Let's Make a Deal

In the 70’s there was a television game show called ‘Let’s Make a Deal’.  It was exactly what you’d expect from the 70’s.  The host would pick a contestant.  Say one worked at a farm implement manufacturer, who was from somewhere in Iowa. 

 The host would begin to negotiate when the contestant was on the verge of deciding…did they want to pick door number one, two or three?  Behind one was  new car and another had something like a 100 pounds of potato au gratin mix.  The contestant could also choose a smaller prize box that was certain to have something nice in it but of lesser value.  Say a portable FM radio (hey, it was the 70’s).  The risk was limited even more.  But so was the reward.

Oh, the high drama and dilemma of what to select or not to select.  The audience would attempt to help by screaming “PICK DOOR NUMBER 3!”  What did THEY know that the guy from Iowa didn’t? 

Everyone is engaged.  No one is thinking that like a casino, the odds are stacked against them, and they are all guessing.  But it doesn’t feel like they are guessing.  That’s what makes the show. 

 The guy from Iowa exhales. He has made his decision.

"Door Number Two, Monte.  That’s it.  That’s the one."

 Dang.  The consolation music is queued.  It’s not the Camaro.  Everyone groans.  But as the host points out,  it wasn’t 100 pounds of potato mix either.  That was behind Door Number One. 

 The guy from Iowa stares at what he had just won…a full set of brand-new camping equipment.  Not bad, but not the hot rod either.  .

 When you have imperfect information, perceived trends,  limited tools and a bunch of people telling you what they think they know or what they believe, what do you do?

 Today’s state of the art in product management or merchandising is full of data, just like the game show. .  Reams of data.  But data is like opinions.  Neither by themselves are facts.  Just representations of facts.  Facts come from the insights.  But how many of the insights in today’s CPG world are certain?  Or even mostly certain.

 The terms ‘Spray and Pray’ is still used for a reason.  Profiles are built based on past results.  Look-Alikes are generated.  Focus Groups, whose members are paid to give an influenced opinion are tapped, Prizm data is ingested.  Prototypes, test markets. Incentives, coupons, ad campaigns, merchandising, planograms, slotting fees, co-op dollars, listening engine data feeds, retail data samples, third party rolled up data feeds.  The list goes on.

 Sure, it all informs, but it all comes in across a period of 3 or so months and is, well, less than precise.  As a member of the brand’s cross functional team, you are no better off really than the guy from Iowa.  But it is what you have.  Given that, winning the consolation camping set prize seems like a good day. 

 The problem is, when you do some research across the CPG category, spending is going up as reported in 10-Q filings and market shares are slowly eroding.  Down 1-2% anymore is a win.  Preserve rather than grow.  The CPG game has gotten a lot harder.  Hitting the jackpot required to gain and keep market share is now as much luck as skill. 

 Mind you, the skill is supremely important.  Brand teams MUST have highly talented people with great instincts and insights.  Perfect insights without great team members is as useless as having the opposite.

 In the past few days, I’ve had a few conversations with some former colleagues.  A former global CPG brand president of Unilever, a CXO of Proctor & Gamble, the former US Chief Revenue Officer  of a top 3 alcoholic beverage conglomerate and the former CMO of one of the top 3 soft drink brands in the U.S. 

 I also asked them each the same question: 

“If existing systems could be enabled by AI to identify where optimal customers were, down to the ZIP codes, and exactly what conversion triggers were required for conversion and that conversion drove cost effective growth, what would keep you from doing it?”

 Here were their responses:

“Fear of being first.  But then later, fear of missing out and losing market share to the organization whose culture was more innovation and change oriented.  We’ve done this before and have paid high prices for those mistakes.”

“Fear of making a catastrophic, unknown mistake by relying on AI too heavily.  However, it we could control and manage that, nothing”

“The fear found in my teams who would tell me, “we already do that” when they in fact don’t and can’t”

 See a common theme?  Fear.  Fear of uncertainty or mistakes. 

 I asked each of them, their level of certainty of Artificial Intelligence MATERIALLY impacting CPG teams, either positive or negatively in the next 24 months.  Materially means changing at least 1/3 of how and what is done…how much harder or easier it gets and the associated results.  They all said the same thing: 

100%

 Seems like the old adage ‘change being the only constant’ is still true.  However, change, like luck, favors the prepared.

 The game is not over.  We are still in the early innings.  Find the appropriate place to start a small fire.  Try something.  Control it.  Be strategic.  Integrate it properly into your legacy systems.  Train to use it.  Then throw some gasoline on it.