I’m a runner and I regularly train for half marathons.
I am also a Product Manager working on the automation within our Ocado Smart Platform warehouses around the world. But what do running and Product Management have in common? Here are five things that successful running and successful product management should have in common.
1: Set Smart Goals
Depending on the distance you train for, training plans can range anywhere from eight to 18 weeks. Before I commit myself to many months of effort and focus, I have to start with a goal I want to achieve. For example:Run the Great North Run with a chip time of 1 hour 30 minutes or less.
My training is then very much outcome-based. This is also a good example of a SMART goal as it is Specific, Measurable, Attainable, Relevant and Time-based.
Before you start out on your next product iteration, what are the goals or OKRs for your product? It’s essential to have clear goals, to make sure the development team is producing output that has the right impact. In the running world, you might heed advice to avoid ‘junk miles’ - those runs that offer no benefit to your performance.
2: Build a Roadmap
With your goal(s) in place, what’s next? If I have just come out of a period of not running and I am targeting a half marathon, a usual strategy is to focus on “base conditioning” for eight to 10 weeks before switching to an eight week “peak performance” phase of training. During base conditioning, the aim is to regain the ability to run 13.1 miles, and I map this out via weekly running total and a long run distance. For example, week one might be to run 20 miles total with a five miles long run all the way to week 10 which might be to run 40 miles total with a 12 mile long run. This forms the basis of my running roadmap.
The parallels to product management are clear here - the roadmap should tell a story of what you expect to do to achieve your goals. It is important to note at this point, there still isn’t a concrete plan. For any particular week, I do not yet know the exact runs I will do, where I will do them, or at what time.
3: Make Plans and Retrospect
Just like in a scrum framework, I plan my running schedule in weekly sprints (not the running kind). With a busy job, and two children at home, my weekly schedule is usually unpredictable. It is in this uncertain environment where agile thinking and methods excel, providing the flexibility that I need most. At the beginning of each week I have a much more confident idea of my calendar and as such, I can plan the exact training for that week.
Informed by the roadmap and a retrospective on the previous week’s progress; I can plan out the exact training sessions - what they will include, where I will do them, at what time, who with, and so on.
4: Obsess over Data
At OT we are obsessed with data, and data-driven decisions are a fundamental part of modern product management. On any run I’ll be kitted out with sensors galore tracking raw data like time, GPS position, heart rate, altitude and cadence. This data can be used to compute secondary metrics like distance travelled, pace, VO2 Max and elevation gained. In a similar manner, when creating new features or products, I strive to ensure I have a plethora of data available on the respective business and product metrics. However, this data is useless unless used to inform your work. For example, I use my heart rate data to help me refrain from over-training. Between my runs, I’ll analyse the data for any trends or correlation. Likewise, during a sprint we might try a new idea and see how it moves our key metrics, or analyse the data over several sprints to ensure we are trending in the right direction.
5: Iterate and Learn
Going back to point 1, how did I know that one hour and 30 minutes was an attainable target? And in point 2, what confidence did I have that my roadmap was correct for achieving my goals. This is where experience and iteration comes in. After many years of running and racing, I have built up experience of what works and what doesn’t and this is invaluable to consistently and efficient delivery. In a world full of quantitative data, experience is a valuable source of data and insight.
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