Quota Over-assignment and Culture

Here’s a great slide from the CFO Summit at Zuora’s 2017 annual flagship Subscribed event.

underassign

Since they talk about this as under-assignment, since people aren’t great at flipping fractions in their head, and since I think of this more intuitively as over-assignment, I’m going to invert this and turn it into a pie chart.

quota over

So, here you can  see that 22% of companies have 0-11% over-assignment of quota, 44% have 11-25% over-assignment, 23% have 25-43%, 5% have 43-100% over-assignment, and 7% have more than 100% over-assignment of quota.

Since this is a pretty broad distribution — and since this has a real impact on culture, I thought examine this on two different angles:  the amount of total cushion and where that cushion lives.

The 0-11% crowd either has a very predictable business model or likes to live dangerously.  Since there’s not that much cushion to go around, it’s not that interesting to discuss who has it.  I hope these companies have adequately modeled sales turnover and its effects on quota capacity.

The 11-25% crowd strikes me as reasonable.  In my experience, most enterprise software companies run in the 20% range, so they assign 120 units of quota at the salesrep level for an operating plan that requires 100 units of sales.  Then the question is who has the cushion?  Let’s look at three companies.

cushion

In company 1, the CEO and VP of Sales are both tied to the same number (i.e., the CEO has no cushion if the VP of Sales misses) and the VP of Sales takes all of the cushion, giving the sales managers none.  In company 2, the CEO takes the entire 20% cushion for him/herself, leaving none for either the VP of Sales or the sales managers.  In company 3, the cushion is shared with the CEO and VP of Sales each taking a slice, leaving nearly half for the sales managers.

While many might be drawn to company 3, personally, I think the best answer is yet another scenario where the CEO and VP of Sales are both tied to 100, the sales managers to 110, and the aggregate salesrep quota to 120.  Unless the CEO has multiple quota-carrying direct reports, it’s hard to give the VP of Sales a higher quota than him/herself, so they should tie themselves together and share the 10% cushion from the sales managers who in turn have ~10% cushion relative to their teams.

I think this level of cushion works well if you’re building it atop a productivity model that assumes a normal degree of sales turnover (and ramp resets) and are thus using over-assignment simply to handle non-attainment, and not also sales turnover.  If you are using over-assignment to handle both, then a higher level of cushion may be needed, which is probably why 22% of companies have 25-43% over-assignment in their sales model.

The shock is the 12% that together have more than 43% over-assignment.  Let’s ponder for a minute what that might look like in an example with 60% over-assignment.

company4

So think about this for a minute.  The VP of Sales can be at 83% of quota, the sales managers on average can be at 71% of quota, and the salesreps can be at 63% of their quota — and the CEO will still be on plan.  The only people hitting their number, making their on-target earnings (OTE), and drinking champagne at the end of the quarter are the CEO and CFO.  (And they better drink it in a closet.)

That’s why I believe cushion isn’t just a math problem.  It’s a cultural issue.  Do you want a “let them eat cake” or a “we’re all in this together” culture.  The answer to that question should help determine how much cushion you have and where it lives.

Speaking of India: Five Lessons on India-Based Product Development

One of the interesting new challenges I faced when I joined Host Analytics about 5 years ago was working with an offshore development team in India.  Host was originally co-founded in both the US and India, so literally from inception we had employees in both places.  While this has proven to be a huge advantage for us in the market, I learned a few important lessons along the way that I thought I’d share in this post.

Lesson 1:  Read Speaking of India.

When I lived abroad in France for 5 years (which I’ve written a bit about, here), my team discovered a book, French or Foe, that we gave to every new expat when they arrived.  The book explained many important basics of language and culture that we referred to frequently as we tried to make sense of our day-to-day experiences.

Consequently, the first thing I did in approaching India was to search for a book to help me.  I found a great one, Speaking of India, which is all about communications (and how they go wrong) between people from US and Indian work cultures.

