The concept and use of “Digital Twins” technology is rapidly gaining momentum as a viable and productive alternative to product and process design and development. It’s potential for trade promotion planning, management and execution is wide open.
Simulated environments have been around for a long time. In fact, NASA’s Houston teams simulating the problem that occurred on Apollo 13 saved the lives of three courageous Astronauts. In manufacturing environments, we have built scale models and used them to flush out issues with design and to identify performance problems.
The concept of digital twins is just that—a simulated duplicate subject against which you can test and validate the design specifications, and experiment with a variety of performance criteria without having the build and destroy the equipment every time—except, in totally digital environments.
Most people can clearly visualize a digital twin environment such as the example here with a turbojet engine. With the advanced graphics and artificial intelligence we have now, being able to replicate a full piece of equipment and actually run it in simulated performance, opens up an incredible new world of design and development across every product category and industry—especially consumer goods.
And especially in trade promotion planning and execution.
In my book, “The Invisible Economy of Consumer Engagement,” I have included several examples of how a consumer products company moves through the various stages of technology and process evolution to end up with the ability to effectively prescribe a particular promotion with confidence that it will produce the desired end effect, whether it is a higher ROI, moving clearance products, or establishing a new product.
In the book, I presented a step process of development of internal capabilities that combine technology with process and advanced data management to create a powerful foundation of accuracy and trust in future outcomes. 
It further expands collaborative planning to involve all the key stakeholders from sales, marketing, and the customer teams to leverage the array of talent, technology, and data that produces the highest outcome possible.
You’ve no doubt seen the myriad of charts and “building blocks” to achieve TPx stardom, but I boiled it down to what I call the four “Dimensions of Knowledge.” Essentially, it takes a whole bunch of steps and consolidates them into logical levels of capability that are a bit easier to define and on which to measure attainment.
Most CPG companies are squarely on the “Foundational Track,” with more pioneering and technically innovative companies hitting the “Optimized” level on some degree, certainly not fully at this point.
Prescriptive is the ability to have enough solid and trustworthy data and intelligence to effectively prescribe all of the promotional mechanics, timing, product grouping, and market environment to have a confident and consistent level of promotional performance—enough to be in a position to prove it with results, every time.
It’s safe to say everyone is pointing to that level of attainment, but nobody has yet hit it.
The fourth level is “Engaged,” which goes beyond confidence in near-100% ROI target-producing promotions and adds the dimension of consumer engagement at a super high rate. It is being able to know and leverage what the consumer needs and what they will (and will likely NOT do) in every situation, enabling promotion planning to be driven off those key consumer need and purchase behaviors with a similar near-100% outcome achievement. 
This is going to take a very long time to achieve, but it is gratifying to see so many consumer products companies taking real steps and actions to get the foundations in place with data and advanced AI/Machine Learning technology.
Here is where digital twins come into play with trade promotion.
Like the turbojet engine simulations that are able to digitally reproduce everything from temperatures to flocks of geese flying into the cowling during flight, TPx can also benefit from digital simulations for virtually any consumer, channel and market event we can name. Here’s one:
How will Covid impact supply chains?
We should create a digital twin of the conditions we have experienced, load it up with even more outlandish potentials (which no longer seem to be so outlandish these days) and give it a go. Once we have run these simulations against all known variants and environments, continue until there is a “digital consensus” that the result will likely happen. That is oversimplifying, I know, but what makes digital twins work is a combination of the right data, historical performance, and a total understanding and clear picture of the potential environmental impacts.
In other words, for TPx, it means knowing what the consumer will and will not do in every situation you can think of.
The consumer action is the key. We, as a consumer product industry, really do not have a solid set of historical data objects from which we can effectively operate a digital twin. Some of you are getting there, to be sure, but it is going to be a lengthy process.
To understand the consumer is the key here. Trade promotion management and execution has always been more about short term promotions and immediate achievement of volume sales, but that perspective too is changing. Hats off to those consumer products companies who are now incorporating the metrics of promotion success into their sales teams’ compensation. This is a good start—focusing on the REAL reason we do this—to incite consumers to buy our products.
Right?
A digital twin can be created to simulate the various dimensions of the consumer’s decision cycle from identifying through the purchase, consumption and opinion of the product and every potential environmental scenario known. Each scenario can be applied, measured, and tested against real performance. As each component of these dimensions are added in, the model learns and accommodates, adapting to changing conditions, criteria, and stimuli. One such stimuli is, of course, the nature of the promotional offer.
Today, we drive the promotion plan based on two things: (1) Need to generate volume and achieve forecast, and (2) to incite the customer to buy. Most TPx stakeholders tend to believe that more emphasis has historically been put on the first purpose than the second one. But if there is one thing Covid-19 has taught us is that environmental forces have far more impact on our buying habits and supply chain than we have thought.
So, what is the difference between the efforts consumer products companies are making now to achieve predictive promotion planning superiority versus digital twins?
The answer lies in the heavy volumes required to make digital twins work. I have always heard CIO’s say, “We have tons of data, but we need advanced technology to help us leverage that data.”
To make the digital twin work requires more data than what we capture now, and that is most likely the reason why even the innovative leaders in consumer products have difficulty articulating ways to achieve this level of near-100% ROI in trade promotions.
But what we also know is that this new technology can indeed leverage petabytes of data that can be assembled in one database from which we can begin to compare realistic scenarios with real, trustworthy, and precise data to build the number of scenario arrays and conditions that will help to create this consistency and trust.
Some of the more advanced consumer products companies are beginning to collect, store and effectively leverage larger streams of quality data, but we have only scratched the surface of being able to confidently prescribe and execute promotions that do what we want them to do. Creating the digital twin framework will establish a very specific set of conditions that can be manipulated, cross-checked, and continually tweaked to deliver trusted results. When it does, we can save and rerun those scenarios over again, with the ability to sprinkle in new environmental conditions, market impact, weather, and even political events to catalog and store full scenarios into the memory banks that AI and machine learning can take advantage of.
Today’s digital twins may be more applicable to heavy industry, but I am betting that consumer products teams outside the halls of research, design and testing will begin to see the value.
Rob Hand is the CEO of Hand Promotion Management, LLC, and the author of the new book, “The Invisible Economy of Consumer Engagement.” He is a leading consultant in the area of consumer promotion, focusing on trade channel promotion, co-op advertising and channel marketing across all consumer industry sectors. He is based in the Austin, TX area.
