As the business world continues to evolve, the way that people work has changed as well. Knowing this, in today’s low code world where finance and IT teams are moving from monotony to influence, the way that we consume data has changed as well.
The New Face of the Analyst
This is the reason that Host Analytics introduced Host Dashboards, why Microsoft introduced its Power BI platform, and it’s why Gartner recently announced that there is a new group of power users in the analytics field: Self-service users.
“Organizations are embracing self-service analytics and business intelligence (BI) to bring these capabilities to business users of all levels. This trend is so pronounced that Gartner, Inc. predicts that by 2019, the analytics output of business users with self-service capabilities will surpass that of professional data scientists.
“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.””
This, according to Gartner, is creating new opportunities for technology, and providing an opportunity for leaders to embrace the concept of a data-driven culture.
This is an important shift. If trained, enthused, and coached on how to use data, the end user has a leg up on the data scientist (at much lower cost)—due in part to his or her ability to draw from experience AND leverage new tools. Your current end users already know the company, know their role, and know what they need.
Empowering the New Analytics User
However, you can’t just implement a new analytics or dashboard-based product and just say “do something.” The move to self-serve analytics and the data-driven culture as a whole needs to be planned and executed to perfection.
“To avoid a descent into chaos, it’s crucial to identify the right organizational and process changes before starting the initiative.”
Build Confidence in the Concept
As you make the move to a promote a self-service analytics agenda, you need to help users understand the value of using such a platform. This requires a commitment to celebrating success. Sell the flexibility and availability to users and allow them to develop best practices for their unique needs.
Understand that There is Still a Long Way to Go before Self Sufficiency
Even if your people know their field, they aren’t data scientists. While the technology has brought them closer to self service, there is still a long way to go before users are self-sufficient. This, according to Forbes Contributor Brent Dykes, Director of Data Strategy at Domo, who recommends that someone is there to ensure the data is useful and consistent.
“[…] someone needs to ensure useful information flows out of your self-service BI tool on a consistent basis. Business users expect to receive relevant data from these tools, which means somebody must ensure the metrics and reporting options evolve to meet the changing needs of your organization.”
This, of course, leads to another concept—trust.
Help People Trust Their Data Outputs
One of the biggest issues that exists in business intelligence is a lack of trust in the numbers. In order to promote confidence in the numbers, points one and two have to be taken with gravitas—users need to be coached on how to do it better and successes need to be celebrated. Businesses generate boatloads of data, and without best practices in place, users can get paralyzed by it, turning this asset into a major liability.
“While it’s healthy to question one’s data, it can be debilitating when you lose complete faith in it and resign to “flying blind.” […] Once data distrust takes hold at an organization, it can significantly undermine all analytics efforts and remain a barrier until it is adequately addressed.
Dykes notes that you can still trust somewhat flawed data, so long as that data is precise.
“In the quest for perfect data, most companies will experience diminishing returns as they inch closer to a 100% match between two systems,” Dykes adds. “Rather than shutting down whenever you run across unexpected differences or anomalies, it’s important to build up your “dirty data” immunity system and tolerance for imperfections so you can continue to extract value from your data.”
Don’t Overthink It—Focus on What Matters
More data, more analysis. This creates a problem in its own right, in which decision makers experience paralysis from seeing too much. This creates two problems: Analysts can’t confidently present when executives demand massive meta-analyses, and decision makers fear committing when there are dozens of variables interacting with one another.
This requires a commitment to Key Performance Indicators, or KPIs. Even with all of the data available, some things just don’t matter as much as others. This is the beauty of the executive dashboard, which presents consolidated “big picture” information and smaller supporting information as needed.
New Users, New Technologies, New Competitive Environment
At Wipfli, we know how important it is to empower users and decision makers as they look toward new technologies. As a provider of industry-leading CIO Advisory services and reseller of leading finance applications including Sage Intacct, Microsoft Dynamics, Microsoft Power BI, Host Analytics, and more, we would love to help you improve your visibility and results with new technology. Stay tuned as we dive deeper into analysis, intelligence, and visualization in the coming weeks, and contact us for more information.