It’s an exciting time to be in data management. It is one of the most rapidly-changing periods in the history of data management, particularly with innovations around Big Data and related solutions. Even more exciting than the technological transformation that is occurring, is the business transformation that is resulting from new opportunities available within data-centric technology. Data is becoming an economic and business driver, and a disruptive force in the market.
The concept of data driving business success is certainly not new. Organizations have been using data for years to gain an edge on the competition and to become more cost-effective and efficient. In the past, however, the focus was on making existing business processes more efficient, not necessarily creating new, innovative products or services directly based on the data itself.
Across a wide range of industries the shift is moving from being a data-driven company to becoming a data company. What’s the difference? A data-driven company uses information to gain strategic advantage in its current market. For example, a telecommunications company might build better marketing campaigns based on high quality customer data in order to gain a larger market share in its existing region. Making a shift to become a data company, that same telecommunications company realizes that the data itself is the highest valued product in their organization. While network availability is becoming a commodity, the usage data from the range of telecom customers is a valuable asset, whether it is from footfall analytics to help city planners better understand commuter travel patterns during rush hour or customer usage patterns of smart phone applications for new product development insights.
Monetization of information is of growing interest across a wide range of industries, as organizations are transforming their business models to become “data companies.” Internet applications and search engines have long seen the value of customer click-through data as an asset to marketing organizations. With the rise of Big Data usage across diverse sectors of the economy, we’re seeing the rise of data as a valuable economic commodity in its own right. Energy companies are seeing the value of Big Data for Smart Meters as a next-generation business model in the coming years. Smart Cars are of interest to multiple sectors from Insurance companies looking to understand the driving patterns of their customers in order to better personalize insurance rates, to product safety organizations looking to better understand the factors involved in traffic accidents, to auto manufacturers themselves who can not only better understand how customers use current products, but are innovating with new data-driven products such as driver-less automobiles. The list goes on, and the list is continually growing as new innovations arise in both the available technologies and the new business models that are possible as a result.
What does this mean for today’s data management professional? In terms of career possibilities and visibility within an organization, it’s never been better. But in order to capture the opportunities resulting from the rapidly-changing data environment, we must evolve our skills along with these changes. The most obvious skills are the technical ones, as staff who for example may be familiar only with relational databases look to expand their skillsets into the Big Data ecosystem and related technologies. Perhaps less obvious, but equally if not more important, is to expand business knowledge as well.
I feel honored to have had the opportunity in my career to speak with a number of high-level business leaders. A positive trend I am hearing from many such leaders is the realization that data is critical to the future growth opportunities of their organization. A common frustration of these leaders, however, is that they feel the lack of an IT team who can support their data-centric vision. Data-related skills are in short supply to the meet growing demand in the marketplace and that, of course, exacerbates the issue. But the larger issue is the communication gap between business people and data professionals. We as data management professionals often lament that business people don’t understand the complexity of our environment and the difficulty in solving key data challenges such as a “360 View of Customer.” If only the business better understood IT! But perhaps the gap could be solved by IT gaining a better understanding of the needs of the business, and helping to be a catalyst for change. More than ever, executives are looking for strong guidance and advice in ways to take advantage of new, innovative business models based on data, and IT is poised to have a seat at the table if we’re able to have a meaningful, informed dialogue.
One of the common tools we use in our practice is the Business Motivation Model. While the term “model” implies a technical artifact, done correctly it is more of a facilitation tool for better understanding the business drivers of an organization and brainstorming innovative ways to support these drivers. A starting point of the motivation model is the Mission and Vision statements of the organization. If you’re not familiar with the mission and vision for your organization, go looking for them. They are often readily available on the corporate website and/or on office billboards and posters. For example, the vision statement might be “To be the respected source of automotive products worldwide, creating an online community of auto enthusiasts.” While this is a short statement, it speaks volumes. For example, the corporate vision is towards online, digital sales. Data on customer shopping patterns should therefore be prioritized around online shopping, not transactions from brick-and-mortar stores. Online community is another part of the vision. How can we use data to better support this through efforts such as social media sentiment analysis and/or social relationship graph analysis? The corporate vision should drive and inform the IT vision and, ideally, there should be a feedback loop between the two groups as IT helps suggest ways to innovate based on technological advances.
A second part of the motivation are the external and internal drivers for change. For example, what are the factors outside the organization that are driving the stated vision? Are competitors moving towards online sales fueled by social community interactions? Are regulations driving the need for better audits? It’s valuable to step back and take a look outside your organization at the macro trends that are driving innovation and change. On a similar note, what are the internal drivers? Is cost the main concern? Or is the need for innovation in order to be competitive a larger driver? Take a look around the wider organization in order to see what the main priorities are.
These internal and external drivers, coupled with the corporate mission and vision, should inform and drive the goals and objectives for your data-centric projects. For example, with the push for online shopping, the mainframe application supporting the brick-and-mortar retail stores may need to move down on the priority list. Priorities should also be made around the data itself, in addition to the applications and technologies that support the data. What are the key data elements that support the business vision? For example, Customer and Product data would be key to the online shopping experience, whereas Store Location data would be of lesser importance. A conceptual data model and associated business glossary is a helpful tool in the prioritization of business elements. Once defined, focus efforts of governance, quality, and data augmentation around these elements as a first priority. Time and budgets are limited in every organization, so it’s key to focus around the data that matters most.
Once you’ve prioritized your projects around those with the highest value to support the organization’s goals, take some time to think of how you’ll describe these projects to a businessperson. It’s helpful to take some hints from the sales and marketing teams—what is the “elevator pitch” that sums up your project in a clear, actionable way if you were to speak to the CEO in the elevator on your way to the 5th floor? Use words that would both pique the interest and make sense to the CEO. For example, “I’m building an application to better understand customer buying patterns for the new online shopping portal so that we can help drive sales of new motorcycle accessories.” It’s not enough to build a project that supports the corporate objectives—you need to let the organization know about your efforts as well. Many of us in IT are shy about promoting our efforts, but it’s important to do so in order to be properly recognized. Once the business staff can better understand the relationship of IT’s efforts to support their business objectives, the dialogue becomes more of a conversation. The goal is to nurture a two-way exchange of ideas. A data professional that understands both technology, as well as the business drivers and opportunities, is well-placed to have a seat at the table in senior-level discussions. Business leaders are eager to understand how technology can help them, provided it’s relevant to their business goals and explained in a clear, intuitive way.
It is a period of great opportunity in the data management community, and a time where many of us can benefit from taking a step back and looking at our roles in a new way. How can we be a voice of growth and transformation in the organization? How can we use our in-depth knowledge of the organization’s data in a way that can transform and benefit the long-term vision? It may be a combination of learning new technical skills, new business understanding, and/or simply explaining our existing efforts in a more relevant, intuitive way. Whichever it is for you, enjoy the journey as you become a catalyst for innovation and success in your organization.