Is the Promise of Self-Service Data Analytics Real or Just More Hype?

By Keiter Technologies

Is the Promise of Self-Service Data Analytics Real or Just More Hype?

Adoption of business data tools: The benefits and barriers

Picture the following scene. A curious marketing manager doesn’t understand why her last campaign failed to gain traction. She sits down, opens a modern data analysis tool (such as Tableau or PowerBI) and begins exploring the data. After creating a few charts, the light bulb goes off as the data reveals what went wrong with the campaign and, better yet, what to do differently next time.

Many variations of this scenario have long been part of the sales pitch for numerous analytics software products. If there’s been one consistent trend in data tools, it’s been the constant push to get those tools into the hands of the people making day-to-day decisions. The benefit to the software company selling this vision is obvious: a bigger install base. The benefit to the business seems clear as well: what leader wouldn’t want their organization to make decisions based on hard evidence? This is the essence of “self-service analytics,” a movement that promotes both data democratization and employee empowerment.

The idea is simple: develop data analytics software that doesn’t require coding skills, provides basic instructions and training, and your employees will suddenly have productivity super-powers! With the demand for data insights outstripping the supply of talent in the market, this approach seems to be a no-brainer. Better yet, the data professionals you already employ will have more time for high value projects, unburdened by trivial tasks in this self-service utopia. So why are only 25% of employees with access to these tools using them, and why hasn’t that number budged in years?1

3 barriers to adoption of data analytics and PowerBI

The answer stems from three very stubborn barriers that prevent the best-intentioned companies from experiencing wide-spread adoption of self-service data analytics and BI tools.

  1. The data in many organizations is messy, incomplete, and often poorly documented. To truly activate an army of self-service analysts, the data needs to be curated, sanitized, easily accessible, and meaningful to the analyst. This is possible with the right amount of investment, but often requires a strong data engineering foundation to exist within the organization.
  2. Assuming you have overcome the previous barrier, the next obstacle is time. Individuals require time to learn the basics of working with data, the correct visualizations to use in different contexts, and how to apply the statistical building blocks of analysis. The irony is that the individuals, such as managers and executives, who could benefit the most from self-service analytics, often have the least amount of time to dedicate to it.
  3. The biggest obstacle of all is that analytics is a craft requiring practice and experience for proficiency. Anyone can learn the basics, and everyone should have the opportunity to work with data. However, deriving actionable insights from data requires knowing how to frame questions, interpret statistics, follow the evidence, and apply design thinking; all skills that benefit greatly from practice and experience.

Future of self-service analytics for businesses

In conclusion, self-service analytics has the potential to revolutionize how organizations operate, but widespread adoption of these tools has been hindered by persistent barriers. Companies need to invest in clean and curated data, provide adequate training and time for employees to learn how to use these tools, and recognize that deriving actionable insights from data requires practice and experience. However, advancements in artificial intelligence (AI) are poised to overcome these barriers and create a new self-service analytics future. With AI-powered analytics, employees will be able to ask questions in a conversational way and receive meaningful insights, leading to increased productivity and better decision-making.

The Keiter Data Solutions team has a wealth of experience helping to implement AI, machine-learning, and analysis capabilities for our clients. From optimization models to advanced analytics, Our team can provide the tools, guidance, strategy, and support necessary to ensure a smooth transition to an AI-driven, data-centric future for your business. As a trusted partner, Keiter’s Data Solutions team is committed to helping organizations unlock the full potential of their data and derive actionable insights that can help your business grow. Contact us for assistance with your businesses data challenges and opportunities.


1 “Strategies for Driving Adoption and Usage with BI and Analytics”, The Eckerson Group/BARC, March 2022.

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Keiter Technologies

Keiter Technologies

Keiter Technologies focuses on serving businesses with their strategic technology needs through data science, cybersecurity, and IT audit and consulting.

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