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SmartData Collective > Analytics > Understanding User Expectations
Analytics

Understanding User Expectations

LyndsayWise
LyndsayWise
5 Min Read
Understanding User Expectations
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Self-service access to analytics is becoming a key component when trying to expand BI and analytics access throughout the organization. For SMBs, this is especially important. Organizations need access to information that is relevant to business pains being experienced and to plan for the future. Analytics can also be used to identify trends and whether the right steps are being taken to move to the next level.

Self-service access to analytics is becoming a key component when trying to expand BI and analytics access throughout the organization. For SMBs, this is especially important. Organizations need access to information that is relevant to business pains being experienced and to plan for the future. Analytics can also be used to identify trends and whether the right steps are being taken to move to the next level. The reality however, is that data and the use of analytics are only as good as what’s done with them. Information is required on a daily basis within most, if not all, job functions. But simply having BI doesn’t lead to business value. Organizations need to implement solutions and integrate them within business processes so that they can be acted upon. From the perspective of users, this means meeting end user expectations and delivering solutions that are easy to access, interact with, and reliable. A good starting point is to look at the following:

Data access

Most business users do not have the expertise to join tables, identify the fields they need, apply algorithms, and defined business rules accurately without guidance. In addition, many users struggle with the fact that they are interacting with information they don’t fully trust. Therefore this needs to be done for them by developing a front end whereby the data layer is taken out of the equation. At the same time, the information being acted with needs to be governed in some fashion to ensure its accuracy and validity over time. Anything less means that information over time cannot fully be trusted. In cases where two levels of users exist and there are people within the organization who understand the data layer, there needs to be more flexibility in the way in which data is interacted with.

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Data discovery and interactivity

Once data is prepared, business users need to be able to explore the data the way they see fit. Interactivity needs to be valid, in the sense that users need to be able to ensure that their data is joined properly (in the way that makes sense for their business questions, etc.). The challenge with this is granting users enough access allowing them to explore data without having to determine a predefined set of pathways, while making sure that they are unable to develop analytics based on wrong assumptions. Organizations, therefore, need to balance these two aspects to make sure that solutions are designed with a high level of flexibility to sort through data, but not too much that allows people to make the wrong joins or develop conclusions based on inaccurate assumptions.

Self-service and ease of use

Self-service takes this one step further by making sure that the tools used to support decision making and analytics are easy to use and match the level of expertise of the user. Within organizations this might mean having more than one type of access to ensure that decision makers can access data in the way that best meets their needs. One of the challenges of “ease of use” is that solutions are generally developed by IT developers. What this means is that not all user friendly, self-service solutions are actually self-service for everyone. To really achieve self-service it becomes important to make sure that implemented solutions are intuitive to those interacting with them.

Although BI users have many expectations, these three areas provide the basic requirements when developing interactive BI and analytics access points that support broader decision making across the organization.  

This post was brought to you by IBM for Midsize Business and opinions are my own. To read more on this topic, visit  IBM’s Midsize Insider. Dedicated to providing businesses with expertise, solutions and tools that are specific to small and midsized companies, the Midsize Business program provides businesses with the materials and knowledge they need to become engines of a smarter planet.

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