For example, see this excerpt which demonstrates “the Indian no” (i.e., the absence of saying yes) in action.

MARIAN: I’m fine, thanks. I was wondering, Kumar, what you would think if we decided to move up the date for the systems test?

KUMAR: Move it up?

MARIAN: Just by a week, at the most.

KUMAR: I see. Do you think it’s possible?

MARIAN: Should be. But what do you think?

KUMAR: Me? I guess you don’t see any problems?

MARIAN: Not really. My people can be ready at this end if your people can be up to speed by then.

KUMAR: I see.

Kumar is basically screaming no here while Marian might very well be hearing yes.

These kinds of misunderstandings are common and if you teach yourself listen appropriately then you can actually hear what is, or in this case, is not being said.

You’ll learn this — and much more — in the Speaking of India.  And you can learn some unique Indian-English words/expressions (e.g., a fresher) as well.

Lesson 2:  Show Up.

It’s hard to get to India.  From San Francisco, it’s 16 hours to Dubai and then 3.5 to Hyderabad (or 14 hours to Hong Kong and then 6 hours to Hyderabad). It takes me a full week to get about 3.5 days of actual work time there.  And let’s not even talk about the 12.5 to 13.5 hour time difference.

But that’s the point.  Because it’s hard, too many people don’t do it, preferring conference calls at odd hours over noisy telephone lines.  If you are serious about your India development center and the people in it, then you need your top executives to show up — at least a few times per year — to get to really know the people and the work environment.

I go three to four times per year with a agenda that typically looks like:

  • A large number of 1-1 meetings
  • Attendance at a few regular group/team meetings
  • A few special, topical meetings
  • An all-hands meeting at the end where I report back on what I’ve learned
  • A few dinner / drinks meetings along the way

Remember the old Woody Allen quote, 80% of success is showing up.  It’s a great rule to follow when thinking of your India development team.

Lesson 3:  Think of Product Management as a Giraffe.

I first came up with the giraffe analogy when I was at Business Objects in Paris.  While our development team (the body) was in France, we needed to have our eyes and ears in the US market if we wanted to be globally competitive.  Hence, product management needed to be the long neck that connected the two.

Concretely, this means you need to staff product managers in both locations, typically putting a greater number of more specialized product managers (PMs) in the USA and a lesser number of more generalized PMs in India. This means your PM investment might be higher than it would be with a co-located model, but it’s worth it.

Some people believe you should call the US-based staff product managers and the India-based staff product owners (POs), but I prefer to call them all product managers.  The reality is the job will inherently be different as a function of location — the USA PMs more customer-facing and the India PMs more engineering-facing — but in the end they are all product managers in my view.

Lesson 4:  Do Real Work.

The fact that we build our core SaaS offering in Hyderabad is a big attraction for talent.  Too many companies use India to do only lower-value work (e.g., porting, localization) which sets up a self-fulfilling prophecy of getting lower-quality talent.  We have found that when you do real work in India — core, critical stuff — that you will have a much easier time attracting talent to do it.

Lesson 5:  Do More Than Development.

Finally, we’ve increasingly been leveraging our footprint to do additional work — such as customer support, customer success, professional services, and even some marketing — which helps transform the environment from purely a “development center” to a generalized satellite office.   This is great because it provides developers and product managers with more direct access to the business — because people in other customer-facing functions are working right across the hall.   Practically, this helps with 24×7 operations (e.g., techops, customer support) as well, where we can provide customers with round-the-clock monitoring and services without having to ask too many people to work the graveyard shift.

I hope you’ve learned something from my journey.  Please feel free to share lessons from yours.

