Apps and tools, such as Microsoft Power BI, make it easy for users to visualize data and build interactive reports. These Apps allow for effortless sharing of dashboards through the Cloud. Each report contains individual interactive tiles that can be used to explore data, focus on a specific dataset, or conduct drill downs for deep dives. The data can be easily filtered to focus on specific data subsets.
Despite the power of such tools, including their general flawless performance, organizations seeking to use these Apps for better, faster, and more cost effective decisions get hobbled by a number of challenges.
- Data capture depends on timely and accurate input of key work-facing employees, who must input the correct data at the right time.
- Data models are managed by IT organizations that are one step removed from the consumers of the data and generally don’t own the actual data.
- The data that’s presented in the reports and dashboards takes advantage of the power of the tools and various visualization capabilities, but the story presented is not clear. As a result, the data is not actionable, begging the “so what” question.
- The data presents an impressive snap shot but fails to support better decision making.
Organizations generally fail to realize that implementation of the App is only the first step in their journey. To make their journey successful, they must implement a number of programs to enable the full potential of their tools.
Designing relevant reports
The tendency of the report and dashboard developers, is to deliver a “wow” experience for the user. This is evidenced by the vast array of capabilities of the App, as well as the ability to build a plethora of charts and graphs. Complicated dashboards, with the ability to drill down into the data, are useful for data analysis and analytics, but not useful for business reporting. When designing a reporting system, the designers must take into account what questions their clients are trying to answer and what story they are trying to convey.
It’s become a cliché, but junk-in-junk-out is an expression that applies to App functionality. The quality of reports is only as good as the data in the system. Developing and implementing a data governance committee, that covers multiple functions that data crosses, is necessary to increase data quality. Overtime, data governance will eliminate data quality concerns. As the quality of data improves, so will App usage, resulting in more people willing to use the tools for reporting.
The tools can be used for 3 key purposes: 1) Reporting that requires high quality data; 2) Internal resource management that requires efficiency and effectiveness metrics and moderate data quality 3) Analytics and forecasting that require access to a variety of data that is linked in the data model with moderate data quality. Management is generally interested in using the tools for reporting or internal resource management; however, the highest value of the tools and the highest ROI is derived from gaining insights through analytics and forecasting. For organization to reach the levels of sophistication to be able to take advantage of these tools for better decision making requires a journey. To build skills, get quality data, and learn to trust the tools for better decision making, is the journey that must be taken.
Training and competency building
Users require training so they can easily navigate Apps and not rely on experts to do this work for them. Organizations must drive 10% to 15% of the organization’s employees, to gain sufficient skills to open and use their Apps on a regular basis to handle common data queries. 25% to 30% of the managers must know how to open and consume the dashboards regularly. Training can be delivered through a variety of venues, including classroom training, recorded on-demand video training, access to commonly asked questions database, PowerPoint training decks, and OneNote reference materials. The goal is to help employees easily and readily find answers to common questions on App usage. Some of our clients have discovered that training must be mandatory for certain populations, such as managers who should know how to navigate tools and filter data. Training requires repetition before it sinks in. Monitoring attendance and how often people access the learning sites will provide insights into how broadly and deeply knowledge is being built in the organization.