Category Archives: Pipeline

So, you’re missing plan and revenue growth is down.  Well, welcome to the club.  You’re certainly not alone in these times. 

In this post, I’ll discuss what you can do about it – specifically, how you can apply some of the ideas I’ve discussed in Kellblog to troubleshoot go-to-market (GTM) performance.  I’ll focus on troubleshooting new business (“newbiz”) ARR plan attainment, the area where most companies seem to be having the most trouble [1].

Don’t Knee-Jerk Blame the Plan

The immediate temptation when missing plan is to blame the plan.  “It’s not realistic.”  “It was driven by the fundraise, not the bottom-up.”  But blaming plan is a poor place to start for two reasons.                        

First, you signed up for the plan when you submitted it to the board for approval.  Next time, if you don’t believe in a proposed plan, don’t be so quick to fold in the face of internal pressure.  Remember the old Fram oil filter commercial and think, “you can fire me now or fire me later” so if you’re asking me to sign up for a plan that I don’t think I can achieve, you might as well fire me now [2].  The need to make such difficult judgments is the price of admission to the sales leadership role.  Cop out at your own peril, because they will indeed fire you later.

Second, when you follow the approach in this post, if the plan is unachievable it will emerge from the data.  So, bite your tongue, avoid any initial temptation to blame plan, and instead go look at the funnel.

The Two Questions and Two Metrics

Recall in this post, I argued that you should ask two questions when you’re missing plan.   Every quarter: 

1. Are we giving sales the chance to hit the number?
2. Is sales converting enough of the pipeline to hit the number?

That’s it.  Everything comes down to these two questions.  No matter the root problem, it will be revealed in answering them.  Remember, the way to make plan for twelve consecutive quarters is one at a time.  So why not focus on next quarter?  And if you’re chronically missing plan, why not make a steady-state assumption to simplify things further? [3]

Starting with the above two questions makes things simple by breaking the entire funnel in two.  Simplifying the problem is important because you can quickly and irrecoverably descend into analytical quicksand.  When I first meet them, many companies are neck-deep in such quicksand, comparing dashboard clips, reports, and spreadsheets derived from different systems, lost in an endless sea of non-footing detail, having completely lost the business forest for the salesops trees.

Note that neither of the two above questions assigns blame.  As a consultant, I have the distinct advantage of not caring where the trouble is, making me a disinterested party, de facto impartial.  I encourage CXOs to adopt a similar approach, simply stating facts, avoiding blame (e.g., inferred causes), and acting as dispassionate analysts when analyzing GTM problems.  While you will eventually need to ask why you have certain problems, it’s always best to start with simple statements of fact, get agreement on them, and build from there.  For example:

• “We consistently start quarters with insufficient pipeline coverage” is a blameless statement of fact.  It does not say whose job it is to generate pipeline (if that’s even been detailed out across sources) or why they are failing to do so.
•  “We are converting a below-normal percentage of our week 3 pipeline,” less obviously, is also a blameless statement of fact.  While it’s clearly the job of sales to convert pipeline, the statement makes no assertion as to why we are seeing abnormally low conversion rates (e.g., pipeline quality, change in competitive market, sales execution).

When it comes to metrics, the first of the above questions is measured by pipeline coverage, more precisely week-3 pipeline coverage [4] [5]. The second is measured by a conversion rate, specifically week-3 pipeline conversion rate.  Notably, this is not a win rate, and please read this post to ensure that you understand why.

Are We Giving Sales a Chance to Hit the Number?

Make a chart like this one to answer this question.

Here you see, for newbiz ARR for the trailing nine quarters, week 3 pipeline dollars, week 3 pipeline coverage (pipeline/plan), ARR booked, week-3 pipeline conversion, and the pipeline coverage target implied by the week-3 conversion rate (i.e., its inverse).  Pipeline conversion rates are more interesting when viewed in conjunction with plan attainment, so I’ve added ARR plan and plan attainment as well. 