Eight Words that Can Limit Your Career: “Let Me Get Back To You On That”

As executives there are certain things we are expected to know — in our heads — about our jobs and our functions.  Sometimes I call this “the 3:00 AM test” because someone should be able to wake you up at 3:00 AM in the middle of a sound sleep and you should be able to answer questions like:

  • What’s the forecast for the current quarter? (Sales, Finance)
  • How many MQLs did we generate last week?  (Marketing)
  • How many customer bugs are outstanding?  (Engineering)
  • What’s the monthly PR retainer?  (Marketing)
  • What’s the ending cash forecast for the quarter?  (Finance)
  • How many unique visitors did we get on the website last week?  (Marketing)
  • What are the top three deals in the current quarter?  (Sales)

In another post, I playfully called these the other kind of in-memory analytics, but I was focused mostly on numbers that you should be able to recall from memory, without having to open your laptop, without having to delegate the question to your VP of Ops (e.g., salesops, marketingops), and without having to say the dreaded, cringe-worthy, and dangerous eight words:  “let me get back to you on that.”

The same logic that applies to numbers applies to other basic questions like:

  • What’s our elevator pitch against top-rival?  (Marketing)
  • What’s the structure of the sales compensation plan?  (Sales)
  • Which managers are the top 2-3 hot spots in the company?  (People)
  • What are the top three challenges in your department and what are you doing about them?  (Any)

You see, when you say the dreaded eight words here’s what everybody else in the meeting is hearing:

“I can’t answer that question because I’m not on top of the basics, and I am either not sufficiently detailed-oriented, swapped-in, or competent to know the answer.”

And, worse yet, if offered unapologetically:

“I’m not even aware that this is the kind of question that everyone would reasonably expect me to be able to answer.”

Here are three tips to help you avoid falling into the eight-words trap.

  1. Develop your sensitivity by making a note of every time you hear them, how you feel about the specific question, and how it reflected on the would-be respondent.
  2. Make a list of questions you should be able to answer on-the-spot and then be sure you can.  (If you find a gap, think about what that means about how you approach your job.)
  3. If you feel the need to say the dreaded eight words see if offering a high-confidence range of values will be enough to meet the audience’s need — e.g., “last week’s web visitors were in the 10,000 to 11,000 range, up a few percent from the week before.”

And worst case, if you need to say the dreaded eight words and you think the situation warrants one, offer an apology.  Just be mindful that you don’t find yourself apologizing too often.

Kellblog Predictions for 2018

In continuing my tradition of offering predictions every year, let’s start with a review of my hits and misses on my 2017 predictions.

  1. The United States will see a level of divisiveness and social discord not seen since the 1960s.  HIT.
  2. Social media companies finally step up and do something about fake news. MISS, but ethical issues are starting to catch up with them.
  3. Gut feel makes a comeback. HIT, while I didn’t articulate it as such, I see this as the war on facts and expertise (e.g., it’s cold today ergo global warming isn’t real despite what “experts” say).
  4. Under a volatile leader, we can expect sharp reactions and knee-jerk decisions that rattle markets, drive a high rate of staff turnover in the Executive branch, and fuel an ongoing war with the media.  HIT.
  5. With the new administration’s promises of $1T in infrastructure spending, you can expect interest rates to raise and inflation to accelerate. MISS, turns out this program was never classical government investment in infrastructure, but a massive privatization plan that never happened.
  6. Huge emphasis on security and privacy. PARTIAL HIT, security remained a hot topic and despite numerous major breaches it’s still not really hit center stage.
  7. In 2017, we will see more bots for both good uses (e.g., customer service) and bad (e.g., trolling social media).  HIT.
  8. Artificial intelligence hits the peak of inflated expectations. HIT.
  9. The IPO market comes back. MISS, though according to some it “sucked less.”
  10. Megavendors mix up EPM and ERP or BI. PARTIAL HIT.  This prediction was really about Workday and was correct to the extent that they’ve seemingly not made much progress in EPM.

Kellblog’s Predictions for 2018

1.  We will again continue to see a level of divisiveness and social discord not seen since the 1960s. We have evolved from a state of having different opinions about policies based on common facts to a dangerous state based on different facts, even on easily disprovable claims, e.g., the White House nativity scene.  The media is advancing, not reducing, this divide.

