Consumerized analytics applications are everywhere, but their presence isn’t obvious. Managing this phenomenon at the executive level isn’t easy. People are always looking for the silver bullet, the single solution. It can’t all be known. Or, put another way, if it can all be known then it’s not changing, not evolving, not transforming. Enterprising analytics To be “enterprising” is to be eager to undertake or prompt to attempt. To show initiative and be resourceful. These are leadership traits, so to be enterprising is to lead. “Analytics” is how we use data to inform decision-making, in the context of achieving business objectives. These are management practices, so analytics is about management. “Enterprising Analytics” is about being creative, resourceful and adventurous with decision-making to achieve business objectives. It is about the set of leadership and management practices that need to be in place for an organization to make the most of its analytics investment. Left unmanaged, analytics can shake an organization apart Consumerized analytics applications are everywhere, but their presence isn’t obvious, just as it isn’t obvious which species has the largest collective global biomass. The strategic CxO knows that smart providers are making good, easy-to-use tools available for employees who just want to get on with things. And because these people are, generally speaking, acting in the general interests of the enterprise, she doesn’t want to get in their way too much. After all, when people sidestep rules in the pursuit of business objectives it’s as much a failing of management as anything else. SUBSCRIBE TO OUR NEWSLETTER From our editors straight to your inbox Get started by entering your email address below. Please enter a valid email address Subscribe Basic analytics packages are getting baked into pretty much everything. With the growth in awareness of the potential for the internet of things, analytics capabilities are becoming ubiquitous. The easy availability of cloud-based analytics packages is being fed by a growing industry of startups targeting unmet demand within specialist business units. The steady rise in professionals with foundational data science capabilities increases the indirect influence of analytics within the boundaries of the enterprise. Managing this phenomenon at the executive level isn’t easy. Left unresolved, the tensions associated with different parts of the enterprise using analytics to amplify performance in pursuit of business objectives can shake an enterprise apart. The challenge for the strategic CxO is similar to that faced by Spain in its efforts to remain integrated. Like Spain, the strategic CxO can’t simply ignore the demands of customer-facing business units to have their own analytics capability. Like Spain, she can’t just turn a blind eye to what’s occurring in the rest of the industry. The enterprise is a social construct and changes as society changes. Or should if it wants to prosper. The enterprise is a complex adaptive system One of the conceits that the strategic CxO is wary of are promises of the one ring to rule them all. And there are many such promises being made. People are always looking for the silver bullet, the single solution. Peter Drucker wrote about this in 1999 book Management Challenges for the 21st Century when he talked about the belief that there is or must be one “right“ organizational model: “Just as there are a great number of structures for biological organizations, so there are a number of organizations for the social organism that is the modern institution.” We like to think of an organization as an orchestra that can be harmonized. That may well be the case for organizations built around a Dunbar number but, given the continued drive for scale at the expense of an ecosystem, we usually get a cacophony instead of a symphony. It’s in the interests of vendors to promise to help the strategic CxO wrap her arms around the entire enterprise. But history is full of false promises. And, while many promises are motivated by good intentions, the road to hell is paved with good intentions. The question to ask is, “What would have to be true for a vendor’s promise to provide full management capability for the enterprise analytics stack to be an accurate one?” The first thing that must be true is that everything occurring within the enterprise is capable of being known. Because we can’t manage what we don’t know. Yet a primary contention that emerges from the intersection of data science and organizational behavior psychology is that the enterprise is a complex adaptive system. The enterprise as a transactive memory system It can’t all be known. Or, put another way, if it can all be known then it’s not changing, not evolving, not transforming. And what strategic CxO bases her work program on the contention that the enterprise isn’t transforming? None. This is not to say that we’re powerless. After all, changing the paradigm is what a leader is for. Within the enterprise analytics network, there should be a node that does nothing else but work on emergent problems of organization dynamics. Sometimes this node is missing entirely. That’s because the dominant management paradigm is oriented toward managing the known. This is also another way of saying we tend toward a strong delivery culture. Where this is the case, the best value adding elements of the enterprise analytics network aren’t in play, which means that the enterprise isn’t transforming with intent. For this sort of organization, digital transformation just means digitizing analog processes. And you don’t need an expensive analytics investment for that. But we do need an enterprise analytics investment if we see ourselves as a Levitin organization. A Levitin organization is an organization that views itself as a transactive memory system. I use the term in the context of Daniel Levitin’s excellent 2014 book The Organized Mind: Thinking Straight in the Age of Information Overload which describes companies this way: “The company as a whole is a large repository of information, with individual humans effectively playing the role of neural networks running specialized programs. No one person has all the knowledge, and indeed, no one person in a large company even knows whom to ask for every bit of knowledge it takes to keep the company running”. Enterprise analytics is about focusing on the links between networks This theme is explored further by Cesar Hidalgo in his 2015 book Why Information Grows: The Evolution of Order, From Atoms to Economies. Recognizing that we can only remember and understand a limited amount of knowledge, he introduces the idea of thinking about people as “personbytes.” It’s simply impossible to know everything, but all of the knowledge is available because the information contained by each individual personbyte is connected within the enterprise by networks. The bigger and better the network, the more personbytes can get connected. And the thing here is that there is a strong social and cultural element to making these networks effective. We are of course talking about the enterprise and the ecosystem which it inhabits. This is why the strategic CxO understands that the claims of being able to see the whole business are hollow. The task of the strategic CxO comes down to focusing on the links between networks in a Levitin organization. And the way to do that is focusing on culture and learning. The enterprise view of analytics helps the strategic CxO resolve problems of the organization shaking itself apart without buying into the impossible dream of making the entire enterprise manageable through analytics. Related content opinion To manage GDPR data risk, pay attention to your service level agreements Your technology suppliers provide a pipe, platform or other web-based application to enable their clients to do business over the Internet. Unless the client has stipulated their security requirements, the supplier is likely to only provide a basic s By Rohan Light Mar 29, 2018 8 mins Regulation Government Technology Industry opinion Data governance moves past throwing facts together Learning how to learn is becoming a critical executive skill and learning to think probabilistically will become table stakes. 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