Fortella, which I’ve served as an advisor over the past year or so, makes a revenue intelligence platform. The company recently published an interesting survey report entitled The State of B2B Marketing: What Sets the Best Marketers Apart? Rahul is super passionate about marketing accountability for revenue and the use of AI and advanced analytics in so doing, which is what drew me to want to work with him the first place. He’s also an avid Kellblog reader, to the point where he often reminds me of things I’ve said but forgotten!
In this webinar we’ll drive a discussion primarily related to two Kellblog posts:
That pipeline isn’t a monolith and that we need to look inside the pipeline to see things by opportunity type (e.g., new vs. expansion), customer type (e.g., size segment, industry segment) and by source (e.g., inbound vs. partners). We also need to remember that certain figures we burn into our heads (e.g., sales cycle length) are merely the averages of a distribution and not impenetrable hard walls.
By decomposing pipeline we can identity that some types close faster (and/or at a higher conversion rate) than others, and ergo focus on those types when we are in a pinch.
Let’s start by unveiling the last block on the sheet we’ve been using the previous two posts. Here’s the whole thing:
You’ll see two new sections added: next-quarter pipeline and all-quarters  pipeline. Here’s what we can do when we see all three of them, taken together:
We can see slips. For example, in week 3 while this-quarter pipeline dropped by $3,275K, next-quarter pipeline increased by $2,000K and all-quarters only dropped by $500K. While there are many moving parts , this says to me that pipeline is likely sloshing around between quarters and not being lost.
We can see losses. Similarly, when this-quarter drops, next-quarter is flat, and all-quarters drop, we are probably looking at deals lost from the pipeline .
We can see wins. When you add a row at the bottom with quarter-to-date booked new ARR, if that increases, this-quarter pipeline decreases, next-quarter pipeline stays flat, and all-quarters pipeline decreases, we are likely looking at the best way of reducing pipeline: by winning deals!
We can see how we’re building next-quarter’s pipeline. This keeps us focused on what matters . If you start every quarter with 3.0x coverage you will be fine in the long run without the risk of a tantalizing four-quarter rolling pipeline where overall coverage looks sufficient, but all the closeable deals are always two to four quarters out .
Tantalus and his pipeline where all the closeable deals are always two quarters out
We can look at whether we have enough total pipeline to keep our salesreps busy by not just looking at the total dollar volume, but the total count of oppties. I think this is the simplest and most intuitive way to answer that question. Typically 15 to 20 all-quarters oppties is the maximum any salesrep can possibly juggle.
Finally, there’s nowhere to hide. Companies that only examine annual or rolling four-quarter pipeline inadvertently turn their 5+ quarter pipeline into a dumping ground full of fake deals, losses positioned as slips, long-term rolling hairballs , and oppties used for account squatting.
I hope you’ve enjoyed this three-part series on forecasting and pipeline. The spreadsheet used in the examples is available here.
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 Apologies for inconsistences in calling this all-quarter vs. all-quarters pipeline. I may fix it at some point, but first things first. Ditto for the inconsistency on this-quarter vs. current-quarter.
 You can and should have your salesops leader do the deeper analysis of inflows (including new pipegen) and outflows, but I love the first-order simplicity of saying, “this-quarter dropped by $800K, next-quarter increased by $800K and all-quarters was flat, ergo we are probably sloshing” or “this-quarter dropped by $1M, next-quarter was flat, and all-quarters dropped by $1M, so we probably lost $1M worth of deals.”
 Lost here in the broad sense meaning deal lost or no decision (aka, derail). In the former case, someone else wins the deal; in the latter case, no one does.
 How do you make 32 quarters in row? One at a time.
 Tantalus was a figure in Greek mythology, famous for his punishment: standing for eternity in a pool of water below a fruit tree where each time he ducked to drink the water it would recede and each time he reached for a fruit it was just beyond his grasp.
 Even though most companies have four different pipeline sources (marketing/inbound, SDR/outbound, sales/outbound, and partners), marketing should, by default, consider themselves the quarterback of the pipeline as they are usually the majority pipeline source and the most able to take corrective actions.
 By my definition a normal rolling hairball always sits in this quarter’s pipeline and slips one quarter every quarter. A long-term rolling hairball is thus one that sits just beyond your pipeline opportunity scrutiny window (e.g., 5 quarters out) and slips one quarter every quarter.
