As the business world continues to evolve, technology is becoming more and more intertwined in our everyday work. Whether this is in the form of new opportunities for automation or the rise of new data users, it’s an exciting time for companies who can take advantage of the technology at hand in order to improve.
One such trend is the rise of the self-service analyst, an individual who leverages the advanced technology at hand to inform business decisions. While this person will not replace the data scientist, they will take on an ever-expanding role in the coming years, blending their intuition with technology to analyze and provide insights.
The Rise of Self-Service Analytics
In fact, according to Gartner, Business Intelligence and self-serve analytics are changing the way organizations look at hiring and analysis.
“’The trend of digitalization is driving demand for analytics across all areas of modern business and government,’ said Carlie J. Idoine, research director at Gartner. ‘Rapid advancements in artificial intelligence, Internet of Things and SaaS (cloud) analytics and BI platforms are making it easier and more cost-effective than ever before for nonspecialists to perform effective analysis and better inform their decision making.’”
As the environment shifts and businesses embrace a data-driven culture, self-service users are set to exceed data scientists in analytics outputs within the next year. While we discussed the importance of data visualization in a recent blog, we would today like to turn our attention to potential pitfalls and what you can do to avoid them.
Challenges in Achieving Success as the Data Stacks Up
In his article discussing the “Data Explosion” taking place, Digitalist author Chris Johnston warned that the biggest threat to creating a successful insight and analytics team is that of becoming too data-rich and insight-poor:
- They accumulate vast stores of data that they have no idea what to do with, and no hope of learning anything useful from.
- To add to the problem, a lot of data has a lifespan. At some point in time, it becomes no longer relevant, inaccurate, or outdated. But often it is held onto anyway in the mistaken belief that someday it might come in useful.
- It’s important to remember also that collecting and storing data costs money: data requires storage and electricity to power it. And, if the information is sensitive, attention must be spent on security and data privacy, especially in the new world of enforced GDPR compliance.
- Of course, the problem becomes even bigger when we take into account the predicted growth in the data companies will produce. In short, if a company is already struggling to store and analyze its own data now, it will be drowning in data in the next few years. IDC predicts that over the next three to five years, most companies will have no choice other than to commit to digital transformation on a massive scale, including fundamental cultural and operational transformations.
Finding the Truth in Your Data
Your data is only as good as your people’s and technology’s ability to slice and dice it. In order to get the information and insights you need, it’s important to build a pathway towards understanding and using the data to your advantage.
“’If data and analytics leaders simply provide access to data and tools alone, self-service initiatives often don’t work out well,’ said Gartner’s Ms. Idoine. ‘This is because the experience and skills of business users vary widely within individual organizations. Therefore, training, support and onboarding processes are needed to help most self-service users produce meaningful output.’”
Preparation and Sponsorship
No matter how easy-to-implement or easy-to-use an analytics or business intelligence platform is, getting users enthusiastic and ready to use the software should be your primary focus.
In order to make this happen, companies need an authoritative and charismatic business leader who can act as a project sponsor and who can keep the project on path and the employees motivated. Keeping the enthusiasm high during training could be another challenge, so it’s important to keep a constant reminder of the benefits this implementation poses—to employees’ jobs, work/life balances, and career growth.
Onboarding and Training
Following the implementation and deployment of a business intelligence platform, leaders need to work with their partners to ensure that employees know how to turn vast swaths of data into useful information.
“Data and analytics leaders must support enthusiastic business self-service users with the right guidance on how to get up and running quickly, as well as how to apply their new tools to their specific business problems,” said Ms. Idoine. “A formal onboarding plan will help automate and standardize this process, making it far more scalable as self-service usage spreads throughout the organization.”
Embrace and Empower the Self-Service User
As you work to instill a data-driven culture at your organization, there are many paths to success. Whether you start with informative dashboards or a long journey to in-depth analytics and insights superiority, the best way to make it happen is to make a plan and to get started. At MIBAR, we’ve helped companies across the Northeast to implement the technologies and processes they need to build their business and prepare for the future.
We invite you to learn about the many options we support, including Power BI, Acumatica, and NetSuite, all of which not only empower the self-service analyst, but your business as well. Contact us to learn more.