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The demand for new products and disruptive innovations echoes like a drumbeat through the halls of major corporations around the world. Leaders hunt for sparks from product people and others as they recall the work of Jobs, Gates, Page and Brin. Yet, for all the investments in innovation, the fact remains that business case success rates still hover at about a third, with billions of dollars hauled off to the trash bin of failed products.
Meanwhile, it’s fair to say that companies make their money from the actual products that are sold, not the products that are conceived or placed into development. Innovation and development activities drain cash from the corporate treasury.
Product revenue and profit add to the treasury.
The key is to tip the scales in favor of more money coming in and less going out. Simple. Right?
If I were to say that product people can start to balance the scales by being more vigilant about the optimization of the performance of current products, you’d probably agree. I can also safely suggest the obvious: Solid profits are not always made from the next big feature or newly created user experience. It’s about cost management, efficiency oriented, and geared to make better business decisions.
However, that’s on the surface. I want to encourage you to look below the surface at the gold that needs to be mined, refined, and utilized. That gold is data.
Product managers must understand that data are the fuel that runs the product’s business. Data are necessary to help you evaluate how your product performs and how it contributes to the bottom line. For example, complaint or defect reporting data can be associated with certain triggers that require attention. If a component or module is causing problems, it can be fixed. Your role is to ensure that the right data are available and to actively facilitate the integration of myriad data elements.
Data don’t always appear as figures on a financial statement or graph points on a market share chart. Data can be derived from documents you read, processes you use, customers you observe, and competitors you meet on the market battlefield. Data can also reside in many systems in your company and in publicly available repositories.
Your job is to identify the right mix of data that can be used as measurements (like yardsticks) to figure out the path taken (especially compared to established goals) and to form a fact base.
Then, mechanisms need to put in place to track and analyze data. From this, fact patterns and the resultant insights can be seen. Fact patterns are used by lawyers to establish a trail of evidence in a case. The same technique can be used by you and your team.
Once you have your measurements, I recommended that you synthesize and integrate these into some kind of product health report that can provide an indication of how you’re doing against established plans, and from which variances can be surfaced and traced back to the root cause of an issue. Another method I like is to plot a number of data elements so they resemble a host of overlapping curves; product life cycle curves.
When you can associate a relatively finite set of measurements and create associations, you can more easily articulate what happened, why, and what can be done. This is where “connecting the dots” becomes so important.
While fact-base synthesis is easy to suggest, it’s made more difficult when you don’t have current, relevant data. Also, and as I’ve alluded to, not all data is a number so you might have to fill in some gaps with some relevant hypotheses. Your job is to continually fine-tune these, work with your cross-functional team specialists, and come up with ideas and investments that will help you grow and prosper – and of course – make more money.
Alternatively, shoot me an email and perhaps we can discuss tools you can use to optimize your product’s contribution to the company.