Competitive advantage through data analytics

As data is fluid and ever-changing, the competitive advantages that it can bring need to be continually worked on. Organizations who have set up a data analytics infrastructure have the ability to keep on top of these changes but on its own, this simply isn’t enough. The ability to adapt, pivot, and target identified changes are important criteria when looking for a data-driven competitive advantage.

When thinking about extracting maximum value from data by using data analytics to provide a competitive advantage, we can ask questions such as:

• Are we able to convert insights from data analytics into our product or service features?
• How easy is it for competitors to replicate these features?
• How quickly will the insights we’ve gained lose relevance due to rapidly changing variables?
• Do we have unique data assets? If not, do we have assets that can be better utilized in alignment with our strategy than our competitors?
• Are we better placed to take advantage of these data assets due to our more advanced data analytics capability?
• Are we thinking about our data analytics in a way that allows us to drive new insights and value propositions?

To remain competitive, organizations will need to adopt data-led capabilities and practices, using the data analytics infrastructure. As John Behrens sees it, applying data analytics capabilities and practices is essential for a competitive advantage.

An example of competitive advantage through data analytics is Google Maps. Many design features of the Google Maps interface can be easily replicated, but a key part of Google Maps’ value is its ability to predict traffic and recommend optimal routes. Google has the data analytics capacity to take advantage of the constantly updating data-sets. This data is constantly updating, becoming obsolete within minutes, and therefore much harder to replicate. Google Maps’ rivals don’t have the real time data flow to compete with it.

Sustaining competitive advantage with data analytics

When your competitors are also using data analytics, it’s relatively easy for them to duplicate your capabilities, unlike factors such as geography, high entry barriers or tariffs. This means that the competitive advantages brought by data is a continual exercise.

Here are a few practices you can use to sustain your advantage:

• Prepare and train your business teams. An excellent data team with high quality insights are ineffective if your business teams and processes are unable to execute the changes that need to happen.
• Be open to new techniques and tools. Considered experimentation could provide the breakthrough you’re looking for. Such a strategy can provide for an exciting and possibly fast-growing business, but generally few companies are able to execute it.
• Invest in talent. The success of this strategy relies on a highly effective data science team. As a growing but still relatively young discipline, there are big variances between talent, with the best data scientists being much more valuable than the average. If you have a great team, you may be confident that you can keep ahead of the competition.
• Invest in obtaining quality data over quantity of data. The ability to derive any competitive advantage through data analytics relies on having both the right data and reliable data. If the value you get from your data depreciates faster than you can use it or implement changes, then you’re going to find it difficult to gain any competitive advantage, no matter how much data you happen to have.

Now that we’ve gained and sustained our competitive advantage, we can start to look to the future and think about innovation.

In fact, innovation is one of the ways we gain a competitive advantage. Once again this is an area where, if we’ve put in the hard work, we can reap the rewards of being data-led.

In the next video interview, we’ll explain how data analytics can create opportunities for innovation.