We’ve all heard of the North Star.
But in the business world, the North Star is something different. It’s the single concept that guides companies and over the years it keeps businesses on the path to fulfill their mission, whatever it may be. Staying on the path in today’s complex business ecosystem is not easy, but it is vital. This is why this star is so vital. It has even been said that following your North Star is the single largest driver of sustainable long-term growth in business today.
Here’s why. A powerful North Star can motivate thousands of people in an organization whose day-to-day actions need to align with the greater mission of the company. For many companies on the digital transformation journey today – Hitachi Vantara included – our North Star can be summed up in three words: return on data.
Data is the new intellectual capital and, after employees, is a company’s most valuable asset. Big data and analytics have transformed data from a by-product to an opportunity to increase revenue. The trick is to get the right data into the hands of the data-driven innovators—those people in your organization who can use data to better understand your market, your products and how to create more revenue through data-enabled products.
In many companies, data-driven innovators spend the majority of their time trying to find the data, accessing the information from silos and deriving insights. We all know that’s expensive in terms of resources and missed opportunities. So, amplifying your return on data is crucial. You need to put under management the maximum amount of data possible and do so at the lowest cost possible. Once that’s done, get it into the hands of as many data-driven innovators as possible. My colleague Bill Schmarzo writes about this concept extensively in the paper, Applying the Economic Concepts to Big Data.
Bringing data under management to eliminate silos, expediting insights and getting data-driven innovators what they need quickly isn’t easy. Let’s look at what I call the three-point approach to maximizing return on data.
1. Take the cost out of infrastructure: Traditionally, IT has allowed companies to save by driving more efficiency in processes. With new architectural disruptions such as the internet of things (IoT), companies can extend those efficiencies into new areas such as predictive and diagnostic analytics. While that extends cost savings, it doesn’t necessarily address the “take the cost out” part of the equation. To do that, companies need to look at making their IT infrastructure more automated so the costs of driving insights into the business go down as well.
The logical question at this point is the “how.” How can you bring this automation into your business? The answer is advanced analytics, artificial intelligence (AI) and machine learning. By applying these emerging technologies to your data, teams can gain more insights into the internal functioning of their business at a lower cost than was previously possible. And with AIOps (AI-enabled operations), they can operate with more data in their IT infrastructure for much less money. (For more on AIOps, check out a recent blog from Hitachi Vantara CIO Renee McKaskle.) Spending less to manage this data allows businesses to get much more data under management. And the more data you have under management, the more value you can drive to your organization.
2. Rationalize data management so you can focus on innovation: The biggest hurdle to innovating with data has always been breaking down internal silos to get access to the data, whether the silos are technical (architectural) or organizational (departmental). A company’s data is controlled by the investments it has made in its infrastructure. Since these are typically department-led investments, businesses often end up with many little pockets of data, which makes it impossible to get the big picture.
By rationalizing data management, businesses can bring a companywide strategy to all of their data, allowing teams to link each piece from across the value chain. With the flexible consumption models and managed services available today, companies can free up innovators to focus on what’s most important – innovating.
3. Innovate with data: AIOps and automating infrastructure help get the data needed and at a lower cost, but they don’t help with this final step: innovating. Innovation comes from the people. Only when you have as much data under management as possible and make it accessible, can a business start to realize an optimal return on data.
It’s at this point that innovators can begin to focus on better understanding of customers, product pricing, how equipment is operating, how to better maintain that equipment and much more. They can even apply advanced data science techniques to the data. And they can use its accessibility to find ways to create more revenue through data-enabled or even completely data-driven products. With this agile, automated back-office infrastructure, there is also an opportunity to find new ways to drive value to existing customers and to new customers in adjacent markets, further accelerating the return on data.
By using these three strategies to maximize return on data, businesses will free their data-driven innovators to take advantage of the tremendous value produced by the stream of data coming into the organization. In my next blog, I’ll build on this three-point approach by introducing the Hitachi Vantara Data Stairway to Value, a framework for success that can help you achieve data value at every step to accomplish the highest return on data.