This conviction is based on two pillars. First, on experience, I’ve gathered with setting up complex KPI dashboards with companies across the globe. Second, on features our dashboard product offers in that context and the feedback we’ve received from clients.
KPI Dashboards Can Drive Additional Value Without Substantial Additional Invest
The exciting part of the three KPI dashboard use cases I will introduce with this blog post is the following. First, none of the use cases is linked to colossal effort and costs. On the contrary, I consider those use cases as high-value add-ons KPI dashboards provide.
Quick Background About The KPI Dashboard Infrastructure
To present KPIs and information on a dashboard, you requirer a technical infrastructure. And to make that clear right from the beginning: I’m not talking about Excel dashboards but a sophisticated KPI dashboard.
Therefore, you need an infrastructure that collects, processes, calculates, and stores data. For example, with our product, the aWall, we operate a data hub, data warehouse, and specific data services tailored to these tasks.
Significantly, the data warehouse is tailored to process data from different sources/systems and to archive it in a structured way. Displaying the information on the KPI dashboard is finally only the icing on the cake. Most of the effort is linked to collecting and processing data but not to visualizing it.
Here Are 3 KPI Dashboard Use Cases You’ve Never Thought About
Data analytics has become an essential part of many companies’ performance management. And I’m not even talking about big data, machine learning, and stuff like this. On the contrary, I’m talking about a reliable and comprehensive data source to fuel analytics measures.
Many companies —tiny and mid-sized— we talked to in recent years told us that they do not operate a dedicated data warehouse. Conversely, data often is stored in databases of different systems. In we all know the term of data silos in this context. Such a setup massively hinders the process of data analytics.
KPI Dashboards Collects Data And Builds A Source For Analytics
As mentioned above, one crucial step to setting up a KPI dashboard is connecting data sources, collecting data, and storing it. Accordingly, since all the required data is already available, a combined and reliable source can be provided for data analytics without additional hardware, interfaces, or anything else.
The only step to take is to provide access to this data. Typically, this is achieved by using standard tools, for example, Tableau or PowerBI.
The benefits are apparent:
- Besides standard analytics tools, no need for additional infrastructure.
- You can access a holistic data platform
- You access the same data with your KPI dashboard and analytics measures.
Although we actively promote real-time KPI dashboards, weekly and monthly reports still have a right to exist. Moreover, they provide substantial, additional value. What we’ve learned when working with companies in the following: A considerable portion still relies on manual or semi-automated creation of weekly and monthly performance reports.
Also, from discussions with companies, we know that the creation process is painful. So what happens in detail? First, someone collects data from different sources systems. Afterward, companies use Excel to calculate and prepare raw data. As a final step, the Powerpoint gurus come in and create and pretty report.
In simple words: Creating reports most often is a time-consuming, inefficient, and error-prone process.
Since one vital function of KPI dashboards is —unsurprisingly— in calculating KPIs, it seems reasonable to extend the usage to creating historical reports, especially bearing in mind that all required data is already available.
With our product, the aWall, we provide a smart add-on that calculates historical KPIs (weekly, monthly, etc.). Subsequently, we offer KPIs in an easy-to-read report format on a defined regular basis.
Single-Source-Of-Truth Or API To Drive Business
The final use case we want to introduce is a more complex one. But also one that holds such enormous potential. Again, the core idea behind this is that the data warehouse contains data from various enterprise systems.
Now, setting up new systems or extending existing ones often leads to building required interfaces. Usually, building those interfaces is one of the major efforts and cost drivers. This is mainly because data is scattered across various systems in different formats and qualities.
Of course, middleware solutions are one way to tackle this challenge. Nonetheless, an alternative we consider as super-efficient is providing structured access to the entire data contained in the warehouse of the KPI dashboard.
We achieved this by setting up a standardized API that allows access to data in real-time. Thereby, systems that require specific data can efficiently utilize the existing API and request required data in a standardized, documented, and structured way.