RevOps and the Command Center
If you’re new to this newsletter then welcome! Thank you to the 1,400 revenue operations professionals who continue to subscribe to this newsletter. You’re the reason I continue to write each and every week on a Go To Market related topic. When I have a template to share paid subscribers will get access. I don’t have all the answers in revenue operations. That’s impossible because RevOps can be uniquely situated for each unique situation. But what I hope you can take away a few guiding principles or tactical snippets which you can use in your day to day. Before jumping into the newsletter, let’s hear from our sponsors that keep most of this newsletter free to readers.
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This week’s newsletter is all about creating a Command Center for Revenue Operations. I thoroughly enjoy Wikipedia’s definition of a command center:
A command center enables an organization to function as designed, to perform day-to-day operations regardless of what is happening around it, in a manner in which no one realizes it is there but everyone knows who is in charge when there is trouble.
What I love about this is you can break it down into its components:
enables functions as designed: you set a plan in motion and the business behaves as intended. BRILLIANT.
to perform day-to-day operations regardless of what is happening around it: it is resilient AND useful. It is set up in a fashion which everyone can leverage it without question.
in a manner no one realizes it is there: it’s deeply embedded in your business. It’s the last thing you think about. Like electricity, no one notices it until it’s gone. Revenue operations and leadership use the tool with intention.
In order to build up a command center of your own I think it sensible to start with escalating your business up the Decision Maturity Curve.
How mature are you at decision making?
This is not a real framework but it should be.
Level 1: The Drudgery
Level 2: The Dashboard Era
Level 3: Leaning into the Narrative
Level 4: The Command Center
Level 1: Manual data drudgery
This stage can be characterized as building manual reports. Communication is achieved through spreadsheets and presentation decks. In fact, because the data sources are obscured it leads to a high level of suspicion around the veracity of the data. Each time an analysis is completed it is potentially done differently each time. This is the drudgery.
Before going into the second phase of data maturity, organizations will take intermediate steps to resolve the issues with phase one. Namely:
Defining data standards (i.e. waterfall enrichment, building a data dictionary
Setting operating rhythm standards (i.e. forecasts are submitted on Fridays and locked on Mondays, snapshot taken on Monday evening)
Combine all data into a data repository (datawarehouse, datalake) from which dashboards can build atop
Level 2: The Dashboard Era
The second phase is the era of the dashboard. The data becomes more trustworthy. Soon, more department leaders start knocking on your door because they want what you have. The ability to see their business clearly without obfuscation. Dashboards start to bloom like flowers in the spring. The overhead to maintain this level of internal product may require a centralized data team. As good things often do, it comes with a price. Teams of data scientists and analysts are formed to spread the gospel of good data.
Downsides exist with this model. Shadow data teams can arise. In fact, the cost to maintain said data can be higher than one thinks. The cost of data infrastructure and the data team itself can be shocking. Dont be surprised if this entire setup sets you back $500,000 or greater. The worst part is when the data infrastructure is misused by savvy analytics users only to come up with different answers. In fact, the one source of truth becomes multiple, inconsistent sources of truths.
Level 3: Leaning into the narrative
In this phase the business has truly shifted from reactive to proactive. Here, the business has not only built dashboards, but has built the underlying architecture from both a process and a systems perspective for others to repeat. In this organization, the following have been achieved:
Data procedures are documented
Data sources are inventoried
Rules and policies have been defined and optimized
Responsibilities assigned (use a RACI matrix here)
Workflow redundancies have been reduced
Rules and policies are continuously enforced
That last piece is the most important to me. In a previous post I talked about setting up an operating cadence. Do the same with your decision maturity. Embed your new data and insights into your day-to-day and week-to-week.
Let’s use forecasting as an example
Imagine that you have a weekly forecast call every Monday at 11 AM PST. You know that your team has a difficult time submitting their forecast before Monday. So how about setting up the following schedule for them and for you. Read these bullets from bottom to top (I often like to work backwards).
Monday 11 AM PST: forecast call
Friday 2 PM PST: review forecast and document questions (share with leaders)
Friday 12 PM PST: forecast LOCKED
Friday 8 AM: review feedback from reps and document as notes.
Thursday 4 PM PST: review forecast and document questions for reps. Comments due. by Friday at Noon.
Thursday Noon PST: forecast SUBMISSION is due
Everyone’s technology stack is going to be different but let’s say for example you had the following as part of your infrastructure:
Slack (weekly reminders)
BoostUp (used for forecasting and pipeline management)
Asana (forecast follow ups)
With Slack you can set up weekly reminders. You can something like this up with the following command:
/remind #sales Hey @channel Submit your forecast in BoostUp on Noon this Thursday every Tuesday at 10:00am
Obviously, sales reps don’t need reminding but hey you never know!
Now every forecasting setup is going to be different but let’s say you had BoostUp. With this tool you’d be able to do the following:
Bottoms up submission from your reps
Indicator if forecast is missed (uh oh! governance issue)
Roll-up summary of forecast
Manager haircut or upward adjustment (override)
With a similar setup you’ve moved into a proactive state by setting up your cadence and alerting the entire team as to how and when to fill out the forecast. And with your tool of choice, you’re able to communicate out to the organization the entire rollup as well as the detail below.