This is the second in a three-part series focused on forecasting and pipeline. In part I, we examined triangulation forecasts with a detailed example. In this, part II, we’ll discuss to-go pipeline coverage, specifically using it in conjunction with what we covered in part I. In part III, we’ll look at this/next/all-quarter pipeline analysis as a simple way to see what’s happening overall with your pipeline.
Pipeline coverage is a simple enough notion: take the pipeline in play and divide it by the target and get a coverage ratio. Most folks say it should be around 3.0, which isn’t a bad rule of thumb.
Before diving in further, let’s quickly remind ourselves of the definition of pipeline:
Pipeline for a period is the sum of the value of all opportunities with a close date in that period.
This begs questions around definitions for opportunity, value, and close date which I won’t review here, but you can find discussed here. The most common mistakes I see thinking about the pipeline are:
Turning 3.0x into a self-fulfilling prophecy by bludgeoning reps until they have 3.0x coverage, instead of using coverage as an unmanaged indicator
Not periodically scrubbing the pipeline according to a defined process and rules, deluding yourself into thinking “we’re always scrubbing the pipeline” (which usually means you never are).
Applying hidden filters to the pipeline, such as “oh, sorry, when we say pipeline around here we mean stage-4+ pipeline.” Thus executives often don’t even understand what they’re analyzing and upstream stages turn into pipeline landfills full of junk opportunities that are left unmanaged.
In this post, I’ll discuss another common mistake, which is not analyzing pipeline on a to-go basis within a quarter.
The idea is simple:
Many folks run around thinking, “we need 3.0x pipeline coverage at all times!” This is ambiguous and begs the questions “of what?” and “when?” 
With a bit more rigor you can get people thinking, “we need to start the quarter with 3.0x pipeline coverage” which is not a bad rule of thumb.
With even a bit more rigor that you can get people thinking, “at all times during the quarter I’d like to have 3.0x coverage of what I have left to sell to hit plan.” 
And that is the concept of to-go pipeline coverage . Let’s look at the spreadsheet in the prior post with a new to-go coverage block and see what else we can glean.
Looking at this, I observe:
We started this quarter with $12,500 in pipeline and a pretty healthy 3.2x coverage ratio.
We started last quarter in a tighter position at 2.8x and we are running behind plan on the year .
We have been bleeding off pipeline faster than we have been closing business. To-go coverage has dropped from 3.2x to 2.2x during the first 9 weeks of the quarter. Not good. 
I can easily reverse engineer that we’ve sold only $750K in New ARR to date , which is also not good.
There was a big drop in the pipeline in week 3 which makes me start to wonder what the gray shading means.
The gray shading is there to remind us that sales management is supposed to scrub the pipeline in weeks 2, 5, and 8 so that the pipeline data presented in weeks 3, 6, and 9 is scrubbed. The benefits of this are:
It draws a deadline for how long sales has to clean up after the end of a quarter: the end of week 2. That’s enough time to close out the quarter, take a few days rest, and then get back at it.
It provides a basis for snapshotting analytics. Because pipeline conversion rates vary by week things can get confusing fast. Thus, to keep it simple I base a lot of my pipeline metrics on week 3 snapshots (e.g., week 3 pipeline conversion rate) 
It provides an easy way to see if the scrub was actually done. If the pipeline is flat in weeks 3, 6, and 9, I’m wondering if anyone is scrubbing anything.
It lets you see how dirty things got. In this example, things were pretty dirty: we bled off $3,275K in pipeline during the week 2 scrub which I would not be happy about.
Thus far, while this quarter is not looking good for SaaSCo, I can’t tell what happened to all that pipeline and what that means for the future. That’s the subject of the last post in this three-part series.
A link to the spreadsheet I used in the example is here.
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 In enterprise SaaS at least, you should look at it the other way around: you don’t build pipeline and then hire reps to sell it, you hire reps and then they build the pipeline, as the linked post discusses.
[1A] The same is true of close dates. For example, if you create opportunities with a close date that is 18+ months out, they can always be moved into the more current pipeline. If you create them 9 months out and automatically assign a $150K value to each, you can end up with a lot air (or fake news/data) in your pipeline.
