Why do most analytical and business intelligence solutions end up not getting widely adopted?
The right analytics and business intelligence (A&BI) solution can be one of your most valuable competitive advantages because they are supposed to help all employers embrace data analytics and become data-driven. Organizations that use customer analytics extensively, for example, are 23 times more likely to attract new customers and 19 times more likely to be very profitable according to a .
Regrettably, this is not the case for many businesses. The use of A&BI tools by employees is still quite low. So, what went wrong? In this piece, we will look at some of the common stumbling blocks to A&BI adoption in most businesses.
It is crucial to understand what happens once a company deploys new A&BI solutions before we get into the challenges of BI adoption. We believe that in companies with a low level of BI maturity, one of three scenarios plays out, all of which end in people not being able to get the most out of their data investment. You are probably in one of these three camps if your A&BI implementation hasn’t gone as anticipated.
- It was doomed from the start: Analytics failed to take off in these circumstances. Employees with minimal data literacy, limited familiarity with analytics tools, or a lack of excitement for learning new technologies are likely to face this.
- It was fun for a while: It went like this: people began to use analytics software. Even yet, something goes wrong — generally due to software complexity and employee dissatisfaction — and everyone returns to utilizing spreadsheet programs like Microsoft Excel.
- It didn’t turn out the way you had hoped: People analyze data on a regular basis, yet adoption is limited due to product limits for customers. They’ll only be able to produce basic findings in the end, rather than the higher-quality analytical insights they require.
If you are having trouble with your A&BI adoption because of one of these issues, it is important to figure out why this happened and how your firm got here. Before organizations can bridge the adoption gap, they must overcome some of the most prevalent technological and cultural hurdles.
Your data infrastructure isn’t built to scale
Because of the vast amount of data generated on a daily basis in today’s corporate climate, firms must be able to satisfy increased analytics demand, particularly during peak periods such as the end of the quarter or Monday mornings. As a result of this demand, data and BI teams are frequently asked to generate new dashboards, create or re-run reports, and do ad-hoc analysis on short notice. These workloads get delayed or bottlenecked in typical data infrastructures, taking hours (or even days) to finish. Analysts and business users become frustrated. If domain experts can’t receive the answers they need when they need them, they either go forward without data or, worse, they take matters into their own hands and return to spreadsheets. This process negates the objective of your business intelligence investment. You need infrastructure that can expose insights right now, not in a week.
Investing in complex A&BI tools
Slow, complicated software tools inhibit the passion needed for mass adoption — and the highest possible return on data investment. If A&BI is to become more broadly embraced, businesspeople must join in. Unfortunately, the bulk of tools have user interfaces that are unfamiliar or were not designed with businesses in mind. And learning new software might be intimidating, especially if it isn’t your primary objective. Finding the time and place to become proficient might be difficult.
Domain specialists frequently need higher technical skill sets, such as SQL skills, to ask challenging questions and go beyond dashboards, in order to examine data and unearth high-quality analytics. Alternatively, they may require the BI team to step in and assist them on a regular basis. This skill gap often creates bottlenecks in the long run.
Because data and business specialists don’t speak the same language, BI and data teams are forced to make educated guesses about business demands and processes. Because questions are rarely answered the first time, this adds to the report backlog and diminishes the usability of data models, creating a vicious feedback loop.
Low data literacy
Unfortunately, many people lack the basic statistical skills and analytics knowledge needed to unearth valuable information. Even if you invest the money and time to build data architecture, centralize data sources, and create dashboards, none of your efforts will be worthwhile if no one understands what to do with the data. If domain specialists lack the ability to ask more in-depth questions of the data or the knowledge required to turn it into an actionable strategy, they are unlikely to embrace the tools you’ve purchased.
Where to go from here
Analytics and business intelligence projects do not have to fail; they do so for a variety of reasons, including those stated above. You will have to put in the work if you are serious about closing the A&BI adoption gap. The good news is….? ScaleWork is here to help! Watch the video below to discover more about how we can assist you in developing a business case for analytics so that you can avoid these common pitfalls!
Scalework | AI: Why do lots of analytics solutions don‘t get the adoption rates they expect to?
