How to Get Your Organization to Embrace Data

Data is a part of everyone's daily life in business.

Data is a part of everyone’s daily life in business.

Data is a part of everyday life for business analysts, but it can be a complete mystery to anyone outside of their department. If your company doesn’t follow data-driven decision making yet, then the time, money and effort put into collecting and analyzing data and presenting concepts based on that analysis is wasted.

BAs and data scientists are learning that complete organizational change needs to occur if companies are to embrace the benefits of big data to drive future growth. This isn’t as simple as adding a new employee and investing in a few software options but requires full data acceptance.

Data Analytics Will Change How Companies Operate

Data analytics is changing organizations in the same way computers and the internet did in decades past. Most leaders don’t understand the full scope of how analytics will affect their day-to-day tasks.

Will Goodrum, Ph.D. at Elder Research has watched organizations approach data analytics in the same way they approach threats from their competition or disrupting organizations. Instead of using the tools as possible advantages, companies dig their heels in and try to push through with the status quo. A few common barriers to full data acceptance include:

  • Companies lacking sufficient data to address a problem;
  • Legacy organizational and IT structures holding adoption back;
  • Inflexible people and processes unwilling to adapt;
  • Poor communication between functional groups.

Without these four factors, business analysts are left trying to push their tools and opportunities to people who can’t or won’t listen to them.   

“The worst thing you can do is overlay your new system on top of your old, antiquated processes,” Jay Hammerquist of Evolve Partners, writes. Especially when you’re using tools meant to eliminate waste in your current processes!

Change is on the horizon, and companies can either embrace it or ignore data analytics until their competition overtakes them.  

Make Sure Key Stakeholders Are Invested in Data-Driven Management

Data doesn't play office politics.

Data doesn’t play office politics.

The first step toward organizational change is stakeholder buy-in. One of the main benefits of big data can also be one of the hardest pills to swallow. The numbers are objective, and clean data doesn’t play office politics.

“Actionable analytics and insights remove the subjectiveness in business,” Kelsey Purcell writes at DemandZEN. “Without the correct reporting in place, all your team has are instincts and opinions being thrown around, taking you in a million different directions.”

Your executive team and company managers need to stop making decisions based solely on gut instincts. Unfortunately, this means some people will have to set their egos aside. “Your team will have to adopt a mentality of being a learner as opposed to expert, and this starts at the top,” Jeffrey Pruitt, CEO of Tallwave, writes.

If senior leadership won’t listen to the data insights, then employees at every level of the company won’t bother using them. Start with the stakeholders and then work through the rest of your organization.  

Consider Restructuring Your Business to Prioritize Data

If your company still can’t fully accept the value of big data, changes to the organizational structure can shake things up and give data analytics the respect it needs.

Senior management consultant John Weathington says that organizational leaders who are serious about creating a data-driven company should invest in a Chief Analytics Officer (CAO) or similar to report to the CEO. This position serves as an advisor to the CEO and leadership team, helping them understand the possibilities of data as a decision-making tool.

Along with hiring a CAO or similar position, Joshua Siegel, director of professional services at Dell EMC encourages companies to institute two governing bodies:

  • An Analytics Governance Council (AGC) to monitor the transition and use of big data systems. They determine the data to be used for maximum impact.   
  • A Data Governance Council (DGC) to function on the operational level, making sure data collection stays clean and available. They remove roadblocks in data collection and the analysis process so the AGC can deploy it.

The committees ensure there’s not just one person managing data analytics and making their own strategy, but rather the data is applied to the most important areas of the organization.

Collect High Quality Data, Then Take Action

Organizational change is significant and difficult.

Organizational change is significant and difficult.

While organizational change can be significant and symbolic in your company, the data has to prove its worth to earn its place. Taking action and driving results is where most modern companies struggle.