2.  The war on facts and expertise will continue to escalate. Read The Death of Expertise for more.   This will extend to a war on college. While an attempted opening salvo on graduate student tuition waivers didn’t fire, in an environment where the President’s son says, “we’ll take $200,000 of your money; in exchange we’ll train your children to hate our country,” you can expect ongoing attacks on post-secondary education.  This spells trouble for Silicon Valley, where a large number of founders and entrepreneurs are former grad students as well as immigrants (which is a whole different area of potential trouble).

3.  Leading technology and social media companies finally step up to face ethical challenges. This means paying more attention to their own culture (e.g., sexual harassment, brogrammers).  This means taking responsibility for policing trolls, spreading fake news, building addictive content, and enabling foreign intelligence operations.  Thus far, they have tended to argue they are simply keepers of the town square, and not responsible for the content shared there.  This abdication of responsibility should start to stop in 2018, if only because people start to tune-out the services.  This leads to one of my favorite tweets of the year:

Capture

4.  AI will move from hype to action, meaning bigger budgets, more projects, and some high visibility failures. It will also mean more emphasis on voice and more conversational chatbots.  For finance departments, this means more of what Ventana’s Rob Kugel calls the age of robotic finance, which unites AI and machine learning, robotic process automation (RPA), natural language bots, and blockchain-based distributed ledgers.

5. AI will continue to generate lots of controversy about job displacement. While some remain optimistic, the consensus viewpoint seems to be that AI will suppress employment, most likely widening the wealth inequality gap.  A collapsing educational system combined with AI-driven pressure on low-skilled work seems a recipe for trouble.

6.  The bitcoin bubble bursts. As a reminder, at one point during the peak of tulip mania, the Dutch East India Company was worth more, on an inflated-adjusted basis, than twenty of today’s technology giants combined.

tulips

7.  The Internet of Things (IoT) will continue to build momentum.  IoT won’t hit in a massive horizontal way, instead B2B adoption will be lead by certain verticals such as healthcare, retail, and supply chain.

8.  The freelance / gig economy continues to gain momentum with freelance workers poised to pass traditional employees by 2027. While the gig economy brings advantages to high-skilled knowledge workers (e.g., freedom of location, freedom of work projects), this same trend threatens low-skilled workers via the continual decomposition of full-time jobs in a series of temp shifts.  This means someone working 60 hours a week across three 20-hour shifts wouldn’t be considered to be a full-time employee and thus not eligible for full-time benefits, further increasing wealth inequality.

freelancers

9.  M&A heats up due to repatriation of overseas cash. Apple alone, for example, has $252B in overseas cash.  With the new tax rate dropping from 35% to 15.5%, it will now be ~$50B less expensive for Apple to repatriate that cash.  Overall, US companies hold trillions of dollars overseas and making it cheaper for them to repatriate that cash suggests that they will be flush with dollars to invest in many areas, including M&A

10.  2018 will be a good year for cloud EPM vendors. The dynamic macro environment, the opportunities posed by cash repatriation, and the strong fundamentals in the economy will increase demand for EPM software that helps companies explore how to best exploit the right set of opportunities facing them.  Oracle will fail in pushing PBCS into the NetSuite base, creating a nice third-party opportunity.  SAP, Microsoft, and IBM will continue to put resources into other strategic investment areas (e.g., IBM and Watson, SAP and Hana) leaving fallow the EPM market adjacent to ERP.  And the greenfield opportunity to replace Excel for financial planning, budgeting, and even consolidations will continue drive strong growth.

Let me wish everyone, particularly the customers, partners, and employees of Host Analytics, a Happy New Year in 2018.

# # #

Disclaimer:  these predictions are offered in the spirit of fun.  See my FAQ for more on this and other usage terms.

