In 1917, Nikola Tesla, one of history’s great innovators, was awarded the Edison Medal. During his acceptance speech, he revealed the secret to his success: “a new method of materializing inventive concepts and ideas.” By constructing a new idea in his mind and considering calculated iterations before generating a final product, he was able to avoid losing steam and preserve the integrity of the original idea.
“ALMOST ANY SUBJECT PRESENTED CAN BE MATHEMATICALLY TREATED AND THE EFFECTS CALCULATED…” – NIKOLA TESLA
Today, thanks to the evolution of technology, there’s no need to use our minds to run these projections. Machine learning and simulators can help manufacturers in the fast-moving consumer goods (FMCG) industry achieve what Tesla discovered more than 100 years ago. By applying this process of predictive research, successful innovations can be realized without the sacrifice of quality and time.
These are precisely the elements at stake when a product or marketing plan is launched before being truly ready, later demanding course correction. Yet in the current FMCG landscape, where manufacturers are pressured to be more agile in order to achieve growth, quality is sacrificed for speed in the name of being “agile.” So while beta testing in market—when a product is launched in a live setting and only then improved upon and iterated, based on initial launch feedback—is one of several common approaches responding to the call to be more agile, it presents risks.
In previous research, we concluded that it’s the combination of being faster and smarter that ultimately improves the chances of success. Agile market research should help you prototype your ideas in a safe environment and enable you to identify the best possible version of each prototype before you invest in more expensive execution steps. And the concept of predictive research as an agility enabler can increase your chances of success by 3x.
DON’T THINK MINIMUM VIABLE PRODUCTS: THINK MINIMUM SUSTAINABLE PRODUCTS
The temptation to run to market with a new product is almost too great to overcome. Crossing the finish line to get on the shelf and in the hands of today’s digitally enabled consumer may feel like a rush of victory. Not to mention it can remove the pressure from the top to launch more products quickly, with an ever decreasing budget. So what could go wrong?
Through our research, we’ve identified two primary risks that come with launching an initiative using a trial-and-error or “see what sticks,” iterate-in-market approach. Firstly, this method can mistakenly weed out potential winners prematurely and, secondly, increase the likelihood of placing a stake in potential losers or distractors.
After reviewing distribution data across more than 3,000 recent launches in several markets, we found it takes an innovation an average of six months before it shows its true destiny as either a grower or a decliner. Before that, a product’s chance of success is relatively indistinguishable without the right benchmark. So those manufacturers that rush a product to market and then jump in to “rescue” it (or iterate) before the sixth month mark can’t be sure that the product was truly in need of help.
In fact, by going back to the drawing board six months in, they’re adding to the timeline. Realistically, in the time it takes to launch, correct and relaunch a product, it’s likely been a full nine months of waiting, added cost and lost opportunity. For many, the most likely outcome is even more dire: the product has been slated for delisting after irking a preferred retailer. Over time, this pattern could incur irreversible damage to a crucial relationship.
In software development, agile means pushing a minimum viable product to a device upfront. But the cost for the tech industry is typically minimal: an app may have bugs that require updates, but these can easily be sent as they’re developed in subsequent sprints. In contrast, a shaky product on-shelf will not garner nearly as much forgiveness from consumers. Launching a minimally viable product may be acceptable in the tech world, but the effects are drastically different when applied to FMCG. Manufacturers who take this approach face the risk of:
A very low rate of endurance, or longevity in the marketplace, by launching suboptimal products; and
An expedited decline in the rate consumers repeat their purchases.
For physical products like food and beverages that consumers take home to give to their families, what’s really needed is a minimum sustainable product: something that they can be counted on to purchase again and again, in its current state.
The reality is that barely 5% of products with poor experience for consumers endure past their first year. Once in store, a snack cannot—and should not—be beta-tested as if it were an app.
Failing fast once in-market may seem appealing, but the long-term consequences mitigate perceived benefits: cost savings are negated by the need for re-work, and opportunities are lost to learn more about the category early on.
And even if those poor-performing products are adjusted after they’re in market, the online reviews from the consumers who bought the first product aren’t going to disappear.
In short, your product is not the place to simulate and experiment once in stores. By using predictive research prior to launch, paired with a good simulation of marketing support scenarios to boost sales, you will spend less time waiting to see if the product succeeds and trying to apply quick—expensive—fixes.
THE TRUTH ABOUT TRANSFERRING CONCEPTS
In the process of bringing new products to market quickly, manufacturers frequently apply an approach whereby a favorable idea is “lifted” from its global or regional home and then “shifted” and applied directly to other markets, with little refinement. While this may seem like an easy win, research has found that consistent interest for a concept across multiple countries is rare.
The reason for this is that consumer tastes and preferences differ across markets, as do competitive landscapes and market development. In fact, performance typically will match around 20% of the time. Basing launch decisions on one country’s success with the hope that performance is transferable could result in a 20-25% drop in volume potential. And this could be the difference between staying on shelf or being delisted.
At the same time, when action standards are not met in one country, this doesn’t necessarily translate to a failure in another. Therefore, careful planning and considerations are necessary. Manufacturers looking to release a new product in multiple countries shouldn’t try to cut corners on testing across regions by selecting one single market to use as a surrogate prior to launch. Instead, they need to ensure testing is focused on the countries scheduled for the launch.
HITTING HOME THE FIRST TIME
Rather than engaging in risky launch behaviors, a true agile approach is available in a “fail-safe” simulated test environment, fuelled by technology. Simulated test markets can isolate variables in an environment created for that purpose alone. Through this process, it becomes possible to quantify the impact of changes, uncover hidden risks and areas for improvement, and finally unlock the potential to have the best idea, concept and product to take to market from the start.
Learn fast: Machine learning can quickly test thousands of ideas, identifying the best.
Fail safe: Isolate individual proposition changes before launch; adjust prototypes early on
Forecast: Marketing plans can be refined with precision when analyzed properly
Plan: Consider global optimization early on, allowing for local market refinement
This is also true when considering marketing spend. Marketing allocation plans, and the forecasts run from them, are instrumental in determining whether the level of support is indeed enough to keep a product afloat. Bypassing these calculations can lead to a potentially great product missing expectations.
By conducting a simulated sales forecast using several marketing plan scenarios, the result provides enough accuracy and confidence before launch to eliminate uncertainty. To put it simply, it’s choosing the option to save on frustration and move forward with confidence.
INNOVATING IN AN AGILE WAY FOR SPEED AND EFFICIENCY
When thinking of the word agile, the word efficiency should resonate, and not just speed. Efficiency only happens when you trust the direction you are taking when in a rush.
Nikola Tesla perfected his ideas by simulating scenarios in his mind and releasing a solution in a single effort. Conversely, one of his chief rivals, Thomas Edison, failed across several real world trials until finding the right solution. Both are inspiring, but which one do you think is more efficient? The good news is that, using the right technology and research methodology, you can test out your innovations several times like Edison, but in a safer and more controlled environment, while also succeeding to efficiently create a single final version of your product like Tesla.
Written By Erin Dowd, Innovation Partner, Nielsen, and Lynn Quinlan, Manager, Innovation, Nielsen
