Why Your Big Data Needs to Be Agile
When we talk about the digital transformation, we often refer to the importance of agile businesses. Enterprises willing to adapt to new technology are better poised to come out on top –but companies aren’t the only things benefiting from agility that allows them to pivot in real time.
Big data, as we know it, is just getting started. The mainstream adoption of the Internet of Things (IoT) has led to massive amounts of data accruing in centers. The more businesses adopt IoT, the sooner they’ll realize that data comes with responsibility. Big data, just like big business, must be agile. But how to move mountains of data, and with agility? That is a heavy question to ponder.
Execute in Real Time
According to a report published by MarketsandMarkets, big data will continue to be a lucrative prospect through 2021. Today, the big data market is worth about $28.65 billion. By the end of 2012, expect that number to be $66.9 billion – with a compound annual growth rate of 18.45 percent. A significant portion of this growth, I predict, will be from enterprises leveraging big data to expedite decision-making processes. Using big data effectively requires businesses be actionable. Execution in real time is essential, as anything less can slow down business processes. Skillful execution is also paramount. Let me explain what I mean. More data isn’t necessarily good data; in fact, data for the sake of data will only muck up your company IT and overload your data centers.
A massive amount of customer data – like personal information – is also unhelpful. Consumers are antsy about targeted messaging and could feel their privacy is being violated. Without human guidance, this machine data can grow out of control (and frankly, will be of little use).
Those who use big data effectively are those who guide the process based on building a relevant relationship with a client. That’s a job for marketing, but these days, IT and marketing go hand in hand. Devise a plan that supports the efficient running of your data centers and gathers pertinent information to enhance the client relationship.
Be Careful with Personalization
I think we’ve all been victims of targeted messaging gone wrong. Here’s a classic example: A man purchased an engagement ring for his girlfriend, and now-discontinued Facebook Beacon posted the information to his wall without his consent… ruining the surprise. Imagine getting a congratulatory call without even popping the question! Incidents like these make targeted messaging seem more like Big Brother, which is a big turn-off. Personalization can be an asset to your arsenal, but proceed with care.
As personalization becomes the norm in business, big data will become agile data. Essentially, it should generate data that’s valuable and unique to the enterprise.
Have Data, Will Profit
The key to devising an agile big data strategy is realizing that having data isn’t as important as the ability to use it. A recent survey of US and European data executives found that less than one-third of companies had turned a profit on their big data initiatives, while 45 percent said that they were only breaking even. Ouch.
So how do we make our big data profitable? Simply stated: the process requires many layers working in tandem. Let’s break it down.
- Define your digital roadmap. It’s hard to anticipate the destination if you don’t know where you’re going. Create specific objectives, and research how your data will help you achieve those objectives.
- Understand how data creates value. Remember: More isn’t necessarily better. Big data is only taking up space in your data center. Brainstorm which types of data are valuable to you as an enterprise, so you can use it.
- Create data governance. CIOs need to have a plan in place for mining, organizing, and storing data. Don’t wait until your centers are overloaded before making a game plan. Consider organizing a task force that continually oversees your data strategy.
- Be a data-driven culture. Big data is becoming the new standard for business. Foster a company culture that’s dynamic and data-driven.
The key here is realizing that data isn’t the solution – it’s the means to the solution. Your data should tell a story about whom you are and where you want to go. It needs human insight; pure data can’t be the result of machine farming. Know what to do with the information, and communicate it in a concise form.
As IoT churns out massive amounts of data, be prepared to use it. Historical data continues to be important, but combine it with real-time data to achieve your digital goals. Devise your big data roadmap, and create a culture that’s data-driven and dynamic. It’s time for your big data to become agile data that will let your business move mountains.