Handling Conflict with the “Disagree and Commit” and “New Information” Principles

In every executive team there are going to be times when people don’t agree on certain important strategic or operational decisions.  Some examples:

  • Should we split SDRs inbound vs outbound?
  • Should we map SCs to reps or pool them?
  • How should we split upsell vs new business focus in mid-market reps?
  • Should CSMs get paid on upsell or only renewals?
  • Should we put the new buzzword (e.g., AI, ML, social) into the release plan?
  • Should we change the company logo ?

The purpose of this post is to provide a framework to get decisions made and executed, without certain decisions becoming a form of weekly nagging at the e-staff meeting, a topic of discussion at every board meeting, or worst of all, a standing joke among the team.

The Disagree-and-Commit Principle

The first time I heard disagree-and-commit I thought it was corporate, doublespeak garbage.  What the heck did it mean?  I’m supposed to go to a meeting, say that I believe we should go left, get overrun by the group who eventually decides to go right, and then I’m supposed to say “sure, everybody, just kidding, let’s go right.”  How disingenuous — everybody knows I wanted to go left.  How controlling of the establishment.  How manipulative.  This is thought control!

“You may disagree, but you must conform … (wait, was that our outside voice) …  you must commit.”

(Recall my first professional job was as at a company we referred to as The People’s Republic of Ingres.)

Let’s just say I missed the point.  My older, wiser self now thinks it’s a great, but often misunderstood, rule.  (And that’s not just because now I am the establishment.)

Here’s a nice definition of disagree-and-commit from The Amazon Way via this blog post.

Leaders are obligated to respectfully challenge decisions when they disagree, even when doing so is uncomfortable or exhausting. Leaders have conviction and are tenacious. They do not compromise for the sake of social cohesion. Once a decision is determined, they commit wholly.

I always missed two things:

  • I took commit to mean change your mind (or “get your mind right” in the Cool Hand Luke sense). It actually means committing to execute the decision wholly, i.e., as if it were the one you had voted for.  You can’t undermine or sabotage the decision just to prove yourself right.  This is a great rule.  People aren’t always going to agree, but if you want to work at the company, you must execute our decisions wholeheartedly once they are made.  There is no other option.

 

  • The obligation to disagree.  I love this part because some people lack the courage to speak up in the meeting, and then want to passive-aggressively work against the decision and/or attempt a pocket veto by going to the person who was in charge of the meeting and saying, “well, I didn’t feel comfortable saying this in the meeting, but, ….” Such behavior creates a potential paradox for the executive in charge — particularly if she agrees with the pocket veto argument.  Does she overrule the group decision based on the new argument (and reward dysfunctional behavior) or does she stick with a decision she no longer prefers in order to avoid incenting pocket vetoes.  In my opinion, in 95% of the cases you want say, “Sorry Joe, I wish you’d said something in the meeting because that’s an interesting point, but the decision stands.” Worst case call another meeting.  Never, ever just overrule the decision.

Explicitly embracing the disagree-and-commit principle is one great way to end endless, nagging disagreements:  we met to discuss the issue, we came to a conclusion, I know you didn’t agree with it, but you need to commit to execute it wholeheartedly.  (Else we’re going to have a conversation about insubordination.)  We want a rational culture.  We debate ideas.  But we need to make and execute decisions, and you’re not going to agree with every one.

The New Information Principle

But what if the issue keeps coming up anyway?  Perhaps via periodic serious requests to reconsider the decision.  Perhaps through a series of objections coming from someone not responsible for executing the decision (so “commit” is less relevant) — but who just can’t stand the idea.  Or maybe someone has a personal ax to grind (e.g., I know we’ve talked about this before, but can we please relocate the office) and who just won’t take no for an answer.

