Anyone in a strategic role will tell you that the complexity of business strategy has skyrocketed over the last decade. Competition is a big part of that complexity. New business models, new tools and new methodologies have ushered in an era of competition on a scale that wasn’t possible 20 years ago.
For many businesses in competitive markets, the foundation of strategy has shifted from pure experience to experience enabled by advanced analytics. The increase in strategic capabilities that this shift brings is significant. Strategy teams can successfully navigate unfamiliar situations with the right data driven insights.
With a solid predictive regime, competitors’ moves become more transparent and the best responses are more obvious.
Disruptions are discovered before they hit rather than after their damage is done. Risks and mitigation strategies are easier to identify making strategy planning more certain. Opportunities beyond the obvious are exposed by advanced analytics.
These capabilities are intimidating for businesses considering getting into the ring with a data driven competitor. While the advantage is significant, it is not insurmountable. I’ve built advanced analytic capabilities for both startups and for the Fortune 100. That work has given me perspective on not only what’s out there, but also how it’s leveraged for business strategy. If you’re taking on a data driven competitor, here’s what you need to know:
Businesses are constantly revealing competitive intelligence unintentionally. Data driven businesses are eating that information up and turning it into actionable insights about their competitors. What can a competitor get from publicly available information?
Here is an example of how this happens from my own business. We have a policy of not displaying our clients’ names until years after the engagement is over. Why? We’re a niched consulting company. If you see our name it means the client is working on predictive, data science and machine learning capabilities. The changes associated with those capabilities are well known and competitors of our clients are better prepared to compete knowing that the change in strategy is coming.
The difference between businesses that control their information footprint and those that don’t is obvious. If you look at a Macy’s media release, they are very well crafted. They are concise and maintain focus on their primary communication objectives without inadvertently communicating anything outside those objectives. Now look at a Nordstrom’s release. They are well written but often stray from their primary communication objects or are highly repetitive. Both of those are clues that a competitor’s algorithm can use to start digging for a pattern.
Another example of unknowing leakage of competitive intelligence - Last summer the new owner of Saks Fifth Avenue said they planned to spend $40 million on digital. He preempted their main PR push for that new strategy by over 3 months. He basically told their competitors, “Guess what we’re planning for next quarter?” - giving them time to prepare for a strategy change in the works.
In order to compete against data driven businesses, a disciplined information release process is crucial.
Balancing the need to keep investors and customers informed with the need to keep competitors in the dark requires focus. From job postings to press releases to social media, businesses need to be sure that their communications don’t leave their strategy exposed.
Before stepping into the ring with a data driven business, ask yourself three questions:
Once the information flowing out of a business is under control, it’s time to take control of what comes into the business. That doesn’t start with Big Data. It starts with big decisions. Non-data driven businesses make their decisions based on incomplete information. That’s often the case because there’s no viable alternative. The ‘3 Rights’ are focused on changing that reality.
The first question starts the process of understanding how the business currently makes decisions. Strategy planning revolves around decision-outcome pairs. Outcomes are goals and decisions are the means to achieve those goals. When framed in that context, it’s reasonable to say, “A business wants to make the decision which is most likely to result in the stated goal.” With incomplete information the probability of making the decision most likely to achieve that goal drops significantly, especially in groups.
Analytics combats that problem. The right insights help leaders make more informed decisions that lead to better outcomes. However, analytics delivered too soon or too late in the decision making process can lead to problems as well, which leads us to question 2.
Analytics too soon can lead to paralysis by analysis. Analytics too late in the decision making process leads to second guessing and a lack of confidence in subsequent decisions; “What happens if we make this decision and later find out we missed something? Should we put it off?”
Delivering insights at the right point in the planning process is just as important as the insight itself.
The 3rd question is the obvious, tactical one. Now that the business understands what it doesn’t know, it’s easier to look for data that fills in the gaps. An important piece of that process is data quality. If leadership doesn’t trust the data, insights and timing are meaningless. No one will act on them.
Another important piece is the Big Data and data science component. Don’t worry about going all in on highly complex algorithms, the latest software or massive datasets.
If the business has access to talented data scientists, they can turn even normal sized datasets into actionable insights. If the business has access to large datasets, the algorithm complexity has diminishing returns. If the business’s IT infrastructure is mature, let them handle a lot of the heavy lifting using commercially available software tools and their expertise.
Create analytics capabilities that play to the business’s strengths while avoiding weaknesses. Don’t fall into the trap of trying to build a core competency that’s beyond the need or reach of the business.
The biggest advantage that a data driven business can exploit is the inability of its competitors to make good decisions over the long run. Data driven businesses can sit back and wait for their competitors to shoot themselves in the foot which is what inevitably happens when making decisions with uncertainty. The ‘3 Rights’ focus on leveling the playing field by helping a company make decisions with more certain outcomes.
The first two pieces get a business ready to step into the ring and not get KO’ed in the first few rounds. Now that it’s no longer a Tyson fight, the business needs a knockout punch of its own. In business strategy, that has always started with the talent and creativity of its people. There are numerous examples of innovative startups that challenge data driven businesses. However, data driven is a sustainable advantage while innovation on its own is not. Making better decisions beats making inconsistent decisions in the long term, even if one or two have amazingly positive outcomes. Rita Gunther McGrath writes an exceptional proof for innovation, among other things, becoming a transient rather than sustainable competitive advantage.
That is unless the business can sustain its creative bursts.
Google is a great example of combining data driven with creative talent and experience. Creativity is encouraged throughout the company. Unlike most startups, Google has a more controlled approach to the creative process. The company uses data to direct creativity in ways that are most likely to benefit the company. Google also validates the creative direction using data. They evaluate innovations to see which ones are most likely to result in high quality outcomes for the business. With this approach, a search and marketing company is able to see the value of everything from drones to open source contributions to self-driving cars.
As with many strategies, the flaw in data driven is also its greatest strength. Data driven alone is very consistent. People are exceptionally good at making leaps and that’s the Achilles Heel of data driven; a competitor which rides from one innovative, transient competitive advantage to the next without being wrong very often. This is the underlying principal behind data driven business models.
Building this capability puts a business in a class with Disney and Google.
A big part of the change is cultural. Having creatives and data driven personalities working together requires both to see the value of the other’s contribution. Each needs to understand when data leads and when creativity leads the process. Building trust in data, creativity and experience across the organization is a reason why Disney and Google are such successful companies not only financially, but also as an employer of choice.
As I said at the beginning, strategy is complex and a big part of that complexity is competing with a data driven business. These businesses operate with relative strategic certainty and a high level of focus on positive outcomes. Competing with data driven companies is a combination of mitigating weaknesses while focusing on strengths, just as ‘competition’ always has been.
Data is a disruption to those businesses who can’t leverage it and a significant advantage to those who can. However, talent and creativity are still the most powerful advantages a business has over its rivals. In a data driven competitive landscape, how creativity and talent is leveraged changes.
The third pillar, insights, make what people bring to the table more effective and focused. Combining all three is critical to successfully competing with a data driven business.