Companies know they can benefit from analytics and other data-driven technologies. Most have even acknowledged that these technologies are essential for remaining competitive. So it’s not surprising that in one survey, 97 percent of executives said they were actively investing in data-driven projects.
Most of these executives are also realizing that leveraging analytics is easier said than done. The same survey showed that only a third of executives have successfully installed a data-driven culture at their companies. In practice, analytics has immense but elusive potential. As a result, a lot of data initiatives stumble to start.
Instead of falling into these traps yourself, learn from the mistakes of others. [bctt tweet=”Below is a list of some of the most common obstacles in data analytics, along with ways to avoid them.” username=”TTN_TheTechNews”]
Culture Is Not Data-Driven
Data analytics isn’t just a tool, it’s a whole new approach to business. Treating it like an optional asset puts a hard cap on how much value it delivers. In order for analytics to really excel, it needs to be baked into the company culture. It helps to offer education and training to staff regarding data literacy. Data literacy is the ability to read, understand, create and communicate data as information; and, as you might expect, this is essential for establishing a data-driven company culture. It also helps to rely on analytics tools that are accessible enough for everyone to use.
Projects Lack a Clear Business Goal
It’s not enough for analytics to have potential. Companies need to understand why they’re using analytics, when to use data, and how to apply it. Without clearly defined business goals and objectives, analytics gets used occasionally and feels unfocused. Make sure everyone on the team knows where analytics fits into the overall strategy.
Access Is Limited
Data is both complex and sensitive, leading companies to control it closely. It’s only accessible to IT staff, executives, and everyone else on an as-needed basis. But analytics needs to be accessible to as many people as possible for it to live up to its full promise. Relying on tools that prioritize self-service makes data-driven insights available to all.
Analytics Is Isolated
Lots of analytics tools offer intuitive features, but users have to go out of their way to access them. It’s an inconvenience that interrupts workflows. As a result, employees use analytics less than they could or should. With embedded reporting from companies like ThoughtSpot, the insights are built into the applications and processes users already rely on. It becomes effortless to base every decision on data.
Reporting Is Everything
Being able to run reports quickly is great, but it’s not always useful. Reports are over-sized and inflexible documents that don’t necessarily reveal what users really want or need. Instead of making reporting the focus, look for analytics tools that emphasize answers to data questions, whenever they arise. Users can find the exact insights they need on-demand. It’s a lot faster and easier than trying to pick them out of a report.
Customers Get Overlooked
Most companies adopt analytics hoping to increase efficiency and productivity, lower costs and mistakes, and accelerate improvements and innovations. Those are realistic expectations but viewing analytics as exclusively a back-office tool is shortsighted. It’s also capable of improving the customer experience and creating value through goods and services. Said differently, it’s a way for you to engage customers and drive revenue.
Maybe you are dealing with some of these issues. Or perhaps you are dealing with all of them. Either way, you’re hardly alone. Analytics has so many applications for today’s and tomorrow’s businesses that it can’t be dismissed. But without the right tools, policies, and attitudes, it can be more of an obstacle than an asset. If you’re currently feeling discouraged, don’t be. With a few corrections and additions, your effort is back on course. And once that happens, your company is better off than ever.