 For benchmarking purposes, this creates the need for “implied pipeline” which replaces the $0 with a segment-appropriate average sales price (ASP) as most people tend to create oppties with placeholder values. I’d rather see the “real” pipeline and then inflate it to “implied pipeline” — plus it’s hard to know if $150K is assigned to an oppty as a placeholder that hasn’t been changed or if that’s the real value assigned by the salesrep.
[2A] If you create oppties with a placeholder value then dollar pipeline is a proxy for the oppty count, but a far less intuitive one — e.g., how much dollar volume of pipeline can a rep handle? Dunno. How many oppties can they work on effectively at one time? Maybe 15-20, tops.
 “Of what” meaning of what number? If you’re looking at all-quarters pipeline you may have oppties that are 4, 6, or 8+ quarters out (depending on your rules) and you most certainly don’t have an operating plan number that you’re trying to cover, nor is coverage even meaningful so far in advance. “When” means when in the quarter? 3.0x plan coverage makes sense on day 1; it makes no sense on day 50.
 As it turns out, 3.0x to-go coverage is likely an excessively high bar as you get further into the quarter. For example, by week 12, the only deals still forecast within the quarter should be very high quality. So the rule of thumb is always 3.0x, but you can and should watch how it evolves at your firm as you get close to quarter’s end.
 In times when the forecast is materially different from the plan, separating the concepts of to-go to forecast and to-go to plan can be useful. But, by default, to-go should mean to-go to plan.
 I know this from the extra columns presented in the screenshot from the same sheet in the previous post. We started this quarter at 96% of the ARR plan and while the never explicitly lists our prior-quarter plan performance, it seems a safe guess.
 If to-go coverage increases, we are closing business faster than we are losing it. If to-go coverage decreases we are “losing” (broadly defined as slip, lost, no decision) business faster than we are closing it. If the ratio remains constant we are closing business at the same ratio as we started the quarter at.
 A good sheet will list this explicitly, but you can calculate it pretty fast. If you have a pipeline of $7,000, a plan of $3,900, and coverage of 2.2x then: 7,000/2.2 (rounded) = 3,150 to go, with a plan of 3,900 means you have sold 750.
One pattern I’m seeing is CROs increasingly saying that they need more than the proverbial 3x pipeline coverage ratio to hit their numbers  . I’m hearing 3.5x, 4x, or even 5x. Heck — and I’m not exaggerating here — I even met one company that said they needed 100x. Proof that once you start down the >3x slippery slope that you can slide all the way into patent absurdity.
Here’s what I think when a company tells me they need >3x pipeline coverage :
The pipeline isn’t scrubbed. If you can’t convert 33% of your week 3 pipeline, you likely have a pipeline that’s full of junk opportunities (oppties). Rough math, if 1/3rd slips or derails   and you go 50-50 on the remaining 2/3rds, you convert 33%.
You lose too much. If you need 5x pipeline coverage because you convert only 20% of it, maybe the problem isn’t lack of pipeline but lack of winning . Perhaps you are better off investing in sales training, improved messaging, win/loss research, and competitive analysis than simply generating more pipeline, only to have it leak out of the funnel.
The pipeline is of low quality. If the pipeline is scrubbed and your deal execution is good, then perhaps the problem is the quality of pipeline itself. Maybe you’re better off rethinking your ideal customer profile and/or better targeting your marketing programs than simply generating more bad pipeline .
Sales is more powerful than marketing. By (usually arbitrarily) setting an unusually high bar on required coverage, sales tees up lack-of-pipeline as an excuse for missing numbers. Since marketing is commonly the majority pipeline source, this often puts the problem squarely on the back of marketing.
There’s no nurture program. Particularly when you’re looking at annual pipeline (which I generally don’t recommend), if you’re looking three or four quarters out, you’ll often find “fake opportunities” that aren’t actually sales opportunities, but are really just attractive prospects who said they might start an evaluation later. Are these valid sales opportunities? No. Should they be in the pipeline? No. Do they warrant special treatment? Yes. That should ideally be accomplished by a sophisticated nurture program. But lacking that, reps can and should nurture accounts. But they shouldn’t use the opportunity management system to do so; it creates “rolling hairballs” in the pipeline.
Salesreps are squatting. The less altruistic interpretation of fake long-term oppties is squatting. In this case, a rep does not create a fake Q+3 opportunity as a self-reminder to nurture, but instead to stake a claim on the account to protect against its loss in a territory reorganization . In reality, this is simply a sub-case of the first bullet (the pipeline isn’t scrubbed), but I break it out both to highlight it as a frequent problem and to emphasize that pipeline scrubbing shouldn’t just mean this- and next-quarter pipeline, but all-quarter pipeline as well .
