In a Big Hurry for Big Data?

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In a Big Hurry for Big Data?
In a Big Hurry for Big Data?

Companies are working at a feverish pace to acquire newer and bigger data sources as customer data, stats, traffic patterns, and a host of other Big Data metrics has become available, and often is up for grabs in real time. The problem is that most companies are not terribly good at acting on small data; analyzing any data requires discipline to be successful and scalable. So while the unprecedented amount of available information offers great opportunity to understand and respond to customer needs and wants, it also can spin out of control when enthusiasm trumps discipline.

Follow these five rules to build a solid foundation that will help tackle all data, big or small, and improve your loyalty marketing initiatives with actionable customer analysis that creates profitable results.

1. Know your destination.

Focus on doing the right work before focusing on doing the work right. In baseball, the axiom is “you can't win a pennant in April, but you can lose one.” For analysis projects, the parallel is “analyzing the right question does not guarantee a great analysis, but you seldom get one when looking at the wrong question.” Good analysis leads to action and change. Bad analysis done without a purpose leads to spinning wheels. Before embarking on any project, be clear on how the outcome leads to action.

2. Nail it down.

Never guess when the answer is readily available. As data sources, processing speed, and analytical techniques advance, the instances of using gut instinct are waning. Companies should design analytic systems that allow for quick retrieval of the right information. Then, they should challenge each other to actually use the information. Too much is at stake with each decision for baseless assumptions and guesses, especially when the information exists

3. Nothing less than perfect.

Nothing can derail confidence in not only current, but also future projects more than analysis errors. Management often is skeptical of high-level analysis. Don't give them ammunition by making critical errors. Checking multiple data sources for continuity, sense-checking with clients before formal presentations, forming an independent team to review code, and internal reviews are all ways to quality check output. This step is not limited only to presentations; make sure all calculated metrics on dashboards and standard reports are perfect.

4. The rule of threes.

Never do anything manually three times. Today's insight-filled analysis is tomorrow's spreadsheet or dashboard. Keep this in mind when starting a project. The first time, a project is coded by hand. The second time, the project is automated and run in parallel manually to check the results. There is no third time doing it by hand. When a project begins, have discussions about whether the work will be needed on a regular basis and if so, move to automate. Smart companies automate insights, freeing up manpower to find the next set of business-altering insights.

5. No value without action.

Stakeholders don't care how clever analysis is; they just want to know how to act. Most analysis projects begin with good intentions. There are clear question, a clear action plan, and a defined project plan. Then somewhere between the last checkpoint and delivery, the project goes sideways. This is when the practitioner delivers something that impresses him, but is useless to the stakeholder. Unless writing a white paper, the project should be as simple as possible, but no simpler. Good analysts produce good work, while great analysts deliver audience-relevant work.

As the world moves from small to big data, solid analytic fundamentals are more important than ever. Without them, more data will only produce more noise leading to poor decisions. Companies burned by analytic weakness sometimes consider ignoring the real value of data and slide back into gut-based decision making. They will regret this short-term thinking as more and more of their competitors start applying these rules, building a solid analytic foundation designed to handle any data source. It's a competitive advantage no business should give away.

Dennis Goodman is director of loyalty programs at 89 Degrees.

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