Why Businesses Can’t Ignore Big Data
No matter how much we fuss about data today, let’s face it, it has always been there. Always. What has changed, though, is the speed at which data multiplies. The three Vs of big data — namely volume, variety, and velocity — are changing at such a rapid pace that most businesses simply don’t know what to do, let alone how to makes sense of it all. Besides the stacks in their repositories, businesses see the growing mountain of data in the form of emails, texts, social data, etc. on a daily basis. It’s messy and chaotic.
However, big data is also a goldmine of information that predicts customer behavior, the changing market needs, and patterns and shifts that reveal where things are headed. To let go of the opportunities this information presents is not just bad business sense, it’s a grave mistake that may cost companies millions of dollars in lost revenue.
You may ask, “In an age where businesses are expected to run on tighter budgets, can big data promise a higher ROI?” If you consider its role in shaping better decisions that result in improved retention of customers and employees and bigger revenue turnovers, then yes, big data does generate significant ROI.
What Makes Data Useful?
We know that data can be misleading if we look at the wrong type. But how do we know which data to pick and which to shove aside? This is where contextualization comes handy. This can be built around three data types — demographic data (customer information, preferences, purchase patterns, etc.), historical data (customer interaction history, records of buyers’ journey, etc.), and situational data (real-time data, online activities, device usage, etc.).
When the metrics are well-defined, it’s easier to capture info that’s relevant to your business. Simply twiddling with data because everyone’s talking about it can be a poor investment, if not downright dangerous. But, driving your business forward using information that you’re not even sure is what you need to be analyzing can also be risky.
Contextualization — defining the data that may be most valuable for your business — takes the guesswork out of the equation.
How The Right Data Helps
The benefits of big data spans across industries. The latest reports from GE and TEKsystems conclude it is a major factor for business success. GE’s Global Innovation Barometer found more than two-thirds of its global participants considered big data a critical factor for business innovation. Nearly six out of 10 IT leaders surveyed by TEKsystems expect big data spending to increase following its ability to meet business demands.
Big data can be a game-changer for businesses for its capabilities to:
- Provide more personalized products/services
- Predict the changing and challenging business scenarios
- Help businesses look beyond the curve
- Turn companies into customer-centric organizations
- Drive digital transformation
- Ask the right questions
- Enable smart decision-making
- Reduce costs in operations
Big data: A Bubble Or a Boom?
There is a lot of hype around big data. I agree almost to the point of being ridiculous. However, we need to look at big data as a tool that helps to steer our business decisions and not as a magic bullet that will rid us of all of our business problems.
So it boils down to this — big data may be everything that today’s businesses need and even more than it is cracked up to be. But until businesses start to use the right data, it’s just a bubble. To make data useful, businesses need to explore how to implement it across different organizational functions — from sales and marketing to operations to finance. Otherwise, it is just another empty business buzzword.
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This post was written as part of the Dell Insight Partners program, which provides news and analysis about the evolving world of tech. For more on these topics, visit Dell’s thought leadership site Power More. Dell sponsored this article, but the opinions are my own and don’t necessarily represent Dell’s positions or strategies.
This article was originally seen on Millennial CEO blog.