By Tim Segall, Chief Technology Officer at Infogix

When IT is the only department capable of leveraging analytics tools and preparing data for business users, data requests can quickly pile up as they pour in daily. Competing IT priorities often shift these requests to the back-burner, creating a backlog of tasks that is not only frustrating for overworked IT resources, but also to the users who are awaiting results.

The reasons for this gridlock? Highly technical legacy tools that require expertise and lack agility, and an ever-increasing number of business user requests for data. The result? IT resources who spend their time fulfilling data requests from legions of business users, and business users who must wait for days or weeks for results that may be outdated and irrelevant once delivered.

This is, by any measure, a losing data strategy. Valuable IT resources should spend the majority of their time on high-value tasks. At the same time, business users need to develop a deeper understanding of how to effectively leverage data, and take an active role in applying analytics to generate better business insights. This is how organizations can gain an advantage in today’s competitive business environment.

The Consumerization of Data

The demands of an on-demand economy have impacted how we do business. Today’s consumers are savvier, and expect fast service, quick delivery, and quality products. Data consumers are no different. These business users are becoming more educated about data and its potential, and are ready and willing to be active participants in the process of data analysis. They just need to be equipped with tools and tactics to make them less reliant on a scant few IT resources. Enter self-service data.

In the past, the most burdensome part of the data analysis process was data preparation, or the process of gathering, combining, cleansing, structuring and organizing data so it can be analyzed as part of data visualization, analytics and machine learning applications. Indeed, Gartner still estimates that up to 80% of data analysts’ time is spent on these remedial tasks. Cumbersome ETL and other inefficient tools contributed, as well as inadequate data governance that made finding and combining data sources difficult.

Self-service data democratizes analytics, allowing a new crop of users to engage in analytics with minimal technical skills. Agile tools allow users to access data, run reports, and perform analysis tasks with transparency, eliminating “black box” processes that leave users doubting data results and wondering how conclusions were reached. Best of all, these processes are repeatable and allow for users to stop midstream, ask questions, collaborate, and make adjustments, saving both time and effort. With this new generation of tools, businesses can speed up the process to run reports and gain deeper insights, increase flexibility and enable business users to take an active role in data analysis to drive a data-driven culture.

Benefiting from Self-Service Capabilities

With modernized self-service analytics, businesses in any industry can empower more users to perform analysis, reducing the strain on IT resources and redirecting them to high-value tasks. A great example of this comes from the banking industry.

A bank’s IT department was receiving 20-30 data requests daily. For each request, IT had to develop requirements, gain approvals, and allocate costly, highly technical resources. On average, each request took 3 to 6 weeks to complete. When IT finally finished a task, the data was typically outdated and no longer valuable, which only raised new questions, required updated information, and created a never-ending cycle of dissatisfaction.

To combat these challenges, the bank implemented an all-inclusive tool to automate the process of logging data requests, created an agile process for provisioning results, and stored data extracts in libraries with reusable components for business users. As a result, business users were empowered to easily acquire and leverage data for analytics in hours, not weeks, and eliminated the need for recoding or development work.

With an automated process in place, business users prepared their own data and no longer had to wait 20-30 business days for their information. They leveraged timely, relevant data almost immediately. In addition, this automation efficiency freed up $500,000 in resources for other projects within 18 months.

This is just one example of how empowering users with easy data access and agile tools can free up valuable resources, increase efficiencies, and generate more data value for profitability and boost growth.

About the Author:

Tim joined Infogix in 2018 with the acquisition of Lavastorm, where he served as chief executive officer. Today, as Infogix’s first Chief Technology Officer, Tim brings to the organization extensive expertise and a proven track record of setting strategy and overseeing the full lifecycle of product development through delivery. Prior to Lavastorm, Tim held C-level positions at Zaius, Inc., Genesys/SoundBite Communications, and ManageSoft. He holds a bachelor’s in computer science from the University of Queensland, Australia.