After recognizing that our development team would remain inundated with far too many product requests, I decided to examine our entire collection of products with an eye toward slowing or reversing ongoing product investments.
Like any Product team, we are never in short supply of feature requests, product suggestions, looming technical debt, must-have components, urgent customer pain points, etc. And we do our best to stay on top of the things, trying to keep all parties happy-ish. But over the past few months, I had started to see important product enhancements slipping from each release and was able to attribute those slips to other competing product priorities.
Because there are quite a few moving parts in a typical software development shop, there are any number of places you could start the analysis. Our problems could be related to bad grooming practices, poor scoping efforts, or even an understaffed engineering team. But I know the problems we were having were not limited to a single product or any one PM. It was simply proving too difficult to keep all our balls in the air.
We had launched a generous number of products over the past decade but poking around at the ground level was likely to be an unproductive exercise. I needed a model to help me and our team evaluate decisions across our entire portfolio.
What drove this decision
I was getting anxious about the number of product-related discussions the Management team was having and becoming convinced that they had lost some perspective on what we had already committed to. In fact, there were signs that the company's entire product strategy might be in need of a refresh so I scheduled a mid-year strategy meeting with the management team to do just that. But I felt there was a need to connect the day-to-day challenges we were having with each product release to the product discussions that were happening (at an increasing rate) at the executive level.
I needed to create a backdrop for our high-level product investment decisions that would also drive real benefits at the troop level.
The decision: Create a model for evaluating current and future product portfolio decisions
Over the past decade or so, we had made decisions to create new products and not all of them turned out to be winners - no real surprise I guess. The bigger problem was that we had managed to sell each product to some subset of our customer base so we had an obligation to support it through troubleshooting, bug fixing and occasionally, even enhancement-ing. This obligation grew non-linearly with each new product.
I knew the customer usage patterns were irregular and more importantly, the revenue we derived per product was inconsistent and unpredictable. Despite this, we had no plans to sunset any of the products thus perpetuating our dilemma indefinitely.
I needed to spark some productive conversation. I needed to shed some light on the impact of our past decisions and try to head off some questionable proposals that were brewing in the company.
Plan of attack
The diagram that I built only needed to be as complex as the audience I was targeting. I felt I could communicate a great deal with coarse-grained data elements, where conclusions could be drawn (no pun intended) by counting boxes or showing the relative size or positioning of boxes. I ended up with something along these lines (pun fully intended):
1 - Plot the products on a simple graph based on revenue vs. customer use
I strongly recommend that you organize your graphs so that the most desirable position is in the top right corner. Both X and Y axes should go from low to high, least to most, etc.
I started by placing each product on the chart based on how much customers were using it and how much revenue it generated. In using these axes, I was hoping my products would be stacked up and to the right. If plotted accurately, it should be easy to defend ongoing and future product investment decisions with this simple graph.
In an attempt to communicate more information with fewer charts, I decided to use the relative size of the product "boxes" as an indicator of our current investments. Without aiming for exactness, I was able to quickly explain where our resources are being deployed. A slightly more complex approach would have been to use other graphical elements to break down the current investment by Product, Engineering, Operations and Support.
2 - Clarify the ratio of Products to Product Resources
Our company currently has more than 15 products in our portfolio and I'm sad to report, not nearly enough Engineers and PMs to manage a portfolio of that size. We have found ourselves in this situation after years of adding new products because at the time, we believed they were crucial to our company's success.
But like many eager, young software companies, we never seem to plan well for the long-term maintenance and support of each new product. I can't help but make the comparison to the decision of adding a new baby to your family. Everyone thinks it a wonderful idea at first but after spending a number of grueling months bringing it into the world, you find yourself responsible for taking care of another living thing for the rest of your life (or your life at the company at least).
With a few, carefully placed text overlays, I listed on the diagram, the relative sizes of our current teams which revealed the stark truth about our current staffing situation. This helped set the stage for a productive conversation about acquiring more Product/Engineering resources or reducing the size of the product portfolio or both.
3 - Future investment and product goals
I used the same model to spell out some of our short and long term product strategy. With the boxes already arranged on the chart, I added arrows to indicate where we would expect to see movement in the months ahead. Specifically, I predicted the movement of various products over the next 6-12 months in terms of increased/decreased usage and increased/decreased revenue.
By adding a few crude marks over some of the product boxes, I was able to show which products in which I intended to reduce our investment and even more, which I thought we should retire in the months ahead.
There are more messages that can be highlighted and communicated in a chart like this. Seeing all the products intelligently placed next to each other on a single page inevitably invites more strategic conversations like:
- Why are we still supporting this product if the usage rate is that low? It's time to retire it.
- When is the last time we updated the technology behind those products? They're due for a refresh.
- How long has it been since we last sold this product? Let's try lowering the price.
Armed with this new model, I was able to drive a strong Product-focused agenda at the Strategy Summit and was even able to successfully head off some premature ideas that could have led us further down the wrong path.