It’s not a lack of data that’s holding companies back from digital transformation. Data is pouring in from more sources than ever. It’s not that analytics aren’t available. Businesses have access to rich descriptive analytics to build profiles that answer the “who” questions and diagnostic analytics to answer the “why” questions. What they lack is the mechanism to use that knowledge to drive changes in business processes. What they need is prescriptive analytics that translate data into action.
Why Business Users Trash Analytics
The inability to translate data into action is why the vast majority of digital transformation projects fail. Say you’re a data expert at a bank, and you build AI models that suggest a new approach to increase customer responsiveness to an offer or find a way to improve customer satisfaction with a customer management workflow change. This information can help people in specific business units do their jobs more effectively, but it’s presented as a spreadsheet, so nine times in 10, it will end up in the trash.
The problem isn’t the data team, and it’s not the business users. The issue is that there’s a disconnect between the data team’s findings and the business group’s ability to operationalize those insights. The tools the data team uses are built for analysts and data professionals, not business users. As a consequence of that, the reports these tools produce don’t show business users how to optimize their journey and fit new processes within their existing workflows.
AI-Driven Business Intelligence Apps Can Bridge the Gap
So, what’s the answer for companies that are currently stymied in their digital transformation goals? One team (data and analytics) produces the insights necessary to make the jump to more efficient, customer-focused and data-driven operations. But the group those insights can help, business users, don’t get the actionable instructions they need to operationalize the insights. The holy grail in this scenario would be the ability to use data to build workflows.
But most enterprise workflows are complex, and the systems people use to control workflows don’t allow users to embed data into workflows out of the box. For example, enterprise systems that control workflows at a financial institution tend to be enormously complex, and that prevents the bank’s data team from injecting data into the workflow. Instead, the team gives the data to business users, who don’t fully understand how to apply it — and the gap between data and action grows. AI-driven business intelligence (BI) apps that can build workflows in the BI tool can bridge that gap.
Give Users Process Changes, Not Spreadsheets or Reports
Digital transformation demands a framework built on how organizations actually work. To return to the bank example, how many people are involved in a loan decision? Do they have easy access to all of the data they need to make decisions as the application progresses, or do they have to toggle back and forth between systems? To achieve digital transformation, the bank’s leaders have to find a way to simplify the decision-making process for loans — and hundreds or even thousands of other processes.
That’s true across the board for industries. Think about how processes work in any organization — for instance, how hospital personnel schedule patient procedures to maintain optimal bed utilization, how a procurement department tracks inventory and anticipates needs, etc. Too many companies are using spreadsheets to put siloed data together. But with so many apps in the cloud and systems using APIs to ingest and communicate data, there’s a real opportunity to put machine learning to work instead.
Closing the Gap Between Insights and Action
A BI app that is centered on business users (i.e., not code-intensive), capable of ingesting enterprise system data and using AI and Machine Learning to not only identify what is happening but why it’s happening and how it’s relevant to users performing individual tasks can finally operationalize the insights data yields. For companies that are seeking digital transformation but falling short because business units are unable to adapt insights to processes, the right BI tool can be a gamechanger.
The rate of failure in digital transformation projects suggests that digital transformation will remain a top concern for business leaders in 2020 and beyond. Translating data into action is the key to overcoming the challenge. With a BI app that is capable of taking in data from enterprise systems and cloud-based apps and building workflows, companies can bridge the gap between data and action — and achieve the digital transformation they’ll need to succeed in the years ahead.
