About enterprising analytics\nTo 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.\n"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 it\u2019s analytics investment.\nGovernance is for the engaged leader\nAs organizations evolve, or try to evolve, the matter of governance inevitably comes up. As it should, because how the strategic CXO manages governance will determine to a significant extent how the organization will move forward. Governance is, as you\u2019d expect, a primary task for leadership. It\u2019s also something subject to a wide variety of approaches, especially in organizations seeking to balance the agile and waterfall delivery methodologies. Therein lies the rub: no one size fits all. This is a task for the engaged leader, not the templated leader.\nGovernance is essentially about behavior. An early meaning of the word meant "rules of conduct," where "to conduct" meant to "guide." This idea of a guide rather than a set of rules is an important distinction for the strategic CXO to bear in mind. It means her decisions around governance aren\u2019t going to be simple to execute. There won\u2019t be a handy dandy flowchart to follow. Even if a flow chart is put together and gone through the right channels, there\u2019s a good chance it\u2019ll be out of date. There are enough pretty pictures scattered around our desks already.\nGood governance is about good behavior\nElegant delegation and decision rules come undone at the first special case that requires a variation from the norm. The more ad hoc adjustments make a mess of a rules based system and these adjustments are inevitable. Because one thing that is certain with all governance systems is that people will find a way to game them. To combat this, organizations tend to stack checks and balances on each other. What tends to happen from here is that everything gradually slows down.\nA simple rule of thumb for this situation is that governance has an inverse relationship to accountability. No amount of governance can make up for poor behavior in an organization. And because of the business metaphor of 'competition' and the shadow of the leader, the poorest behavior can often be found at the top. Within the governance environment. With the CXO. This means good governance is about an individuals commitment to the responsibility of leadership.\u00a0\nGovernance for enterprise analytics is about taking action\nGovernance is about who has a voice in decision making, the decision behavior (how decisions are made) and who is accountable for executing the decision. Because a core element of the business case for enterprise analytics investments is about improving decisions, governance becomes a critical issue to get right. This isn\u2019t just something that interests constitutional and management theorists. Good enterprise analytics is built on good data science and good data science applies Bayes Rule. This requires an organization to continuously act, adjust and update.\nWhat does this have to do with governance? If there is no action from a decision, then there was no decision. There was only an intention. And we already have plenty of those. This means good enterprise analytics governance emphasizes the taking of actions. Governance of decisions quickly becomes governance of action. And \u2018action\u2019 isn\u2019t a common topic of debate for corporate governance.\nIt's about communication, not information\nWe might expect the governance of enterprise analytics to be all about information. Not so. It\u2019s more about communication. Effective governance of data is (correctly) seen as the requisite first step. But it can be tempting to pause on that first step. The problem that emerges here is that data is inert. It becomes information only when it is shared. The original sense of the word \u2018inform\u2019 was to teach, educate or instruct. Information emerges from the interaction between people.\nIt is communication that converts data into information. Recall that enterprise analytics is about learning at scale. Getting from information to learning means going from communication to community. And at the heart of the idea of community is communion, which is a mutual participation or sharing. But this is where it gets difficult. It\u2019s unrealistic to think of all the members of a large organization (which includes contributors outside its formal boundaries) as a coherent community.\nCommunication leads to communion\nThere\u2019s an industry of leadership books that say we can but anthropology and history suggests otherwise. An organization is a collection of communities and each community makes different meaning from the same information. The larger the organization and the more communities within an organization the more reaffirmation of communal meaning will be required. This leads to a lot of back and forth as, literally, the organization communicates with itself. It's not a case of an organization communicating: it's a case of communications organizing.\nPeter Drucker wrote:\n\n\u201cwhere the traditional organization was held together by command and control, the \u2018skeleton\u2019 of the information based organization will be the optimal information system.\u201d\n\nReading his work, it's clear that he understood that without communication there is no information, only data. For the strategic CXO, governance means oversight of action and negotiating meaning between the various communities that comprise the enterprise. Enterprise analytics can help the modern organization understand itself through better communication. Or it can just amplify the babble and increase conflict.