Said differently, instead of relying on pushed deals from last quarter to make the current quarter’s forecast, sales teams are forced to come together and strategize how they can quickly get back on track.
In the coming years, financial planning is likely to play an even more imperative role in business operations. Overall purchasing behaviors, especially in the world of B2B SaaS, have evolved drastically post Covid and continue to shift in the current economic environment – budgets are shrinking, sales cycles are elongating, and customers are looking to consolidate vendors, just to name a couple trends. Consequently, the need for a 360-degree view into where performance is trending is more critical than ever.
Hyper vigilance around leading indicators should not be limited strictly to sales teams. The same level of forecasting rigor needs to be engrained across customer success. Why? The answer has to do with the higher costs associated with customer acquisition relative to customer retention. According to OutboundEngine, acquiring a new customer can cost five times more than retaining an existing customer. Therefore, a customer base that exhibits high turnover can be extremely detrimental to a business because new customers (which again, require a higher level of spend to win) are needed to help plug the leaky bucket.
In summary, there is no question that establishing a reliable set of leading indicators can be a difficult task. For most companies, especially those early in their evolution, this is a new muscle and one that takes time to develop. Companies are often slow to launch this effort because they operate under the false impression that a seemingly daunting number of KPIs are required to see any lift. However, tracking too many metrics all at once can actually be counterproductive and lead to a condition known as paralysis by analysis. The key is to identify a subset of metrics that provide the greatest insight into future performance. Management teams should take comfort in knowing that this process naturally requires some trial and error to get right.
At the end of the day, companies armed with a proven set of leading indicators are better equipped to make decisions in real time and ultimately drive towards more successful outcomes.
