If you follow our blog and keep up on LatentView news, you know that we’re excited to be celebrating our 10th anniversary this month. This is the 2nd post of our 3 part blog series on how the analytics industry has evolved. In our previous post, we shared some details on LatentView’s creation and how far we’ve come over the course of a decade. Look out for our 3rd article on future trends. Now we’d like to take a broader look back at trends in data analytics over the past ten years and examine some of the industries that are benefitting from growth in the space.
Emerging Analytics
Back in 2006, analytics use was still an emerging concept. For most early adopter companies, the focus was on deriving value from existing internal company data and using that data to glean insight and improve resource usage, productivity, etc. Companies were interested in looking inwards and getting smarter about using the data they already collected. The conversations we have today about unstructured data and external data didn’t exist – it was all about getting smarter with using what was already on hand internally.
Even back then, marketing departments were leading the way with analytics usage. In fact, many of the questions they attempted to answer are still top of mind today: how do we acquire new customers? How do we retain customers? How do we promote business growth? In essence, the primary goals, concepts and usage of analytics haven’t changed over the past decade. What has changed is the amount of data available, the kind of data and analysis opportunities available and the diversity of data sources. Additionally, since 2006 the business world in general has developed a far more data-centric culture. Much has changed from the standpoint of organizational culture and structure as well as the general availability of talent. In 2006, few companies focused on recruiting data scientists; today demand is high and it’s become one of the more difficult positions to fill. Today’s companies are equipped with both the data and the talent to glean far more insight and use that insight intelligently.
Continued Evolution
Over the past three years the landscape has seen its biggest changes of the decade. Namely, analytics has gone mainstream. Industrial businesses – the likes of which never considered analytics ten years ago – have started adopting the tools. The early adopters in 2006 were consumer and services focused businesses. Even the newer age, digital focused businesses – the Twitters, Facebooks, Teslas of the world – are considered early analytics adopters. More recently, traditional, large scale businesses have started to think about analytics in a big way and use it to advance business options. Today, mainstream businesses like manufacturing and oil and gas companies are utilizing these tools in ways never considered before. These trends in data analytics have delivered a better understanding of data, enabling these companies to open up new revenue streams. Essentially, the information analytics has helped uncover has allowed these businesses to sell more than just products, but services as well. For example, imagine a manufacturer selling a scanning machine to a hospital. In today’s data and analytics market, the business transaction is no longer limited to selling the machine and walking away. Companies now have the ability to capture all kinds of data on usage and send it back to the manufacturer. This data then enables the manufacturer to predict machine failures and sell in annual maintenance contracts – a benefit for both the hospital, which reduces machine downtime, and the manufacturer, which ensures a steady revenue stream.
The benefits of today’s data and analytics tools extend beyond big ticket items. Another great example of how data collection can affect an industry as a whole comes from mobile phones. Mobile providers encourage their users to set up user IDs and profiles that enable them to gather great reams of user data. Using that data, providers and manufacturers can better understand usage to improve the next generation of an item and entice a user to upgrade products. They can also develop additional, complementary products to sell based on what they learn about usage. The automotive industry is another area that benefits from analytics advancements. Most new cars today essentially have on-board computers that collect massive amounts of data on drivers and how they use their cars. This data can tell manufacturers if there’s been an accident, how much freight trucks are hauling and much more, giving them more insight into product usage than ever before.
Data capture and analytics usage certainly have come a long way in ten years, and it’s interesting to look back on how trends in data analytics have affected the marketplace. As the Internet of Things expands further and our world becomes even more connected, we’ll see this space continue to evolve. Keep an eye on our blog for the final post in this mini-series: a look at what the future of analytics holds.