Analyzing this chart, we can see a few things:

• From 1Q22 through 1Q23 we converted about 33% of the pipeline
• We were also consistently hitting plan in that timeframe
• Starting 2Q23 we started with only 2.3x coverage, converted a healthy 40% of it, but still came up short, at 91% of plan. 
• That rough pattern continued in 3Q23 and 4Q23
• 1Q24 started with the weakest coverage in the past nine quarters (1.9x)
• While sales is forecasting record conversion of that pipeline (45%), we are nevertheless forecasting to land at only 86% of plan
• I’m not sure I believe the forecast because 45% conversion is borderline unrealistic and could simply be the CRO trying their best to hold the line

I conclude that this company is starting with insufficient pipeline.  That is, they’re not giving sales a chance to hit the number.  How do I conclude that?

• By comparison to pipeline coverage benchmarks.  3.0x is the typical pipeline coverage goal and you’ll note that in the good times (1Q22 through 1Q23) we consistently started with 3.0x+ and we consistently made plan. 
• By comparison to pipeline conversion benchmarks.  33% is a standard conversion rate.  Here we are running at 40%+, which is best-in-class conversion.  Pipeline conversion is not the problem.
• More importantly, by comparison to ourselves.  In our recent history, we consistently made plan when we started with 3.0x+ coverage and missed it when we started with 2.3 to 2.4x.  This quarter (1Q23) we’re starting with 1.9x, forecasting record conversion, and still only 86% of plan.

The solution to the insufficient pipeline problem is, unsurprisingly, to make a plan to generate more pipeline.

Here are some of the high-level steps in making that plan:

• Define pipeline generation targets across the four major pipeline sources.  It’s surprising how many companies don’t start with this basic step.  For bonus points, over-allocate the goals to target 110% of what you need. [6]
• I prefer to set these targets by opportunity count, not pipeline dollars, because I think it’s more visceral and less easily gamed [7].
• Do a cost/oppty analysis across your pipeline sources to get an idea of how much money any given pipeline source (e.g., alliances, demandgen) would need to create, for example, 20 more oppties next quarter.  Remember to focus on variable, not average, cost [8].
• Be sure to check with the leader of each pipeline source on their ability to absorb extra money to generate more pipeline.  If you have 12 SDRs reporting to one manager, they may need to bring in another manager before hiring 3 more SDRs.  Alternatively, sellers may have extra time on their hands and the ability to put more time into outbound.  Alliances may have a hot candidate they want to hire, but no open headcount, and could execute quickly if one were opened.  It’s not just about money; it’s about the ability to productively spend it.
• Accept that you may be overallocated to sales versus pipeline generation.  In this case, the best solution might well be to terminate the bottom N sellers and convert the newly liberated budget to pipeline generation — so that everyone else has a chance at success.  This is painful, but sometimes necessary, and after you’ve had to do it once, you’ll be more careful to plan holistically in the future.

This all goes without saying that no pipeline analytics will work if you lack basic pipeline discipline – i.e., if you don’t have clear definitions for stages, close dates, oppty values, and forecast categories, and if you don’t regularly enforce them via periodic pipeline scrubs.

The Floating Bar Problem

Before diving into pipeline conversion, let’s address a special case of insufficient pipeline:  one where the pipeline initially looks sufficient but burns off at an above-average rate across the quarter.  You can see this by looking weekly at to-go pipeline coverage.

What’s usually happening in these cases is that some material percentage of your week-3 pipeline is effectively fake.  This happens because, when pipeline is scarce and if sellers are under pressure to each carry 3x coverage [9], they will take lower-quality opportunities into their pipeline.  For example, long-shot oppties that appear rigged for the competition, immature oppties where sellers hope to create a buying timeline, or self-nurture leads that may only become real oppies in the future.

I call the tendency to work on lower quality oppties in tough times, the “floating bar problem” because sales silently lowers (or in good times, raises) the bar for admission into the pipeline.  This is insidious because the result is fake pipeline that creates an illusion of coverage which disappears as the quarter progresses.

The solution to his problem is simple in theory, but hard in practice.