The problem is if you always shut down these requests, then you risk creating a big problem with corporate agility.  On one hand you want to shut down the constant nagging about adding data mining capabilities from the data mining zealot. On the other hand, you don’t want to make the subject taboo because maybe your top competitor launched a new data-mining addition last month and it’s hurting you in sales.

So, the principle is simple:  if you want to re-open discussion on something we’ve already decided, do you have any new information that wasn’t available at the time we made the decision?

If the answer is no, we’re not re-opening it here, and we can do at either next quarter’s ops review or next year’s strategy offsite (pending prioritization against other topics).

If the answer is yes, find out what the new information is, and then decide if it warrants an immediate or deferred re-examination of the decision.

With this principle you can keep a firm hand against those who won’t give up on an issue while still being open to new information that might cause the need for a  valid re-examination of it.

Putting the A Back in FP&A with Automated, Integrated Planning

I was reading this blog post on Continuous Planning by Rob Kugel of Ventana Research the other day and it reminded me of one of my (and Rob’s) favorite sayings:

We need to put the A back in FP&A

This means that the financial planning and analysis (FP&A) team at many companies is so busy doing other things that it doesn’t have time to focus on what it does best and where it can add the most value:  analysis.

This begs the question:  where did the A go?  What are the other things that are taking up so much time?  The answer:  data prep and spreadsheet jockeying.  These functions suck time away and the soul from the FP&A function.

dataprep

Data-related tasks — such as finding, integrating, and preparing data — take up more than 2/3rds of FP&A’s time.  Put differently, FP&A spends twice as much time getting ready to analyze data than it does analyzing it.  It might even be worse, depending on whether periodic and ad hoc reporting is included in data-related task or further carved out of the 28% of time remaining for analytics, as I suspect it is.

spreadsheetsrule

It’s not just finance who loves spreadsheets.  The business does do:  salesops, marketingops, supply chain planners, professional services ops, and customer support all love spreadsheets, too.  When I worked at Salesforce, we had one of the most sophisticated sales strategy and planning teams I’ve ever seen.  Their tool of choice?  Excel.

This comes back to haunt finance in three ways:

  • Warring models, for example, when the salesops new bookings model doesn’t foot to the finance one because they make different ramping and turnover assumptions.  These waste time with potential endless fights.
  • Non-integrated models.  Say sales and finance finally agree on a bookings target and to hire 5 more salespeople to support it.  Now we need to call marketing to update their leadgen model to ensure there’s enough budget to support them, customer service to ensure we’re staffed to handle the incremental customers they sign, professional services to ensure we’re have adequate consulting resources, and on and on.  Forget any of these steps and you’ll start the year out of balance, with unattainable targets somewhere.
  • Excel inundation.   FP&A develops battle fatigue dealing with and integrating some many different versions of so many spreadsheets, often late and night and under deadline pressure.  Mistakes gets made.

So how can prevent FP&A from being run over by these forces?  The answer is to automate, automate, and integrate.

  • Automate data integration and preparation.  Let’s free up time by use software that lets you “set and forget” data refreshes.  You should be able to setup a connector to a data source one, and then have it automatically run at periodic intervals going forward.  No more mailing spreadsheets around.
  • Automate periodic FP&A tasks.  Use software where you can invest in building the perfect monthly board pack, monthly management reports, quarterly ops review decks, and quarterly board reports once, and then automatically refresh it every period through these templates.  This not only free up time and reduces drudgery; it eliminates plenty of mistakes as well.
  • Integrate planning across the organization.  Move to a cloud-based enterprise performance platform (like Host Analytics) that not only accomplishes the prior two goals, but also offers a modeling platform that can be used across the organization to put finance, salesops, marketingops, professional services, supply chain, HR, and everyone else across the organization on a common footing.

Since the obligatory groundwork in FP&A is always heavy, you’re not going to succeed in putting the A back in FP&A simply by working harder and later.  The only way to put the A back in FP&A is to create time.  And you can do that with two doses of automation and one of integration.

