4 Keys to Turning Data Analytics into Value

There’s a lot of talk about big data and analytics revolutionizing and changing the way we do business, but not everyone is on the same trajectory to see its potentially profound benefits.

Recent research by McKinsey suggests that, as with any other innovation, there’s a gap between leaders and laggards, and, in the area of data analytics, that gap is growing.

Some companies area already well ahead and have learned how to collect, organize, and analyze their data to reveal previously unknown opportunities, risks and trends that open up entirely new prospects for growth and profit. Others haven’t even started, or they’re struggling with the basics and how to even begin to turn data into real value for their business.

The prospects of data into breakthrough insights and strategic advantages are tantalizing, but the prospect of getting there can seem overwhelming.

How do you enable data analytics in an existing organization, and how do you integrate it effectively so it delivers real value?

To answer that question, several McKinsey partners spoke with analytics leaders at companies across a wide range of industries and geographies. In their conversations, they heard some common and crucial themes, and these are the real keys to achieving a data analytics culture that supports operations and adds value to the company.

Here are some highlights of their findings that our team at SpareHire found particularly helpful.

1. Less is More.

In data analytics, the end game isn’t amassing huge quantities of data. It’s about making good decisions on the basis of that data. It’s about the business opportunities you want to uncover and the problems you need to solve.

Data analytics is about answering related key questions, solving those problems, and helping make informed decisions. In the end, it’s not about quantity. It’s about quality.

Accordingly, companies should focus their data management and data analytics on their core business problems, questions, and opportunities for growth and profits. Never focus on data for its own sake.

By being focused, your data analytics efforts will be more efficient and profitable, and there will be much less data that you truly need. In this case, less is more, and it can help simplify your path to an effective data analytics culture.

2. You Can’t Be Afraid of Commitment.

As with any major initiative business and any effort to change culture, it has to start at the top. To build a data analytics culture, you need understanding and commitment from the C-suite and board of directors.

Some data analytics initiatives are introduced and driven by top leadership. Others come from more of a grass roots effort that requires education of company leaders to build the case and gain support for embracing data company-wide.

But even if it comes from the top, it has to be more than a singular pronouncement or declaration. There must be a sustained commitment and interaction, where company leadership and data scientists and data advocates work together to make sure that everyone understands the value of the effort and buys into the steps to make it happen.

3. Get Everyone Involved through Accessibility.

People can get excited about data and the prospect of turning it into a competitive advantage, but only when they see it as relevant and accessible to them. You can’t just impose data analytics from the top down.

You need to get everyone in an organization to adopt a data culture mindset, but you also need to recognize that it takes time to get there. You need to democratize data, provide systems and platforms that make it accessible and usable.

Once people can easily see and access data, and once they see its usefulness, they can begin to believe in it and allow it to drive new innovation, ideas and processes. It starts by making sure data flows across your organization seamlessly, and it’s readily accessible for everyone.

4. Doing Data Properly Requires Talent.

As more organizations look to leverage data to their advantage, competition for data analysts and data scientists has become fierce. But data talent can be found in places outside the organization or even outside the data realm within your company.

Some companies have found that they have talented data analysts or data scientists in many different departments. They may be outstanding at working with data and creating value from it, even though it may not be at the core of their job title or responsibilities.

As a result, you can look beyond your IT department or your existing analytics experts and recruit future data scientists from within your own ranks.

Additionally, while competition for hiring data analysts as direct employees keeps heating up, new channels for finding the right talent are growing every day.

At SpareHire, our network of over 5,000 elite business consultants includes many data analysts, data scientists and experts with proven experience in working effectively with data and unlocking its value in virtually all industries and types of organizations.

This makes scaling up your data analytics operations much easier and more affordable, by giving you access to on-demand experts who can help you compile, analyze, and convert data into value. You can hire our consultants for everything from part-time, short-term projects to long-term, ongoing data analytics needs.

To get started and explore our data analysts, post a data project or role now, or contact our team to learn more and get personalized assistance with finding a qualified data expert.

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Greg Andrade

Greg Andrade handles SpareHire's marketing and communication programs. A graduate of the University of Michigan, he worked in corporate marketing for 15 years before turning his focus to virtual marketing consulting for startups and global businesses.

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