But you also need a narrative. Is your forecast ahead of projection? Is it behind? Are you good to go for this quarter? But what about future quarters?
This is where the narrative comes into play. Carve out time each week to analyze the numbers for each of your cadences. If it’s a forecasting cadence, assess your forecast numbers and your pipeline numbers. If it’s a pipeline management cadence, assess your sales methodology fields, for example your MEDDICC fields. Start with small wins. Maybe you’re carving out 3% of your week to do this (1 hour) at first. Then get to a place where you’re dedicating 10% to this. To each your own, but here’s where I would emphasize that 10%.
1 hour for forecasting (searching for anomalies, never changing forecasts, “happy ears”, “sandbaggers”, “mailing-it-in” next steps)
1 hour for pipeline management (search for below 3x coverage ratios, past due close dates, poor data hygiene)
1 minutes for your what’s coming up this week prep (i.e. identifying projects to push out or pull-in)
1 hour for the weekly summary (i.e. sprint communication, weekly forecast or pipeline memos, touch ups to investment requests)
Level 4: The Command Center
Lastly and most importantly, the command center level. We’ve gone through the journey of evolving the Revenue Operations team to move from inconsistent / manual / reactive data analysis to consistent / automated / proactive decision making. Now it’s time to start seeing around corners.
In this phase you’ve optimized your cadences and now you can anticipate change. Here, your cadences have scenarios behind them. Your forecast is not just a Commit + Best Case with “Commit” as your worst case scenario. In fact, you know that X out of 10 times you fall short of your Commit. In the Command Center you start to ask yourself what happens if we fall below Commit? Is that realistic?
In most cases, yes it is. Business results don’t always pan out the way you think they will even if you have the strongest possible GTM Operations governance. STUFF HAPPENS.
A customer pushes you out because of legal challenges. Is that on them? Is that on you? Maybe!? But it happened.
The customer was acquired out of the blue and has been decided, for them, that they can no longer work with you.
The prospect you’ve been working with disappears for medical reasons. Couldn’t predict that could you?
Sure, you can always come up with hedges. BUT STUFF HAPPENS.
Operating a thoughtful command center sets up Plan A, Plan B, and Plan C. It tries to develop pathways to de-risk each of those paths. It operates less on hope and more on pragmatism. It doesn’t rely on a hail mary play. It relies on getting down field four downs a drive (American football reference in case you’re wondering).
Let’s say you’re operating a pipeline management call. You’ve set up a target of 3x coverage. This is your threshold because that’s what conventional wisdom says you should do. If you operated this way, you would need 33% of every dollar of your walk-in pipeline to result in a Closed Won in order to hit target. No ifs, ands, or buts. This is what you need to do.
Previously I wrote about the sales motion. In that article I proposed a sample of stages with corresponding win rates.
Closed Won (100%)
One might conclude, well you need to walk in with a third of your pipeline in proposal going into the quarter. NOPE!
We need to also consider deals that will positively progress in the quarter. These deals have a real, albeit lower percentage, shot at closing in the quarter.
We’ll build a stupidly simple weighted view of this. We’re trying to get to Closed Won, but if we can’t get there, let’s at least get to Proposal stage to achieve a 35% bar in line with our 3x coverage (inverted to get 1/3).
Let’s say that your sales motion is 120 days. And you’ve found that 50% of your deals in the Alignment stage progress to Proposal within 30 days of entering that stage. You also noticed that 25% deals in the Demo stage move into proposal within 60 days. You could then look at the following:
All deals in Negotiations and Proposal on DAY 1 of the quarter
50% of deals in Alignment on Day 1 of the quarter
25% of deals in Demo on Day 31 of the quarter
Using these cohorts by stage, you would be able to stack these on top of one another to see if you have an adjusted coverage ratio of 3x or greater.
Imagine putting together risk adjusted scenarios for each of your operating cadences. Do this over and over throughout the business and witness the level of decision making move up several degrees.
Pain and Outcomes
If there’s one thing Revenue Operations teams know. It’s PAIN.
A command center is central for resolving key pains. Get to the source of the issue by identifying trends, insights and use that to develop better processes buttressed with stronger governance.
In due time you may be able to see the pain flipped into a gain.
Unreliable pipeline to predictable pipeline
Misaligned forecasting to accurate forecasting
Failing to get more from reps to having highly productive reps
To wrap, a command center is more than just a dashboard. Put the data in the context of the business. Drive decisions by adjusting your risk ahead of time with appropriate scenario plans. Build internal relationships with your stakeholders and leverage all of the above in your conversations. Look at the problem from several angles and decide which path to follow. Do that over and over and I believe good things will emanate from your decision stack.
For all paid members I’m going to start hosting a Monthly HeRO (Head of RevOps) Town Hall. Which date would work for you? [Poll below]
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