Increase Product Success
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Increasing new product success rates using better front end selection models.
"My division has a product success rate of 9%, how can I improve our performance?" said one general manager recently.
Increase your new product success rate by finding the root causes of poor performance and translating these into selection criteria to pick better products (to develop). This process also uncovers issues that are causing the wrong products to be defined in the first place.Better failure analysis, i.e. why do some new products miss their targets?, can be translated into better new product selection criteria so that more good ideas get into the development pipeline than bad ones.
We do this by defining failure (or success) in terms of four basic criteria that include strategic objectives, right-product, right-time, and right for us. The definition of success is often more than the absence of failure. We also factor in the "absence of intangibles" such as sales force effectiveness, poor customer communications, poor product positioning, lack of sufficient advertising budget, etc. when doing the root cause analysis once products are released to the market.
Product Success Analysis mindmap.
Take for example the case were a development team was late with what turned out to be a poorly defined product. We later learned that they never knew what the customer wanted in the first place as they were not really talking directly to the customer. Had they used a selection model to vet the project before it started, where customer engagement was critically important, it is likely that this product would have received a low raking and therefor may not have been funded.
To test this idea (example below) we ranked six released products against the client's new product selection criteria. The three products that ranked lowest all, it turned out, had failed to meet their target expectations when released to the market. The three top ranked products were all measured as successful, based on the client's financial and strategic metrics.
Analysis done on completed and released products.
Better front end new product selection models tend to improve the chances of product success once a product comes to market. Further, both successful and failed products need to be studied to determine the root causes, in either case, for their performance in the market.
This has to be factored back into improving the front end selection model. Better selection criteria improves the ratio of successful product released. New product success directly impacts growth and profitability as new products tend to provide the greatest contribution to margin.