Using Pipeline Conversion Rates as Triangulation Forecasts

In this post we’ll examine how we to use pipeline conversion rates as early indicators of your business performance.

I call such indicators triangulation forecasts because they help the CEO and CFO get data points, in addition to the official VP of Sales forecast, that help triangulate where the company is going to land.  Here are some additional triangulation forecasts you can use.

  • Salesrep-level forecast (aggregate of every salesperson’s forecast)
  • Manager-level forecast (aggregate of the every sales manager’s forecast)
  • Stage-weighted expected value of the pipeline, which takes each opportunity and multiplies it by a stage- and ideally time-specific weight (e.g., week 6 stage 4 conversion rate)
  • Forecast-category-weighted expected value of the pipeline, which does the same thing relying on forecast category rather than stage (e.g., week 7 upside category conversion rate)

With these triangulation forecasts you can, as the old Russian proverb goes, trust but verify what the VP of sales is telling you.  (A good VP of sales uses them as part of making his/her forecast as well.)

Before looking at pipeline conversion rates, let me remind you that pipeline analysis is a castle built on a quicksand foundation if your pipeline is not built up from:

  • A consistent, documented, enforced set of rules for how opportunities are entered into the pipeline including, e.g., stage definitions and valuation rules.
  • A consistent, documented, enforced process for how that pipeline is periodically scrubbed to ensure its cleanliness. [1]

Once you have such a pipeline, the first thing you should do is to analyze how much of it you convert each quarter.

w3 tq

This helps you not only determine your ideal pipeline coverage ratio (the inverse of the conversion rate, or about 4.0x in this case), but also helps you get a triangulation forecast on the current quarter.  If we’re in 4Q17 and we had $25,000K in new ARR pipeline at week 3, then using our trailing seven quarter (T7Q) average conversion rate of 25%, we can forecast landing at $6,305K in new ARR.

Some folks use different conversion rates for forecasting — e.g., those in seasonal businesses with a lot of history might use the average of the last three year’s fourth-quarter conversion rate.  A company that brought in a new sales VP five quarters ago might use an average conversion rate, but only from the five quarters in her era.

This technique isn’t restricted to this quarter’s pipeline.  One great way to get sales focus on cleaning next quarter’s pipeline is to do the same analysis on next-quarter pipeline conversion as well.

w3 nq

This analysis suggests we’re teed up to do $6,818K in 1Q18, useful to know as an early indicator at week 3 of 4Q17 (i.e., mid/late October).

At most companies the $6,305K prediction for 4Q17 new ARR will be pretty accurate.  However, a strange thing happens at some companies:  while you end up closing around $6,300K in new ARR, a fairly large chunk of the closed deals can’t be found in the week 3 pipeline.  While some sales managers view this as normal, better ones view this as a sign of potentially large problem.  To understand the extent to which this is happening, you need perform this analysis:

cq pipe

In this example, you can see a pretty disturbing fact — while the company “converted” the week 3 ARR pipeline at the average rate, more than half of the opportunities that closed during the quarter (30 out of 56) were not present in the week 3 pipeline [2].  Of those, 5 were created after week 3 and closed during the quarter, which is presumably good.  However, 25 were pulled in from next quarter, or the quarter after that, which suggests that close dates are being sandbagged in the system.

Notes

[1] I am not a big believer in the some sales managers “always be scrubbing” philosophy for two reasons:  “always scrubbing” all too often translates to “never scrubbing” and “always scrubbing” can also translate to “randomly scrubbing” which makes it very hard to do analytics.  I believe sales should formally scrub the pipeline prior to weeks 3, 6, and 9.  This gives them enough time to clean up after the end of a quarter and provides three solid anchor points on which we can do analytics.

[2] Technically the first category, “closed already by week 3” won’t appear in the week 3 pipeline so there is an argument, particularly in companies where week 1-2 sales are highly volatile, to do the analysis on a to-go basis.