What if well-planned innovations still fail?
Q: Will you please continue with your series on product and process innovations? We have a different case for a Marketing Rx. Last year, we attended your continuous innovation seminar. We learned then that for our product line, if we wanted to grow total sales, we needed to align our product innovations with each “new” product’s sales cycle.
We make and sell donuts of over three dozen variants. Each variant has a sales cycle of four to five weeks. Your recommended alignment meant that our product development people in our kitchen should come out with a “new” donut variant every four to five weeks. Allowing for conceptualizing, prototyping and pretesting, our ProdDev told us that they needed about three months’ lead time before any given month’s intro of a new donut variant.
Your seminar recommended also that we observe how the market leader in donuts does continuous donut innovation. Industry observers told us Mister Donut has already overtaken Dunkin Donut as market leader. We saw that Mister Donut has been into an every-month-new-donut-variant selling but with a 1-2 week break between a previous and a new variant. We imitated that sales cycle since July last year to the present.
We have had some total sales increase but only a little. However, the sales of over 60 percent of our new donut intros fell below quota. Since last year, we’ve been analyzing and reanalyzing things and ended with the same question marks. Our CEO has been just as frustrated and started telling us to give up our “analysis-paralysis” routine. But what else is there to do? Please help.
A: We agree that your case is different. But it also happens to be typical of many other product categories that belong to the “hit industry.” And your donut variants participate in this industry.
A product or service has by definition a relatively short or even very short product sales cycle. This makes its presence in the market short-lived as well.
On your side as marketer and producer, the situation renders your organizational and operational problems intense or even very intense. And you’re showing it. But you’re surviving it at least so far. The key is to transition from mere surviving to thriving.
What holds the key to that transitioning? There are several keys. But one that already is right under your nose is to get that “over 60 percent of new donut variants below sales quota” to be above quota. You’ll uncover that if you focus your “analysis and reanalysis” on that issue.
Challenge your CEO’s quick judgment that you’re guilty of analysis-paralysis. That of course can be true. But it’s true only when your analysis and reanalysis take the same direction under the same market assumption. Base your analysis and reanalysis on repeated research.
We tell our hit industry clients to follow this research rule: “Test quickly; test often; and test anew.” You’ll fall into the analysis-paralysis trap if you do testing up to the second level skipping the third. That means you don’t “test anew.” You do not test with a new “hunch,” a new “hypothesis” about what could have gone wrong.
Example. When some ten years ago, the two big telecom companies, SMART and Globe decided to enter the international remittance market, each tested its remittance brand against each other. It tested quickly and often. First, they tested with OFWs in Hong Kong. And then the testing went to OFWs in Singapore, and then with those in Taiwan, and next with those in Australia. Throughout, the results were similar. Sometimes the preferred brand was SMART Padala while at other times, it was GCash. The conclusion and implication drawn were simple: “There’s nothing wrong with either product. It will just take time to penetrate the market. So we just need to persist.”
Limiting and repeating your research on the “test quickly and test often” rule is the wrong analysis and reanalysis practice. It’s certain to lead you to analysis-paralysis. It’s the “fool’s rule.” Philosophers define a fool as asking the same question over and over again and expecting to get a different answer.
Had the research gone to the third level of “testing anew,” the analysis could have concluded and drawn more practical and more insightful implications. Testing “anew” could have asked these two new questions: (1) “What have you been using the most for your international remittance needs and how would you compare SMART Padala/GCash to this remittance means?” and (2) “For what sort of remittances would you find SMART Padala/GCash particularly good to use?”
Hindsight tells us now that the “test anew” on the first question identified the customer-defined competitors as first, commercial banks and second, door-to-door. Against these two traditional international remittance agencies both SMART Padala and GCash rated poorly on “security” and “on-time receipt.” These should be SMART Padala’s and GCash’s product improvement targets. It’s not true that there’s nothing wrong with either of them. From the responses to the second “test anew” question came the insight that SMART Padala and GCash’s more suitable primary target market segment was the domestic remittance market.
So analysis and reanalysis need not end up as analysis-paralysis. Extend your analysis practice to testing “anew.” Test for some other plausible explanations, some other plausible causes. Be analytically literate.
Keep your questions coming. Send them to us at [email protected] or [email protected]. God bless!
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