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 e.g., from marketing, sales, SDRs, alliances. I haven’t yet blogged on this, and I really need to. It’s on the list!
 Pipeline coverage is ARR pipeline divided by the new ARR target. For example, if your new ARR target for a given quarter is $3,000K and you have $9,000K in that-quarter pipeline covering it, then you have a 3x pipeline coverage ratio. My primary coverage metric is snapshotted in week 3, so week 3 pipeline coverage of 3x implies a 33% week three pipeline conversion rate.
 Note that it’s often useful to segment pipeline coverage. For example, new logo pipeline tends to convert at a lower rate (and require higher coverage) than expansion pipeline which often converts at a rate near or even over 100% (as the reps sometimes don’t enter the oppties until the close date — an atrocious habit!) So when you’re looking at aggregate pipeline coverage, as I often do, you must remember that it works best when the mix of pipeline by segment and the conversion rate of each segment is relatively stable. The more that’s not true, the more you must do segmented pipeline analysis.
 See note 2. Note also the ambiguity in simply saying “pipeline coverage” as I’m not sure when you snapshotted it (it’s constantly changing) or what time period it’s covering. Hence, my tendency is to say “week 3 current-quarter pipeline coverage” in order to be precise. In this case, I’m being a little vague on purpose because that’s how most folks express it to me.
 In my parlance, slip means the close date changes and derail means the project was cancelled (or delayed outside your valid opportunity timeframe). In a win, we win; in a loss, someone else wins; in a derail, no one wins. Note that — pet peeve alert — not making the short list is not a derail, but a loss to as-yet-known (so don’t require losses to fill in a single competitor and ensure missed-short-list is a possible lost-to selection).
 Where sales management should be scrubbing the close date as well as other fields like stage, forecast category, and value.
 To paraphrase James Mason in The Verdict, salesreps “aren’t paid to do their best, they’re paid to win.” Not just to have a 33% odds of winning a deal with a three-vendor short list. If we’re really good we’re winning half or more of those.
 The nuance here is that sales did accept the pipeline so it’s presumably objectively always above some quality standard. The reality is that pipeline acceptance bar is not fixed but floating and the more / better quality oppties a rep has the higher the acceptance bar. And conversely: even junk oppties look great to a starving rep who’s being flogged by their manager to increase their pipeline. This is one reason why clear written definitions are so important: the bar will always float around somewhat, but you can get some control with clear definitions.
 In such cases, companies will often “grandfather” the oppty into the rep’s new territory even if it ordinarily would not have been included.
It’s that time of year, I suppose. You’ve hopefully approved your 2021 operating plan by now — even if you’re on an increasingly popular 1/31 fiscal year end. You’ve signed up for some big numbers to meet your aggressive goals (and fund those aggressive spending plans). And now you might well be thinking one thing:
But, I hear you thinking: that all sounds great and I’m sure I should do it one day — but right now I have a problem. I need some pipeline, fast.
Got it. So here are three high-level things you need to do:
Declare general quarters — all hands to battle stations. You should never waste a good crisis, so call an all-hands meeting, start it with this audio file, and tell everyone you want them working on the problem. You want zero complacency  or fatalism: we don’t need people cueing the quartet to play Nearer My God To Thee [3a] when there are still lots of things we can do to affect the outcome.
Focus on winning the opportunities you can win. You think you need pipeline, but what you actually need is the new ARR that comes from it. Let’s not forget that. In math terms, we’re going to need high to record-high conversion of the opportunities (oppties) that are in the pipeline today. So let’s put sales and executive management attention on identifying the winnable oppties and fighting like never before to win them — including potentially re-assigning your best oppties to your best reps .
Focus on finding new opportunities that move fast. Remember that nine-month sales cycle is an average; some opportunities close a lot faster. Expansion oppties tend to move a lot faster than new logo oppties. SMB oppties tend to move faster than enterprise ones. Get salesops to figure out which ones move faster for you — remember you don’t need just any pipeline, you need fast-moving (and high-converting) pipeline.
In addition, if you’re not doing it already, you need marketing to start forecasting next-quarter’s day-one pipeline as of about week 3 of the current quarter, so we can increase our lead time on finding out about these problems next time.