• Sales management needs to hold the line on what gets into the pipeline, applying the same standards in tough times as good ones.
• If sales management wants to allow sellers to work on low probability “oppties,” that’s fine but, well, get them out of the opportunity management system.  Use tasks to track work.  But only promote a lead to an oppty when it meets the standard for being an oppty.

If, for example, SDRs are passing low quality stage-1 oppties to sales that should not show up in the numbers as a reduced pipeline conversion rate.  Instead, it should show up in a higher stage-2 rejection rate.  This point is completely lost on most sales managers so please make sure you understand it.  If you maintain pipeline discipline, lower quality oppties should show up not as a reduced stage-2 to close rate, but as an increased stage-2 rejection rate.  And pipeline discipline starts at stage 2 – where sales decides to accept or reject oppties.  It’s wrong to accept sub-standard oppties, pollute the oppty management system with fake pipeline, convert little of it, miss plan, and wreck the company’s pipeline analytics in the process.

I’m not trying to prevent sales from working on whatever sales management wants them to work on.  But I am saying one thing:  whatever they are, don’t call them oppties in “my” oppty management system if they don’t meet the defined standards for oppties [10].

Is Sales Converting Enough of the Pipeline?

While it’s the job of sales to convert pipeline into ARR, that doesn’t mean sales execution is the only factor that drives conversion rates.

Here you see conversion rates plummeting, dropping by 11 percentage points between 1Q23 and 2Q23 and then by another 5 percentage points by 4Q23.  By the 1Q24 forecast, the pipeline conversion rate has been effectively cut in half from ~32% to ~16%.  Note that during the recent dark times (from 2Q23 to 1Q24) we have been starting with ~3.0x pipeline coverage, but converting so little that we’re landing in the dismal range of 47% to 65% of plan.

Let’s assume we have the operational basics covered, so this is real pipeline, validated and scrubbed by sales management, and held to consistent standards over time.  But we’re converting a lot less of it than we used to.  Thus, I conclude that the company’s problem is pipeline conversion, not pipeline coverage.

What possible factors could be driving reduce pipeline conversion rates?  Well, there are a lot of them, so we’ll talk about each.

• Changes in averages (i.e., ceteris non paribus).  Most productivity models assume a constant average sales price (ASP) and average sales cycle length (ASC).  If ASPs go down, you will hit your count-based targets, but miss your dollar-based ones.  If ASCs increase you may preserve your eventual close rates, but stretch them out over time, reducing quarterly conversion rates and plan attainment. 
• ASP decreases.  Typically, due to budgetary pressure and increased price competition, but also can be due to an overreliance on discounting.  Some of this is inevitable in a downturn.  You can mitigate it through pricing and packaging changes (e.g., new add-ons to preserve price and/or offset churn at renewal).
• Slip rate increases.  When ASCs lengthen, more deals slip to the following quarter(s).  Pipeline scrubs can provide early detection and deals reviews can offer re-acceleration strategies.  The biggest risk is that these deals never close at all and simply hit no-decision or derail.
• Win rate decreases.  Win rates usually decrease when a new competitor enters the market or when an existing competitor leapfrogs your product or your market position (e.g., passes you in market share).  Competitive research, sales training, and selling the roadmap are the usual responses.  
• An absence of big deals.  Some CROs run their business as a mix of baseline deals to hit say 60-80% of plan, topped up by big deals that provide the rest.  During a downturn those big deals may evaporate leaving only the run-rate business.  The usual response is a strategic accounts program to focus on generating big deals and a focus on pipeline generation in the run-rate business to cover the gap.
• Pipeline substitution.  This is a subtle problem due to a change in pipeline mix, with low-converting pipeline substituting for high-converting pipeline.  This is dangerous because you “look covered” at the start of the quarter but end up below plan at the end.  Let’s drill in a bit here.

Pipeline Substitution

Not all pipeline is created equal.  Pipeline for certain products often converts at a higher rate than others.  Pipeline conversion rates typically vary by source, e.g., with outbound SDRs typically converting at a low rate and alliances converting at a high rate.  Pipeline conversion might also vary by geography, with established geographies delivering high conversion rates than emerging ones. 

