Democratizing Analytics: What Matters Most in Today’s Solutions
In our eyes, “Democratizing Analytics” means building and marketing technology that is (1) easy to use, (2) accessible, (3) full of actionable insights and (4) inexpensive. These four pillars, when united, will result in the expansive use of analytics across a wide variety of settings.
“Easy to use” is, apparently, a very elusive goal—even today. Despite aesthetic updates over the past few years, both established and recent entries into the analytics space are still (put simply) quite baffling. From day one, we knew that even the most revolutionary platform would only make a difference if it was geared for use by anyone and everyone.
For a product to be accessible, we mean that all users in an organization—from data scientists to product engineers and business analysts—should be able to quickly familiarize themselves with the software and enjoy its use. Simultaneously, this means that all software should permit not only individual access, but also group access.
This notion also requires that a product must be available for use through the platforms that customers use every day—especially mobile devices and tablets, such as the Apple iPad. This means not merely displaying data or dashboards, but allowing for data analytics and interactive visualizations that are truly available on-the-go.
Within this democratic movement, three groups of users are direct beneficiaries:
This burgeoning user group is typically highly educated, technology and business savvy and (increasingly) tasked to conquer big data and analytics challenges. This group’s analytical needs, as examples, include: instrumenting applications for the corporate website and collecting data; understanding and analyzing various traditional business data relative to social; or creating data-driven apps to better understand mobile customers. Building accessible tools to deal with their data needs—especially interactive interfaces—is key. (It is also a necessary condition for underlying technologies, especially Hadoop, to achieve widespread adoption.)
Group Three: Data Scientists and Software Engineers
These “kings” of the big data and analytics mountain serve various constituencies from groups one and two who are demanding “more insights into their data with faster turnaround.” Data scientists and software engineers are trying to get the most out of their current tools (some big commercial solutions, some home-grown products and some open source projects) to be more productive. Their need for accessibility is two-fold: more data (partially an IT solution and partially a programming solution) and better tools.
Democratizing analytics does not begin and end with putting sophisticated statistical and mathematical software into the hands of scientists; instead, it’s an approach that aims to yield intuitive, easily interpreted resources for the decision makers that need them most. To get there, we’re focusing on superior user experiences, stronger analytics and significantly lower costs.
Is price really an issue holding back widespread adoption, or is it rather value derived for the price? Customer’s always *want* lower prices, but when the value derived is high enough, they’ll support (marginally) higher prices, right? (Look who I’m asking, I mean, you guys have data to confirm or refute this, no?
I’d offer value derived is a combination of your 1st & 3rd pillars, and the question at large is (at least for the “Executive” cohort) “are my tools easy to glean actionable insights from, at the right place & time to fully utilize them”. Achieving this IMHO, is far less often about the tools’ UX needing improvement (at least where web analytics tools are concerned) but rather, analysts/users needing a better framework/foundation/context for . One such example model would be Avinash Kaushik’s “acquisition, behavior & outcomes” though others certainly exist.
A final point regarding accessibility- a question I ponder is do all organizations *want* org-wide access/sharing to/of metrics? They should, but at times I suspect cultural reasons more than technical ones preclude the flow of information.
Really interesting to see your perspective. Thanks for sharing with the audience at large.