3 November 2020

Governed Self-Service Solutions for Process Mining Users

3 November 2020

Governed Self-Service Solutions for Process Mining Users

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Introduction

 

As you might already know, Process Mining allows analysis of any process, on one condition – the process leaves a digital footprint in your enterprise systems and applications. That means it can be used in almost any industry—since enterprises tend to have similar sales, financial and operational processes.

 

But who uses the findings from process mining within an organization?

 

Digital transformation does not only mean replacing manual processes with digital ones, but also that more people have access to data and the ability to use it in on a day-to-day basis. 

 

In a constantly changing and highly competitive world, organizations need to be flexible and able to act rapidly toward changes and arising issues. This is why enabling business users to draw conclusions from data by themselves helps simplify and speed up operational changes and agility, particularly in the face of digital transformation.

 

In the case of data analytics, it becomes crucial to let users without an IT or analytical background be able to discover data, analyze it, make conclusions, and act.

 

Governed self-service solutions represent two ways of managing access to data – governed IT and self-service analytics.

 

What is it and what does it mean for Process Mining users? Let's walkthrough it!

 

Self-Service Analytics

 

To understand what a governed self-service solution is, we first need to define "self-service".

 

Historically, working with big data required highly-skilled professionals with a computer science background. But what if you want any manager to analyze large data sets and gain insights into business processes, without having to study for a four-year computer science degree?

 

That is what self-service is all about.

 

With self-service solutions, employees with a non-technical background can freely visualize, analyze, and make business decisions based on large data sets.

 

Currently, self-service is a term largely used in relation to business intelligence tools, meaning a data analytics approach that enables business users to access and work with corporate data. With self-service BI (e.g. Tableau Software, Power BI, etc.), statistical analysis becomes more efficient and accessible for everyone.

 

Despite this fact, self-service solutions are normally ungoverned, which means there are more security risks – it takes courage to open up corporate data with no control over who gets real access to it.

 

Furthermore, there is the risk of multiple "truths" circulating throughout the organization— people getting the same information in different ways, using different parts of the data.

 

The result? Discussion about how the analysis was conducted, instead of acting on findings.

 

Still, this doesn't mean we have to completely abandon the idea of self-service solutions—why not go for a combination instead?

 

IT Governance

 

Governed solutions normally mean that business professionals have no actual access to any piece of data they want to analyze – the data is owned by the IT department.

 

Contradictory to the self-service solutions, IT Governance gives IT departments an important role as an actual reporter.

 

As seen above, giving complete freedom to end users in terms of data could lead to insecurity and chaos; therefore governance is a must. Governance lets IT ensure the safety and constant update of data, keeping everything centralized and providing business professionals with information requested at a specific moment.

 

However, there are some downsides to this approach. On one hand, an IT department can become a bottleneck when requests come in from different departments.

 

On the other hand, to provide the necessary reports, IT needs to properly understand the business and what information is needed. Providing suboptimal or incomplete reports can lead to follow-up requests, further slowing down the decision-making process of those relying on this information.

 

Indeed, centralization is great, but when giving end users a bit of freedom, IT could specialize in more advanced tasks, and focus on data quality rather than reporting.

 

Advantages of Governed Self-Service Solutions

 

The compromise and solution to this dilemma is combining the best of both worlds – governed self-service.

 

This way an organization can disclose the data openly to its end users, giving them enough flexibility and power to deep dive into any dataset, and decide on further actions based on gathered insights. Therefore, it empowers people that need the information and because of less reliance on IT – speeds up decision times.

 

At the same time, by setting up a centralized common environment, IT still controls access to the data and guarantees security, making sure there is only one "truth". This normally means a shared environment is created by IT and used by business users.

 

Eventually, business users are still limited in their actions but have plenty of insight into the data without having to go through the IT department every time.

 

What Does it Mean for You?

 

When bringing data from process mining into your organization, multiple aspects will influence how it will be used:  

    • A centralized data model: to reduce the risk of multiple "truths" living throughout the organization.
    • Accessibility for business users: to speed–up the decision-making process.
    • Security: to make sure that people only have access to data they are allowed to see. .
    • User-friendly reports: to empower employees to use their own business knowledge and respond to issues faster.

With a governed self-service model, all the above aspects are integrated. On the one hand, the role of IT changes to developing a centralized data model in which end users can get the most out of their reports, while keeping data safe at the same time.  

 

On the other hand, it allows your business users to decide what questions they want to get the answers to and get them independently from larger data sets. By providing them with these necessary tools, they can operate as fast as the business itself and scale up performance accordingly.

 

Sven Bego is a Senior Software Engineer at UiPath.


by Sven Bego

TOPICS: Digital Transformation, process mining

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