Today's Consumer: How Did We Get Here?
Note: Michael's guest this week is Ron Lunde, a consumer goods veteran who has held senior management positions with both food retailers and wholesalers. He was also a senior vice president at marketing agency Leo Burnett. Over the course of his career, Ron has been recognized as a thought leader in such areas as category management development and implementation, frequent-shopper marketing, and big data analytics.
Michael Forhez: Ron, sometimes change seems so incremental and then, all of a sudden, pow! This seems to be one of those times. Please enlighten us.
Ron Lunde: Consumers now live in a world of ubiquitous sensing —autonomous mobility, collaborative systems, cognitive computing and devices, infinite screens, mixed reality, diagnostic wearables and responsive homes. Many of us now inhabit a globalized “as it happens" world of tweets, text messages and on-demand video that demands instant personal gratification. It's just the way it is.
I spent most of my career in an era that believed there was a mass market, that all shoppers were equal and every shopper was a good shopper. In the late 1980s, my team at Price Chopper Supermarkets developed the first frequent shopper card program in the grocery retail space. The same basic model is still used today. What we found was that there was no mass market and that all shoppers were not equal and every shopper was not a good shopper. Shoppers were like snowflakes — they all appeared similar, but no two were exactly alike. Today, we know that every shopper is unique.
MF: I get it: Ubiquitous technology and computing begot today's "connected consumer." So they've changed and are now changing the rules of the retail game by wanting more of what they want vs. what has been mass-offered to them. What's the impact for brands and retailers?
RL: Today, retailers and brands live in a Darwinian era of unfixed reality. Strategy is mutable, as customers and circumstances always shift. How do we know this is true? Big data analytics. We create an estimated 2.5 quintillion bytes of data every day. It just happens! Some data analysts are suggesting that, by 2020, the digital universe will be 40 times larger than it is today — something along the order of 44 zettabytes —becoming even more complex as we begin to add unstructured data to our analytics and cognitive technologies.
To handle this deluge of big data, data scientists are creating a new technology, a revolution in statistical inference, machine learning and algorithmic iterations that some call "fast data." These new tools are velocity-oriented databases that can support real-time analytics and complex decision-making while continuing to process the frenetically increasing streams of available data. Shopper uniqueness is now discoverable and solutions are deliverable — in near-real time.
MF: That's a lot of information to process! I walk the corridors of big retail and meet top execs in consumer goods everyday, and what's at issue with big data is how to convert all that computing power into meaningful insight to drive tangible results. Beyond doubling down on data gathering for its own sake, what guidance can we offer?
RL: New tools mean new rules. Retailers and brands must answer simple questions: Where are we now? Where do we need to be next? What are we going to do? When are we going to do it? How are we going to do it? What is the ROI?
The questions are simple. The solutions, for some, are hard. What do you have to do to serve your consumers better than anyone else can serve them? First, you have to change your focus from product or format to the customer. As a brand, that means you can no longer sell what you make; you must make what you can sell. As a retailer, you can no longer sell what you bought; you must buy what you can sell.
The market rewards those — whether brick and mortar, e-commerce or omnichannel — that can use consumer-centric, predictive big data analytics to understand how product behavior, shopper characteristics, pricing techniques and market information can be used to strategic advantage. Data analytics today is near-real time, consumer-centric, predictive and requisite.
MF: Yes, change. Change is hard. A wise man recently reminded me that, to change we must change twice: we must first change how we see, then change what we do. We have a great big industry and business model that's served us ably for decades. But transformation is clearly needed. What's holding us back?
RL: What continues to surprise me is that so many brands and retailers continue to operate with different "siloed" divisions that often have uncoordinated goals, budgets and a predilection not to share insights or resources. Ultimately, management decisions must be based on one collective version of the truth. I recognize that enterprise success comes from different sources. I suggest that, today, the essence of an effective business strategy can be distilled and articulated in one principle: the enterprise-coordinated exploitation and implementation of big data analytics.
Change is hard! In our current era, the true test of change leadership is not what we know how to do, but rather how we perform when we don’t know what to do.
MF: It's a brave new world. Carpe diem. Hail the consumer!