Now, let’s dive a bit deeper into ways to accelerate existing pipeline and how to generate new, fast-moving pipeline when you need some more.
Pipeline Acceleration Tactics
Here is a list of common pipeline patterns and how you can use them and/or workaround them to accelerate your pipeline.
Expansion pipeline moves faster than new logo pipeline. So have AEs, CSMs, or SDRs contact existing customers to discuss expansion opportunities.
It’s easier to accelerate planned expansions than create new ones. Look at out-quarter expansion pipeline and have AEs reach out to customers to discuss moving them forward and/or offering incentives to do so.
Partner-sourced pipeline usually moves faster than marketing- or sales-sourced pipeline. It also typically closes at a higher rate. Now is a great time to sit down with partners to review opportunities and see what can be accelerated and what incentives you can offer them to help out.
Proofs of concept (POCs) stall oppties in the pipeline. To remove them from your sales cycle try to substitute highly relevant customer references as alternative proof. It’s a win/win: you get your deal faster and the customer gets the benefits of your system faster. Alternatively, reduce the customer’s need for up-front proof by offering a back-end guarantee . Either way, we might be able to cut 90+ days out of your sales cycle.
Reheated, old pipeline often moves faster than new. I’ve often quipped that the best patch in the company is the no-decision pile . Now is a great time to have AEs and SDRs call up no-decision oppties. “So, whatever happened with that evaluation you were doing?” Hey, while we’re at it, let’s call up lost oppties as well. “So, did you end up buying from Badco? How’d that work out?” Both types of reheated oppties have the potential to move faster than net new ones.
SDRs can delay entry into the pipeline. We love our SDRs and they’re great for funnel optimization when times are good. But when times are tough, selectively cut them out of the loop . For example, make a rule that says for accounts of size X (or on list Y), when we get a contact with title Z, pass them directly to the salesrep. Not only might you accelerate pipeline entry by a week or two, but the AE will likely do a better job in discovery.
Legal can stall you out on the two-yard line. Get your legal team involved in your red zone offense by creating a fast-turn version of your contract that contains only your minimum required terms. Then inform the customer that you’re giving them toned-down paperwork and incent them to turn quickly with you on signing it .
Techniques to Generate New, Fast-Moving Pipeline
When nothing other than net new pipeline will do, then here are some things you can do:
Run marketing campaigns to find existing evaluations. If you can’t make your own party, then why not sneak into someone else’s? Run a webinar entitled, “How to Evaluate a Blah” or “Five Things to Look for in a Blah.” Record and transcribe it to get draft 1 of an e-book you can use as a gated asset.
Use search advertising to find existing evaluations. Buy competitive search terms (brand names), evaluation-related search terms (“how to evaluate”), comparison search terms (e.g., “Gong vs. Chorus,” “Oracle alternatives”), or late-funnel search terms (e.g., “Clari pricing”).
Look for warm accounts, not just warm contacts. Sometimes you can see more if you step back a bit. Instead of looking at the lead/contact level, do an analysis of which accounts have high levels of activity across all their contacts. That might be a good clue there’s an evaluation happening or starting.
Buy intent data. Several vendors — including 6Sense, Bombora, Demandbase, G2, TechTarget, and Zoominfo — look for data that signals companies are investigating given product categories. Let someone else do the company-finding for you and then market to (and/or SDR outbound call) them.
Buy meetings. While I’ve always heard mixed reviews about appointment-setting firms, I also know they’re a go-to resource when you’re in trouble — particularly if you’re bottlenecked up-funnel in marketing or SDRs. Consider a service like Televerde or By Appointment Only. While these vendors started out in appointment-setting, both have broadened into more full-servicedemand generation that can help you in many ways.
Stalk old customers in new jobs. Applications like UserGems let you track customers as they change jobs. What could be faster than selling an existing happy customer when they’re in a new position? It won’t hit every time (e.g., if they already have and are happy with another system), but they’re certainly leads that can turn into fast-moving pipeline. You can do roughly the same thing yourself manually with LinkedIn Sales Navigator.
Do LinkedIn targeted advertising. I’m always surprised how many colleagues say LinkedIn doesn’t work that well despite its superior targeting abilities. Perhaps that’s like anglers saying the “fishing is OK” regardless of the action. If you know who to target and think that target can move fast, then go for it.
