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User Types in your Qlik Sense Self-Service Environment

User Types in your Qlik Sense Self-Service Environment

As the interest in self-service BI is picking up across a wide range of industries, different types of user groups are starting to emerge, spotlighting various levels and breadths on how self-service is conducted and to what extent.

While the adoption of self-service typically begins with the IT department, which sets up the infrastructure and usually develops the first apps for a couple of consumers, four distinct groups of customers can be distinguished within a typical enterprise environment:

  • Power Users or Data Champions,
  • Business Users or Data Visualisers,
  • Consumers or Data Readers and
  • IT or Data Overseers.

There may, of course, be hybrid user groups and each type will differ from each other in their level of interest, technical expertise, and the way in which they consume the data, but here are broad descriptions of the four main user segments.

Power Users or Data Champions

Power users are the most tech-savvy business users, who show a great interest in self-service BI. They produce and build dashboards themselves and know how to load data and process it to create a logical data model. They tend to be self-learning and carry a hybrid set of skills, usually a mixture of business knowledge and some advanced technical skills.

This user group is often frustrated with existing reporting or BI solutions and finds IT inadequate in delivering the same. As a result, especially in the past, they take away data dumps from IT solutions and create their own dashboards in Excel, using advanced skills such as VBA, Visual Basic for Applications. They generally like to participate in the development process but have been unable to do so due to governance rules and a strict old-school separation of IT from the business.

Self-service BI is addressing this group in particular, and identifying those users is key in reaching adoption within an organization. Within an established self-service environment, power users generally participate in committees revolving around the technical environments and represent the business interest. They also develop the bulk of the first versions of the apps, which, as part of a naturally evolving process, are then handed over to more experienced IT for them to be polished and optimized.

Power users advocate the self-service BI technology and often not only demo the insights and information they achieved to extract from their data, but also the efficiency and timeliness of doing so. At the same time, they also serve as the first point of contact for other users and consumers when it comes to questions about their apps and dashboards. Sometimes they also participate in a technical advisory capacity on whether other projects are feasible to be implemented using the same technology.

Within a self-service BI environment, it is safe to say that those power users are the pillars of a successful adoption.

Business Users or Data Visualizers

Users are frequent users of data analytics, with the main goal to extract value from the data they are presented with. They represent the group of the user base which is interested in conducting data analysis and data discovery to better understand their business in order to make better-informed decisions. Presentation and ease of use of the application are key to this type of user group and they are less interested in building new analytics themselves.

That being said, some form of creating new charts and loading data is sometimes still of interest to them, albeit on a very basic level. Timeliness, the relevance of data, and the user experience are most relevant to them. They are the ones who are slicing and dicing the data and drilling down into dimensions, and who are keen to click around in the app to obtain valuable information. Usually, a group of users belong to the same department and have a power user overseeing them with regard to questions but also in receiving feedback on how the dashboard can be improved even more. Their interaction with IT is mostly limited to requesting access and resolving unexpected technical errors.

Consumers or Data Readers

Consumers usually form the largest user group of a self-service BI analytics solution. They are the end recipients of the insights and data analytics that have been produced and, normally, are only interested in distilled information which is presented to them in a digested form.

They are usually the kind of users who are happy with a report, either digital or in printed form, which summarizes highlights and lowlights in a few pages, requiring no interaction at all. Also, they are most sensitive to the timeliness and availability of their reports.

While usually the largest audience, at the same time this user group leverages the self-service capabilities of a BI tool the least. This poses a licensing challenge, as those users don’t take full advantage of the functionality on offer, but are costing the full amount in order to access the reports. It is therefore not uncommon to assign this type of user group a bucket of login access passes or not give them access to the self-service BI platform at all and give them the information they need in (digitally) printed format or within presentations, prepared by users.

IT or Data Overseers

IT represents the technical user group within this context, who sit in the background and develop and manage the framework within which the self-service BI solution operates. They are the backbone of the deployment and ensure the environment is set up correctly to cater for the various use cases required by the above-described user groups. At the same time, they ensure a security policy is in place and maintained and they introduce a governance framework for deployment, data quality, and best practices.

They are in effect responsible for overseeing the power users and helping them with technical questions, but at the same time ensuring terms and definition as well as the look and feel is consistent and maintained across all apps. With self-service BI, IT plays a lesser role in actually developing the dashboards but assumes a more mentoring position, where training, consultation, and advisory in best practices are conducted.

While working closely with power users, IT also provides technical support to users and liaises with the IT infrastructure to ensure the server infrastructure is fit for purpose and up and running to serve the users. This also includes upgrading the platform where required and enriching it with additional functionality if and when available.

 

Missed last week’s post on the IKEA effect and its implications for self-service analytics? Read it here

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