Combine Business Intelligence and Process Mining for Data-Driven Decision Making
Organizations today are under so much pressure to be everything all at once. They need to be transparent while generating maximum revenues and profits. They need to provide competitively priced products and superior service. They need to stay one step ahead of the competition and embrace the very latest digital tools and trends.
So how can organizations hit all these goals and succeed in an environment where speed and precision are so critical?
One answer: agility. Admittedly, agility may have been a buzzword for a few years now, but for good reason. This article will explore how companies can be more agile by empowering their workforce to make more effective decisions on the fly. And how that can be done using things like business intelligence and process mining. We’ll also explore how the current business intelligence market has influenced the growing process market, especially in making data more accessible to more groups of people and much easier to understand.
Gone are the days of top-down management, where higher management set direction and passed it down to their teams. To become a truly adaptive, thriving organization, all employees need to have the right tools and information to make fast, informed decisions.
The popularity and widespread adoption of business intelligence and process mining software are testaments to this approach, since both technologies help generate new visibility and valuable insights. business intelligence is more mature and well known. Process mining is following a similar path, especially when it comes to self-service access employees need.
Business intelligence gives end users input into business operations using key performance indicators (KPIs), performance metrics, reports, dashboards, and visualizations, all of which help with data-driven decision making. On the other hand, process mining is used for targeted insight into a company’s specific processes.
Process mining examines a particular process in its entirety, so users can identify bottlenecks, inefficiencies, and risks.
A key difference is that business intelligence focuses on data and local decision making, not the company’s end-to-end processes. Process mining goes a step further than business intelligence, by providing users with a holistic view of a process through a dynamic interface and other intuitive tools. business intelligence tends to use a static model of the process as a starting point to define KPIs and then watch them. But process mining starts by creating a dynamic process graph, allowing to analyze the most relevant data in real time.
Each are effective in their own way, but what if we could take all the best parts of business intelligence —easy visualization, simple reporting, and clear business context—and apply them to process mining?
In other words, what can we learn from business intelligence in order to make process mining even more successful?
Business intelligence started out as a means for a small group of people, sometimes just one person from IT, who could gain data insights, and spread this information to management. The next stage, self-service business intelligence, is less reliant on an IT gatekeeper, so analysts can create their reports for management.
Yet self-service business intelligence presents three real challenges:
Discrepancies: different people may interpret the same data in different ways.
Security: in most self-service business intelligence models, one user has control over all the data, when they really only access a limited amount.
Dependent: users may have to rely on one person to produce various reports, which lead to inefficiencies and bottlenecks.
In the past, when companies tended to favor horizontal reporting lines, both governed and self-service models worked. But now, companies can’t afford to wait for decisions to trickle down from upper management or rely on one person to support their reports. Additionally, security is clearly a major concern and most companies are doing all they can to minimize total risk.
Instead, companies are now recognizing—and striving for—the benefits of empowering the entire workforce to make everyday decisions using a bottom-up method. Such an approach goes together with the idea of governed self-service, where data is safe and consistent, but individuals can access specific data for their own reports and analysis. Governed self-service also enables non-technical management to gain even more insights related to decision making.
As reporting lines become more horizontal, business intelligence tools have become available to even more users on more levels. One of the factors that has driven this democratization of business intelligence tools—examples such as Qlik, Tableau, and Microsoft Power BI—is business intelligence’s powerful visualization capabilities.
Effective visualization in business intelligence is a byproduct of any governed self-service workload since more people need to obtain new information and insights from complex data. We now see a similar trend related to process mining.
While process mining is newer than business intelligence, it is following a similar path. Most tools are now at the self-service stage, yet UiPath is an early adopter of governed self-service. Companies realize that in order to gain the most value out of process mining, they need to equip all process owners with full process mining capabilities to make smart decisions quickly. UiPath Process Mining has early roots in business intelligence, which is helpful in linking processes to overall business strategy and making insights easy to understand, even for non-technical users.
Visualization, for example, is an important tenet of modern business intelligence, and one that other process mining tools often overlook. Visualization is driven by making insights easy to understand and contextual for users. UiPath Process Mining includes a patent-pending process graph algorithm that enhances the visualization and interpretability of business processes. It also includes the ability to easily view historical trends to compare and monitor performance to a previous period.
Overall, our experience in visualization and business intelligence still inspires how we develop new process mining innovations.
In order to remain agile, companies must empower their workforce. A direct way of doing this is providing tools that empower process owners to make effective and clear-sighted decisions. This is the only way companies can remain competitive in a fast-paced environment.
Process mining software can still follow some of the success business intelligence has had to make data accessible to a wider number of users. At UiPath, we strive to ensure UiPath Process Mining is as user friendly and effective as possible. And we’ve been able to do this by drawing on our experience in visualization and business intelligence.
However, it doesn’t stop there. We are constantly looking for ways to make our platform even better to suit the needs of the constantly adapting enterprise. Stay tuned for more developments!
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