Call blitzes. Remember we said to never waste a good crisis. It’s a great time to set up dedicated call blitzes to prospects or existing customers. Just make sure we know who’s blitzing whom so the same person doesn’t get hit by an AE, an SDR, and a CSM all at once.
Contests and prizes. Finally, why not make it fun?! Nothing gets the sales blood flowing like competition and incentives.
Hopefully these ideas stimulated some thoughts to help you get the pipeline you need. And, even more hopefully, realize that we should build many of these now-crisis activities as healthy habits going forward.
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 Meaning that your plan number is larger than your sales productivity capacity. An undesirable, but certainly not unheard of, situation.
 As I’m increasingly seeing time-based closed rates used, something to my surprise. I’d really created the technique for short- to mid-term gap analysis. I generally make an marketing budget purely off an inverted funnel model. But that said, using time-based closed rates by pipeline source would be more accurate.
[3a] While I make light of it in the post, it’s actually both an amazing and touching story. “Sometime around 2:10 a.m. as the Titanic began settling more quickly into the icy North Altantic, the sounds of ragtime, familiar dance tunes and popular waltzes that had floated reassuringly across her decks suddenly stopped as Bandmaster Wallace Hartley tapped his bow against his violin. Hartley and his musicians, all wearing their lifebelts now, were standing back at the base of the second funnel, on the roof of the First Class Lounge, where they had been playing for the better part of an hour. There were a few moments of silence, then the solemn strains of the hymn “Nearer My God to Thee” began drifting across the water. It was with a perhaps unintended irony that Hartley chose a hymn that pleaded for the mercy of the Almighty, as the ultimate material conceit of the Edwardian Age, the ship that “God Himself couldn’t sink,” foundered beneath his feet.” Hartley concluded in saying, “Gentlemen, it has been a privilege playing with you tonight.”
 Most compensation plans allow midstream territory changes and while moving oppties from bad reps to good reps cuts against the grain for most sales managers, well, we are in an emergency, andd we all know that the odds of an oppty closing are highly related to who’s working on it. Perhaps soften the sting by uplifting and then splitting the quota. Or just fire the bad rep. But win the deal.
 Introduce a 90- or 120-day acceptance clause. This will likely have accounting and/or bookings policy ramifications, but we are in an emergency. Better to hit your target with a few customers on acceptance (especially if you’re sure you can deliver against the criteria) than to miss.
 That is, the oppties that were marked by their owners as neither won nor lost, but no decision. Sometimes also called derailed oppties. If you have discipline about reason codes you can find the right ones even faster.
 Perhaps using the freed-up time to prospect within the installed base, if your CSMs are not salesy. Or doing longer-shot outbound into named accounts.
 I’m a little dusty legally, but the ultimate form of this was a clickwrap which, in a pinch, was sometimes used (with the consent of the customer) to work around the customer’s oft-bottlenecked legal department and get a baseline agreement in place that can later be revised or replaced.
I’m Dave Kellogg, advisor, director, consultant, angel investor, and blogger focused on enterprise software startups. I am an executive-in-residence (EIR) at Balderton Capital and principal of my own eponymous consulting business.
I bring an uncommon perspective to startup challenges having 10 years’ experience at each of the CEO, CMO, and independent director levels across 10+ companies ranging in size from zero to over $1B in revenues.
From 2012 to 2018, I was CEO of cloud EPM vendor Host Analytics, where we quintupled ARR while halving customer acquisition costs in a competitive market, ultimately selling the company in a private equity transaction.
Previously, I was SVP/GM of the $500M Service Cloud business at Salesforce; CEO of NoSQL database provider MarkLogic, which we grew from zero to $80M over 6 years; and CMO at Business Objects for nearly a decade as we grew from $30M to over $1B in revenues. I started my career in technical and product marketing positions at Ingres and Versant.
I love disruption, startups, and Silicon Valley and have had the pleasure of working in varied capacities with companies including Bluecore, Cyral, FloQast, GainSight, MongoDB, Recorded Future, and Tableau.
I previously sat on the boards of Granular (agtech, acquired by DuPont), Aster Data (big data, acquired by Teradata), and Nuxeo (content services, acquired by Hyland), and Profisee (MDM, exited to Pamlico).
I periodically speak to strategy and entrepreneurship classes at the Haas School of Business (UC Berkeley) and Hautes Études Commerciales de Paris (HEC).