BPM and Digital Transformation
As companies embrace digital transformation, traditional Business Process Management (BPM) has evolved significantly from being purely workflow and document management to securing and enhancing business value. This transformation is disrupting enterprises across industry sectors, generating a need for re-engineering of their business processes. There are several advanced technology tools specifically designed to manage a scalable BPM. The digital BPM landscape is a combination of colliding segments with traditional BPM vendors, traditional Enterprise Content Management (ECM) vendors and new players from the burgeoning low-code space all overlapping and vying for a piece of the pie. But in the midst of the ensuing collisions and confusion, modern BPM tools of all flavors are finding their place as part of the enterprise’s digital transformation toolkit. In our point of view, digital transformation has three major objectives: efficiency, transparency and insight. Looking at the BPM space through these lenses provides a comprehensive view of this critical business functionality.
Through the implementation of advanced robotics technologies like Robotic Process Automation (RPA), businesses are automating their repetitive, manual, and standardized processes and experiencing immense efficiencies. Repetitive processes that are driven by rules are being automated. Even called the ‘second coming of BPM’, bots are capable of replicating human activity. Business processes that require human intuition are leveraging ‘intelligent automation’, like Artificial Intelligence (AI), that has cognitive capabilities. These technological revolutions are creating an efficient and innovative work culture where human and digital workers are operating side-by-side.
Exemplary user experiences require creating a seamless interaction between digital media, content and business processes. Many technologies are enabling an optimal customer experience by combining cloud-based BPM platforms. Though many business processes are fairly defined and rule-based, there are also many users who deal with tasks where the end is unknown, and the path may vary due to unpredictable work patterns. Now the only work around is to respond ad-hoc to every unscheduled event. With AI-powered technologies, tools are available that provide a dynamic workflow that emulates a human worker based on the input and actions made by the users. We are seeing more BPM manufacturers starting to include the ability to deal with these types of adaptive cases (Intelligent BPMS or iBPMS).
Just having access to this data is not valuable or enough. It requires a data strategy, a set of key use cases, and metrics to translate the numbers to business value
In 2011, a Gartner study predicted the impact that chatbots would have on organizations. Their prediction of about 85% of customer-enterprise communication happening without involving a single human, is well on its way to becoming a reality. There are several advanced technology solutions such as chatbots and intelligent voice recognition software that can enhance the customer experience by creating connectivity between process owners at various steps within the overall business process.
This aspect of digital transformation is the source of creating insights and meanings out of the vast amounts of information that funnel from the implementation of BPM automation and collaboration. Just having access to this data is not valuable or enough. It requires a data strategy, a set of key use cases, and metrics to translate the numbers to business value. Many companies are using data repositories such as data lakes, enterprise data warehouse, data marts etc., but their approach has been ‘tool first’ and strategy after. This is creating a gap in mining the right data, creating a repository of data properties, and understanding the user behaviors. Through leveraging analytics platforms like Qlik, Tableau and Power BI with data modeling techniques, we are seeing a trend of BPM solutions increasingly becoming more business value drivers than simply a functional support.
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