The connected world is often portrayed through inspirational stories. Prime-time television commercials abound with amazing tales of connected cities and autonomous cars linked by graphics of glowing, flowing, fluorescent interconnected trails. We are watching science fiction come to life before our eyes.
Then there are the no less compelling, smaller scale examples of our increasingly connected world. Forget about toys and clothes. This year’s holiday shoppers are wooed with drool-worthy smart thermostats, lighting and even appliances to revolutionize domestic life.
With these as examples, it’s not surprising, however that the connected world can seem far removed from the day-to-day concerns of the vast majority of businesses. So what does the connected world mean for the rest of business?
Actually, quite a lot. It starts with rethinking one’s data environment. Inside most well-run businesses data is structured for the most part in rows and columns, akin to a massive spreadsheet that describes what is going on within the company. From mom-and-pop retailers to multinational corporations, tracking data in this format is common practice. This presentation is great at aggregation, telling one how things are doing.
The untapped opportunity in the connected world is to explore the connections, the previously hidden linkages, between the data to let one see how systems, devices, and people’s behavior are interconnected. Instead of traditional business intelligence charts and tables of aggregate information, it’s now possible to track, analyze and relate data as it emerges from a spider web’s network of connected sources, from sensors and other device information, to web clicks and customer contacts.
Connected data makes it possible to take formerly disparate tables of data and create a unified, coherent visualization of relationships and interdependencies that can then be used to drive decision-making. Consider these challenges:
- Telcos have long had massive amounts of data about their millions of customers: who they call, when they use service and for how long, when they seek support, when they visit the website, and more. There has also been data about customer satisfaction, amassed via call center reports, surveys, or even the impact of a news story. In the past, however, the fragmented, independent nature of those data sources meant that one had to pre-determine (ahem, make an educated guess) about which of those datasets were believed to have a relationship in order to run an analytic to impact churn.
- In the world of grocery stores, enticing a customer to buy a bottle of wine with a 5% margin, as opposed to a 2% margin, can have enormous, bottom-line implications. Big data has made it possible to collect large amounts of data on buying habits. But, when you have 60,000 items on your shelves and millions of transactions, identifying specific enticements to drive that higher margin purchase could be elusive. Armed with the traditional data, companies would still have to rely more on testing assumptions about connections between product A and product B than on readily visible data-driven insight.
- From banks to retail, it is a long-held belief that loss leaders, from free drinks to free checking accounts, drive long-term sales. But do they work? How does one validate the relationship pattern that starts with a free toaster and ends with a mortgage? Is there causality, indicative of developed loyalty, or is each stage of that customer’s journey simply in the moment an opportunism driven choice? Are you really attracting high value customers or people looking for freebies?
In each of these examples there is a barrier, a lack of connectedness that stands between great data and great insight. That’s the change that is here now. Business is retooling its approach to data consumption to embrace a connected world. In each of the examples above, new techniques such as graph analytics go beyond traditional data to look at the relationships between disparate data networks. What were formerly separate columns in a table, each presenting their own conclusion and requiring manual connectedness, is now portrayed as a dynamic visual representation of interdependencies that distinguish how a tweak that impacts the data coming out of one network relates to all the others. One does not have to anticipate the analytic—one can watch it develop and see what is happening.
The connected world does require a different way of thinking about data, networks and visualizations. The recently published “Relationships Matter: The Business Value of Connection Analytics” explores in detail how the connected world is driving that change in the examples given above as well as many others. I’d argue that for most decision makers, the story of how the connected world minimizes production downtime, streamlines compliance, or detects fraud is every bit as compelling as synchronized traffic lights and a warm home.
Karen Thomas is executive vice president of Americas Sales and Services, reporting to Vic Lund, president and CEO.
Karen is responsible for sales, solutions services and go-to-market transformation for the Americas region, which includes the U.S., Canada, the Caribbean and Latin America.
Karen has more than 25 years of experience in the areas of sales, consulting, finance, and information technology. Prior to this appointment, Karen was vice president and general manager of the Bay Area and California region. Previously, Karen held multiple roles at Teradata, including area vice president, U.S. Western Region, sales director for Canada and roles in finance, operations, marketing and customer service with Teradata Canada.
Karen holds an Honours Bachelor of Business Administration degree, from Wilfrid Laurier University in Waterloo, Ontario, Canada.