Is Analytics tool expected to single-handedly improve decision making in an organisation?

Analytics oriented decision follows triple As: "Adaptation, Agility, and Accountability."

More and more organizations are exploring data analytics to gain customer insight or business foresight, and data-driven, fact-based decision making is surely the trend to run a smart business. However, is the analytics tool expected to single-handedly improve decision making in an organization? And what are the principles, practices, and processes to do analytics for better decision making?

Advocate fact-based decision-making: The decision to implement BI or analytics is just a start to better decision making. The push for fact-based business management must come from the top and permeate through the organization at all levels. Business Intelligence will not single-handedly improve decision making in an organization. if the organization does not believe in the analytics capability and usefulness of Business Intelligence, it will not improve decision making. There are so many analytics implementations fail miserably due to lack of adoption. These are not cheap implementations and the lack of success of the effort was squarely shouldered on user adoption. The old adage "you can lead a horse to water but you can't make them drink" is very appropriate here. Just implementing an analytics tool is not going to result in improved decision making for an organization. The technology should be seen as an enabler and should form part of an analytics strategy, but not be its whole. Improved decision making will only come when insights from the analytics system are directly matched to improved decisions and better outcomes. Ensuring these insights are used in the process of decision making should be one of the keys to success for any analytics strategy and that will often require significant organizational change, education, and evangelism by someone in the senior team.

Craft Analytics strategy: Large organizations especially need a comprehensive analytics Implementation Strategy. Culture would be part of that strategy. Culture addresses the willingness to change at the user/analyst level as well as executive-level support. The entire value chain of a Finance/IT management matrix needs to be aligned. Small analytics successes help create momentum in an organization. Senior leadership no longer needs to make funding decisions only based on guts. There is some actual value-added success to base future decisions on. There's often a disconnect between the way analytics solutions are marketed and the way they need to be implemented. The marketing promotes the idea that analytics is a magic bullet: that system-wide improvements slide into place as soon as you install the system. That raises unrealistic expectations in the minds of corporate sponsors, which can lead to crushing disappointment if those gains don't immediately materialize. It's easier to sell a slick technological product than a rigorous, culture-change process.

Follow AAA' principles: The business must be educated to make use of analytics (it's a process!) following triple-A principles: Adaptation for upcoming business trends, Agility to implement new thoughts and Accountability to establish trust with business, analytics is always driven by business. It's incumbent upon those who are implementing analytics solutions to guide organizations into the change from the executive levels down to the operational ones. That means thoroughly discussing the questions that are being asked, getting buy-in to the value of the information being provided, and developing plans to act specifically on that information. Your analytics application must be reliable (information availability-analysis /performance) and aligned with the business needs.

Focus DEEPLY on the culture when moving toward an insight-led/experiment-oriented organization. The alternative you see and get most often is decision-based evidence-making. The next time you're on a fact-finding mission, ask yourself whether you are truly open to new ideas - or if you are only pursuing those that support your current understanding of the facts? It's hard to stop and see it, but if you can, you will dramatically open up your analytics ability to see the potential for insight to change what you are doing and for tools to be really informative in the process. You need to ensure everyone understands the cultural shift that needs to take place in order to make analytics successful. Anything less is a waste of money. While culture is clearly important, think of culture as a derivative, as the result of the cumulative actions taken in an organization that can be pulled together to form a coherent narrative or story about the organization. But you need the actions and quick win first. It’s like a label or the title to completed painting – you don’t quite know what to call it until you’re finished.

Manage Analytics as organic growth; starting off as one cell, multiplying and branching, slowly at first, but gaining momentum as critical mass is achieved. This organic process needs to be recognized as part of the plan and it needs to be nurtured and cultivated. Nurtured, as in identifying the most fruitful areas and fertile ground to start looking for quick wins. Cultivated, as in periodically evaluated and pruned as it develops, so that it doesn’t grow willy-nilly but develops in alignment with strategy. Simply put, you cannot push down a cultural change from the top down. That's a mandate and it seldom works, starting small really counts. Finding parts of the organization that uses analytics (not data) well. In that way they are:

(1) Creating engagement around insight, not reporting the facts

(2) Developing high levels of self-service and self-sufficiency (not IT intervention)

(3) Enabling scenario and forecasting to promote decision alternatives

(4) Focusing on making the complex radically simpler for the purposes of pattern detection (or pattern breakage).

Decision making is both art and science, enterprise scope analytics implementation is an evolutionary journey, think big (strategically) but start small, focus on building ongoing analytics capability, and shape a fact-based decision-making culture, but do not forget common sense,  intuition always has its role in effective decision making. Analytics is just the means to the end, and people with effective tools need to become such decision-making masters.

Posted in: Big Data,culture Master,Decision Making