Ten Factors Impacting Your Data and Analytics ROI

According to McKinsey are high-performing organizations three times more likely than others to say their data and analytics initiatives have contributed at least 20 percent to EBIT. Twenty percent of earnings before interest and taxes from data and analytics alone! That is an incredible contribution and a significant validation of why you should invest in data and analytics.

But as every prudent investor will tell you, do your due diligence before you write your check.  In this case, ask yourself these three questions:
1. How do you know if your data and analytics investments will pay off?  
2. What factors might impact your return on these investments (ROI)?
3. Is there a way to mitigate these factors to improve your ROI?

To help you answer questions two and three above, here are ten major factors impacting your data and analytics ROI today. Consider them wisely.  

1. Data-driven insight is a competitive advantage
Today, nearly every business transformation—be it greater customer intimacy, more optimized operations, or faster innovation—is fueled by data-driven insight. This is your competitive battlefield. For highest ROI, link your data and analytics investments to your business transformation strategy.

2. Time-to-solution is a key differentiator
Remember when your business teams would patiently wait weeks or even months for IT to deliver a solution? On the data-driven innovation battlefield, victory goes to the swift. Embrace agile.

3. Analytics are turning insight into action
You have witnessed how analytics have evolved from what happened, to what is happening now, to what is happening next, to what better outcome would you like to happen, to automatically executing that action for you. Said another way, analytics are now more real-time, more predictive, more prescriptive, and more proactive. Are yours?

4. Business self-service data demand continues to explode
Enabled by easier-to-use, more powerful self-service analytic tools such as PowerBI, Spotfire, etc., your business users constantly demand more data, data from anywhere and everywhere, all of it, at any and all times. Their demand is endless. If you think “data democracy,” you are on the right track.

5. Data’s relentless growth and gravity is accelerating
While IDC’s annual data growth statistics continue to astound, it is the gravity of that data that is resetting your entire data landscape. Gone are the days when you hoped to centralize all your data in one place. So get used to the fact that the data you need is going to be everywhere and get used everywhere  –  your cloud providers, your computer rooms, on desktops and mobile phones, within IoT-connected devices, and at third-parties including your customers, vendors, partners, and more.

6. Real-time data’s importance is soaring
Most IT organizations work with data at rest, not real-time streams. But real-time responses as events occur are increasingly the key to success when engaging with customers and optimizing operations. Let me give you an example. The moment when a customer moves their mouse to the abandon shopping cart icon is the moment when you need to react—not the next day when you get the website metrics report. Compressing your data capture to analyze to get insight to decide to act cycle is key.

7. Data related regulations continue to grow
Compliance with new regulations is not optional as governments respond to citizens’ privacy protections, data security, AI/ML bias, and other data-related threats. The General Data Protection Regulation (GDPR) in EMEA and more recently the California Consumer Privacy Act are actually global in their impact. And concerns about AI ethics and fairness portend a new regulatory wave. With more regulations on their way, expect your data analytics governance and security processes will consume an even greater share of your resources.

8. Data integrity remains an elusive goal
Let’s face it, ensuring data quality, consistency, security, and control has always been hard. Further, data integrity is a moving target as you try to keep pace with your ever-changing business and technology. And exploding data volumes and diversity are making it even harder. Hitting this moving target is difficult and disruptive.

9. Rising data analytics complexity is breaking the status quo
According to Einstein, “The world as we have created it is a process of our thinking. It cannot be changed without changing our thinking.” The rising complexity driven by these disruptive factors has conspired to wreak havoc on your existing data analytics strategy, architecture, infrastructure, organization, and more. To achieve data analytics’ business impact regardless of all these myriad data challenges, you need to heed Einstein and change your thinking.

10. The data analytics skills shortage persists
Let’s not forget the human dimension. From DBA to data steward, from data engineer to developer, business analyst to data scientist, your workloads are expanding exponentially, far faster than your human resources. This slows your realization of data analytics value and lessens your opportunity to gain competitive advantage. Look to AI/ML to automate a greater share of your data and analytics efforts.

Robert Eve is Senior Director of Data Management Thought Leadership at TIBCO Software.