Business Process Management (BPM) and Big Data Integration

Much has been said about Big Data in these recent years. 

After all, big data is what drives individuals, companies, organizations, and governments to work with the increasingly large data sets to mine for useful insights and information.

In the enterprise setting, it refers to the processes and tools with which the data is analyzed and presented so that people can make better-informed decisions. 

It goes without saying that most companies today are finding ways to leverage the massive amounts of data they have to provide input for management, operational, and organizational decisions.

Let’s examine the link between Business Process Management (BPM) and Big Data and how they interact with BPM implementations in promoting the further adoption of the next paradigm: Big Data.

Why Is Big Data Important?

Big data is important not because of the quantity of your process-related data, but rather what you actually do with it.

You can choose to take data from a particular source and drill down on it to discern answers that entitle you to reduce costs, reduce time, provide new insights for new product development and enhanced offerings, and more informed decision-making.

By combining big data and BPM as well as analytics, business-related tasks can be accomplished such as the following:

How Does BPM interact with Big Data?

A large majority of BPM platforms possess built-in capabilities to gather key process parameters and related data during execution of processes.

Most platforms also offer some combination of data analysis tools.

The owners of the processes harness this data to provide key insights about the process. Here are some common examples how:

Thus, BPM platform suppliers and vendors are not strangers to harnessing analytics derived from process data, which is just one of the important reasons why moving to a BPM platform may be recommended.

What is the data used for? Process-related data is further leveraged for predictive analysis in order to tighten up your current processes and analyze the effects of prospective changes to the process over a period of time. Many of these activities are regularly done on process-related data that has been accrued through time.

For multiple, complex processes running and collecting large amounts of data simultaneously, in several cases a standalone analytics engine connected to process data may provide a more holistic and deeper insight than the plain vanilla analytics by the vendor.

However, it is worth mentioning again that the refinement of analytics will vary from vendor to vendor.

All organizations run multiple applications, many of which possess shared data elements, such as customer and vendor information from master data sources.

Oftentimes, these master data sets are not synchronized from system to system. They can be missing key data elements or are otherwise entirely incorrect, which leads to erroneous reporting at the macro level.

Worse, data reconciliation across applications is time-consuming and often the veracity of the data can be questionable.

What are BPM Processes Used For?

BPM process may be used to do the following:

There are some cases wherein BPM can be used to transmit verified data back to your organization’s “core” applications after verifying reports and dashboards that are created through the analytics engine of your choice. This presents an opportunity to save on additional costs rather than making large-scale changes to your organization’s legacy applications.  

As we all very well know by now, one single change can create a far-ranging impact on the application if not done correctly, particularly when the application has outlived its lifecycle and is ready for decommissioning. BPM can also be harnessed to extract data from social media and further delve into it.

The undoubted synergistic relationship between BPM and Big Data is very often easy to deploy in small to medium size enterprises that use only a few core applications. As they grow and scale upwards, they choose BPM tools for quicker implementation and maximum flexibility. There are some cases when the BPM provider liaises with the Analytics provider to create a tailored solution where both companies work on the solution, with the BPM provider performing the integration. 

Yet a more critical reason as to why BPM succeeds in these organizations is because their organizational politics has not yet fully developed and entrenched in the company. Businesses that are rapidly growing often have teams that feel they can scale upwards as well, as opposed to larger, more stable companies where management teams often defend their homecourt, so to speak.

Larger companies (think multinational companies with several IT departments and business unit siloing) wherein applications have been permitted to scale with no true integration or synergistic relationship among each other can become a time and resource pit. Thus, larger companies may be better served by focusing on their core infrastructure and applications for analytics and slowly replace or integrate them into the BPM tools, or decommission unnecessary applications entirely.