Are These Common Data Challenges Stifling Your Growth?
Data is like a crystal ball for your business. Utilize it well and you have a 360 view of where you’re at and, more importantly, where you’re headed. Data insights can become images that help you make informed decisions about everything from your processes to your profits.
It’s estimated businesses collectively create around 2.5 quintillion bytes of data each day, yet up to 73% of that company data goes unanalyzed.
Which begs the question: if data is so plentiful, why aren’t more organizations efficient, well-oiled machines?
Just collecting data isn’t enough. There are real barriers to making sure it lives up to its full potential. Here are five that stand out – and how to overcome them.
1. Legacy Tools and Systems
No one solves new data challenges with old systems. Don’t get us wrong, we’re not knocking spreadsheets. But if you want to gain and maintain a competitive advantage, you’re going to need to evolve how you collect and analyze your data.
Not only do traditional methods risk manual errors, you can unintentionally create data silos that hold critical information hostage from the rest of your organization.
Instead, look for tools that allow you to gather and visualize large quantities of high-quality data in a seamless, user-friendly way. Open-source solutions are particularly low-barrier because of their cost-effectiveness, speed, and flexibility.
2. Digital Skills Shortages
The global talent shortage encompasses 40 million skilled workers worldwide. Forbes says, “If this trend continues, by 2030, companies worldwide risk losing $8.4 trillion in revenue because of the lack of skilled talent.”
And it’s even worse for qualified data specialists.
“With businesses across industries scrambling to acquire AI talent and to increase their own data-driven decision-making, demand for data analytics professionals will likely outstrip the available talent for some time,” explains Deloitt.
Software can help close the gap – so long as employees are properly trained on how to use it. Data scientists and data analysts are important, but don’t lose sight of (or underutilize) your existing talent either.
3. Disorganized Data Collection and Storage
Incomplete datasets will do you little good. If different teams are “collecting” data in different formats, you’re unlikely to get the full picture. You’re also creating double the workload for your data department.
The goal should be to create a universal data collection process that’s the same across your entire organization.
Improper data storage solutions can also create major bottlenecks. You need enough space to house all your current and future data, as well as intentional investments in robust backup and recovery options in case the unthinkable happens.
4. Lax Security and Privacy Processes
It doesn’t matter what type of data you collect. That information is valuable to someone.
Be it proprietary information, bank account numbers, or personal data of your clients or employees, if a cybercriminal can access it, they’re going to exploit it.
Privacy regulations that govern these types of data can be even more of a headache if you’re dealing with international entities or doing business overseas.
If you don’t have a handle on the quickly evolving global data compliance laws, start educating yourself and making changes now.
5. Piecemeal Data Strategy
Again, the aim here is to avoid data silos, understanding that even diverse data elements are interconnected.
As Michael Thompson, Head of BI & Data Analytics, Americas, at JLL Technologies Companies, shares, “Companies require a holistic strategy that defines every data stream and how it interacts with other building data. A robust data strategy needs to define, check, organize and distribute data to the places it needs to go.”
Reality check: Your business isn’t getting away from data. With the right tools, strategies, and skills data can drive massive organizational efficiency and growth. Or, it can keep you small and stuck. The choice is yours.
Content created and provided by ONEAFFINITI.