“I don’t think any company today would say they have a data problem,” Florian Douetteau, CEO at Dataiku, writes. “But I do think many companies, whether they like to admit it or not, have a data value problem. That is, they struggle to gain real business value from all of the data (or any of the data) they’re collecting.”

Having a great deal of data but not knowing how to use it is a common problem, agrees Jon M. Jachimowicz, a doctoral candidate at Columbia Business School. He cites an HR manager who had masses of employee data but found it wasn’t very useful in providing the insights he was looking for. The first problem Jachimowicz noticed was the poor quality of data collected: unreliable, unvalidated and incomplete.

Working with poor data is like reading a map with holes in it: you can see where you want to go, but there’s no clear picture on how to get there — or even where you are.

The ability to collect valuable data and gain insights from it is a challenge companies of all sizes face, from small business to Fortune 100 companies. Leonard Lee, VP and global head of new business at Airbus Group, recently discussed how his company is sorting the massive amounts of data it has and turning it into actionable insights.

Collecting the information isn’t the hard part for his company, he explains, because aircrafts provide tons of data. The challenge is applying new insights: Only two percent of all data from aircrafts is used in a meaningful way. If Lee can bring that number up, even to four percent, then Airbus can take massive leaps to improve their operations and products. For example, one application of big data analytics accounted for more than $36 million in savings over the course of a year.

Strategically Plan Where to Use Analytics Tools First

As you sort your data and are ready to use it to implement changes, look for low-hanging fruit that can drive results. “Without a carefully structured plan, investing in big data can be a waste of time, resources and money with little result,” Alice Payne writes for Graydon UK. “The key is streamlining and tailoring big data to meet your company’s needs, rather than suffering from a data deluge.”      

Data professionals should focus on “hot spots” within the organization, advise David Niles, Deb Henretta, and Sandy Ogg at Data Informed. Instead of trying to make data revolutionize every aspect of the company, choose one project that could yield significant results when data analytics are applied.

Once you’re able to prove the effectiveness of that approach, you will have the momentum and reputation under your belt to move on to other departments and less data-friendly teams. Ronald van Loon, director at Adversitement, emphasizes the importance of broadcasting these victories within your organization. Showcasing team wins is a great way to develop healthy competition.

When teams see what other departments and employees are capable of doing with help from data analytics tools, they will want access to them as well. Soon data-analytics is a new resource people want to test instead of a complicated skill they are afraid of.     

Learn the True Value of Your Organization’s Data

The data your collect is an asset to your organization.

The data your collect is an asset to your organization.

As you incorporate data analytics within your company, never underestimate the value of what you are doing. Your executive team might not see it now, but the data you collect is an asset to your organization. EverEdge Global provides a few examples of how valuable data is on the global market:

  • When Caesar’s Palace went bankrupt in 2013, its data alone was valued at $1 billion, making it the company’s most valuable asset.
  • When online retailer Kogan’s bought Dick Smith’s customer database, it made 15 times their money within three months.
  • Experts estimate that every Fortune 1000 company could increase its annual net income by $65 million with just a 10 percent increase in data accessibility in the organization. The Airbus study mentioned earlier is an instance that proves this statistic.   

These data points are just vanity metrics to defend data investments. Data is unlikely to appear on a balance sheet, but its value can be used to leverage resources within a company, Richard Fusco, senior consultant at Digital Prism Advisors, writes. The more exclusive your data is, and the more granular, the more valuable to your company and others.

Most Companies Want to Take Action From Data Insights

While some executives and companies might push back against data analytics and the changes that come from its use, most want to take advantage of the technology to use and monetize data.

One survey by The Economist Intelligence Unit found that 83 percent of executives have used data to make existing products and services more profitable, “and over two-thirds feel that there is a case for starting a new business unit dedicated to developing data-related products or services.”

Despite this optimism, a lack of understanding and finances continues to block the general movement towards a data-driven culture. In another EUI report, writes that one-third of the executives asked say they don’t fully understand how to apply data analytics to their business and/or they lack the funds to make major investments in data.

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