There’s a lot of talk about Big Data – how much data to collect, and what to do with it once you have it.
Indecision – or lack of clarity – at the start of the process can leave decision-makers with lots of granular information but no real solutions.
One problem is that people assume more data is better data – when actually, you can let lot of value from a little or just the right amount of data. And you don’t need to spend millions of dollars to get it; rather, just enough to gain value.
That’s because the Big Data advantage lies within your analytics capability – your ability to draw conclusions and identify patterns. To get those analytics, you can crunch more information, less information, or somewhere between.
To apply Big Data principles to your own operations, first consider what assets are most critical to your operations: "Start with the end in mind and ask yourself questions like, 'What do we want to get out of this data?' and 'What could data tell us if we had it?'"
Use the acronym STAR to help determine what data you want to collect:
- Simple: The basics will allow people to make quick, informed decisions by providing clear visuals.
- Timely: In today’s connected enterprise, it is essential to make data available when it’s most needed. Timely availability of data is key to success.
- Accuracy: This is important, especially for trust and improving a culture of decision making.
- Relevant: Data should be relevant to whatever the decision-maker is being measured on. If you are being measured on profit, have metrics that help you; if it’s more about uptime, have a KPI (key performance indicator) trained on that.
And remember: the value of Big Data is not in the numbers or statistics or reports; the value is what you learn from the analysis of the information. That means more data is not necessarily better. Some data is better than none, but getting the right data to the right people to make the right decision is the ideal scenario.
