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Analytics Arcade: Applying the Great Game of Business Principles for a High Score
Sanity Check • No. 017
I’m Ben, and welcome to Sanity Check. The data field is so funny with their titles. Here, I don’t worry about them. If you don’t mind meandering through the full range of analytic jobs to be done, you just might like this newsletter.
QQ: QUICK QUOTES
Here’s what’s new with me:
🤿 I hope you all had a Labor Day! We took baby Wilson into the pool for the first time. She loved it!
🏈 Football is back and so far it has exceeded expectations. I got an A+ on my fantasy draft - projected to go undefeated. The Steelers looked sharp with an undefeated preseason. Even the Tar Heels are starting on a high - claiming the rights to the Carolina namesake over USC… oh that name is claimed too.
🕹️ New article this week reflecting on
- my biggest career win with analytics
- lessons from the Great Game of Business book that shaped that win
- takeaways for data practitioners to repeat that success
I plan to post this article to my website as well, but you get to enjoy it here first!
Analytics Arcade: Applying the Great Game of Business Principles for a High Score
On a routine morning, people punched in for their routine factory job, planning to routinely pass the hours until their evening routine began. But this day broke the norm - the plant was to be shut down and sold for parts.
Instead of brushing off their resumes, the employees rallied to buy the business. Their jobs were now safe, but a new challenge emerged. How were they going to run the place?
This is the story of Springfield Remanufacturing Company (SRC). In Jack Stack’s book - The Great Game of Business (GGOB) - he outlines how SRC not only survived but thrived. The book distills SRC’s turnaround into three core game mechanics pinned together by a metric. This playbook puts the need for analytics at its very center - and when I joined my first data team my new employer had just pressed play.
Now my situation wasn’t so dire. No one was on the cusp of losing their job. However, on the water-cooler-to-work ratio of productivity, let’s just say the kitchen needed restocking daily. There wasn’t much getting done. Most employees had the same punch-in punch-out mindset as the factory workers.
Zooming out to how this lax culture came about, this company had seen a lot of change. It was a 30-year-old technology company. They survived pivots from a professional services firm to selling software on CDs to a cloud-enabled Software-as-a-Service (SaaS). Along the way, the company kept collecting acquisitions, each given an animal brand. By the time I joined, our product portfolio was indistinguishable from a zoo.
These product spirit animals ran deep. Sales teams, engineers, support specialists, P&Ls, and even office space were all stratified by product. Shared coffee breaks were unlikely. Establishing a shared company mission was even further off - yet that was the challenge set before me.
I was conscripted by the COO and CFO to join a small task force to tame this zoo. Our “tiger team” was tasked to define the company’s critical metric to unite us all. After many months of Italian food-fueled late Wednesday nights, our two pizza-sized team emerged with our critical metric - NET NEW MRR (Monthly Recurring Revenue).
Now if you’re familiar with SaaS, you may be thinking “no duh - that’s an obvious choice.” To which I would respond, “easier said than done.” Hang with me to drill the fundamentals.
For the uninitiated, you’re the normal ones here. Together, let’s put our Net New MRR metric through its paces. With the GGOB mechanics as our guide, why would this be our critical metric?
Know & Teach the Rules
Net New MRR measures your business’s monthly growth. It adds together the changes in Monthly Recurring Revenue (MRR) from new customers, expansion from existing customers, and lost revenue from revenue contractions. At its simplest, it breaks down into a few components:
Land - a new customer’s first recurring payment
Expand - an increase in the customer’s recurring payment, typically more licenses or a complimentary product
Downgrade - the opposite of expansion, a decrease in a customer’s payment
Churn - when a customer no longer pays to be a customer :(
Understanding the metric components is not enough. Too many data teams do not promote their work. Once we surfaced from our
skunk tiger works we went on an internal roadshow. We earned a recurring spot on our monthly all-hands, hosted lunch-n-learns, and met with department leads to strategize how their work ties into the critical metric.
People caught on quickly. They began educating others. They asked better questions and experimented. Now that the teams were playing, their eyes turned up to the scoreboard.
Follow the Action & Keep Score
With a clear critical metric objective and the autonomy to pursue improving it, people were excited! Teams wanted to see if their work was moving the needle. They would ask if they hit their target yet with the persistence of road-tripping toddlers. Are we there yet? Are we there yet? Are we there yet?
Unlike those poor parents, data teams have a good answer - dashboards!
Dashboards are the scoreboards of businesses everywhere.
But that’s not the whole answer. There is a depth of detail hidden behind that calm bar chart facade. That complexity is wrangled by data engineers. Armed with SQL, a shared drive, and cron job schedules, we were able to gather data from 7 production systems, navigate odd edge cases, and deliver a stable set of metrics. It is not how I would do things today, but I cannot overstate the importance of metric stability while playing. Stable data engineering is a path to the game’s OS layer.
Provide a Stake in the Outcome
Experiments began turning up new winning strategies and the organization shifted to align incentives to them. Instead of sales teams being organized by product, they were divided into “hunter” (land-focused) and “farmer” (expand-focused) teams. Support teams began early outreach “churn-buster” programs to proactively resolve issues for customers that had shown decreased engagement. Then everyone received bonuses and equity compensation for the company hitting Net New MRR growth targets.
For this principle, the data team played a supporting role. Our experiments could inform the strategy, but major credit is due to the leadership team. The executives and VPs followed through a reorg to align teams with Net New MRR growth targets and then generously shared the upside.
After educating the colleagues, keeping them in the game with dashboards, and aligning incentives, our founder began looking for an exit. The data team was called up again to support the due diligence process. Our ability to tie metrics back to our critical Net New MRR metric gave confidence to the buyer that the acquisition would be a good deal. We were able to close the deal at a unicorn valuation, minting 70 millionaires overnight.
That score will always have a spot on my leaderboard.
Analytics played a big role in the success of my employer and the turnaround of Springfield Remanufacturing Company. It does not matter the industry you are in - SaaS, manufacturing, e-commerce, healthcare - the GGOB mechanics of “Know & Teach the Rules”, “Follow the Action & Keep Score”, and “Provide a Stake in the Outcome” will be in play. To rack up your own high score you’ll need stable data engineering and savvy analysts.
Every game is different, but they are worth playing. As a data practitioner, your team is going to need you every step along the way.
Defining the ground rules - metric definitions
Educating colleagues - report presentations
Building a scoreboard - dashboard development
Always keeping score - data engineering
Setting a target - forecasting
Start with defining the game. How does your company operate? If you asked 10 others, would their answer match yours?
When you find the metric that ties all the answers together, you’ll be on your way to playing a beautiful game.
Thank you for reading.
Let’s keep it going. 💜
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