See this chart for an example:

In this example, we start every quarter with $10M in pipeline.  In 1Q23 through 3Q23 we convert 25% of it, but in 4Q23 we convert only 20%.  What happened?  The pipeline mix changed.  Starting in 4Q23, we substituted $2M in high-converting pipeline (from sales/outbound and alliances) with $2M in low-converting pipeline (from SDR/outbound).  Blended pipeline conversion thus dropped from 25% to 20% as a result of this change, effectively substituting nutrient-rich pipeline for nutrient-poor pipeline while keeping the overall amount the same. 

Identifying these problems is a lot of work because you’ll need to segment pipeline by multiple variables — such as pipeline source, product, geography, business segment (e.g., enterprise vs. corporate accounts) – to get historical average conversion rates and percent mix, and then see if changes in pipeline composition are driving reductions in conversion rates.  If so, the usual solution is to re-aim your pipeline generation back to the high-converting segments.

In this post, we have shown how you can troubleshoot go-to-market problems by splitting the funnel in two and focusing on two questions:

• Are we giving sales the change to hit the number each quarter, as measured by pipeline coverage.
• Is sales converting enough of the pipeline to hit the number, as measured by pipeline conversion.

I’ve also provided numerous notes and links that you can use to deepen your knowledge of how to solve these problems.

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Notes

[1] The same analysis approach can easily apply to expansion ARR, which should be analyzed independently via its own funnel because it typically has different conversion rates and shorter sales cycles. 

[2] Deadheads will understand that I had to resist writing, “nothing else shaking, so you might just as well.”

[3] Think:  given that we’re off rails, forget the plan for a minute and let’s analyze what do we need to do to add $4M in newbiz ARR every quarter?  This liberates you from needless, complexifying math that makes it harder to see the answer and is a great way to start in the crawl-walk-run exercise of getting back on track.

[4] More precisely, day-1, week-3, current-quarter pipeline coverage.  Snapshotting Sunday night before the start of week 3 gives you a consistent point to compare across quarters.  Waiting until the start of week 3 gives sales (more than) enough time to clean up the pipeline after the end of the prior quarter but is still early enough to be considered “starting pipeline.”  Note that you may need to apply corrections for any deals that close in the first two weeks of the quarter.  A high-class problem, at least.

[5] Or, in a monthly cadence, day-3 pipeline coverage.  See my post on the mental mapping from quarterly to monthly cadence for more on this concept.

[6] There is a cost to this type of insurance; it’s not great for your CAC ratio if you don’t end up over-performing plan (which ceteris paribus, starting with 110% of your pipeline target, you should).  But it does reduce the risk of missing plan.  To me, the correct sequence is to focus on making plan first, before focusing on efficiency — but you need to have the cash to underwrite that philosophy.

[7] For example, one big deal that masks what’s otherwise a pipeline starvation situation.  If you’re going to set targets on dollars (which typically involves using some placeholder value) then you should create the oppties with a close date far in the future (e.g., one year) that sales can pull forward once they further qualify the account.  The alternative is usually generating lots of fake pipeline that is auto-dumped into next quarter that gets pushed out in the first weeks of the quarter.  Also, see this for more on ensuring pipeline coverage by seller, and not just in aggregate.

[8] You’re not going to hire an extra CMO, an extra PR agency, and an extra product marketer to generate 20 more oppties.  Those costs are effectively fixed.

[9] And putting them under such pressure can run in diametric opposition to pipeline discipline and enforcing pipeline standards by encouraging reps to enter dubious deals as pipeline to get their manager off their backs.

[10] I say “my” oppty management system to remind people that carrying sub-standard oppties has impacts well beyond themselves and that oppty management system is the company’s property, not theirs.  For old movie fans, when speaking of the oppties in “my” oppty management system, I’m always reminded of Cool Hand Luke: “what’s your dirt doing in Boss Keen’s ditch?”