Data Mining

Automating workflow management and processes through streamlined data analysis

13th Dec `16, 04:49 PM in Data Mining

Spending on business process management (BPM) software was predicted to grow by 4.4% in 2015 to reach a…

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Mohammad Farooq Contributor
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Spending on business process management (BPM) software was predicted to grow by 4.4% in 2015 to reach a worldwide spend of $2.7 billion.

Even with these bullish figures, Rob Dunie, Gartner Research director, still stated that,

Managing business processes effectively is a difficult challenge for today’s business leaders, because many of the systems that are used within processes are rigid and difficult to change rapidly.

He further stated that,

The ability to provide more ‘joined up’ insight into business processes through the use of analytics — combined with support for the people involved in processes, allowing them to take advantage of this insight — is what differentiates today’s iBPMS (Intelligent Business Process Management) market from earlier BPMS technology markets.

Undeniably, any process that hinders innovation is bound to have a difficult time sticking around let alone succeeding in this age of social, mobile and cloud technologies.

How can on-demand fulfillment be satiated?

To avoid having rigid and slow business processes; speed, adaptability, insightfulness and better engagement are fundamental.

On-demand business framework

The on-demand business framework

Today’s reality is that advancements and increased adoption of technologies including; social, mobile, analytics and cloud (SMAC) which fuel innovation, continue to be the reason why todays businesses have a greater competitive advantage and therefore a better chance of success in their endeavors.

What’s more is that when businesses (especially, rigid and slow ones) don’t maximize and leverage on the use of big data and analytics, they crutch themselves and forfeit a huge competitive advantage. In an increasingly on-demand economy where instant customer satisfaction is increasingly demanded, instantaneous insights, through big data analytics, can make all the difference.

Big data analytics enhances a business’s ability to:

  • Gain almost instantaneous insights of information.
  • Quickly and appropriately adjust business rules and processes and adapt them to changing circumstances and
  • Provide more engagement and an overall better experience for their customers whether internally or externally.

How does data analytics relate to workflow management?

Workflow management or business process management (BPM) can be broadly understood as the automation of; business processes, administrative tasks and the management of user interactions with a view to improve an organization’s processing efficiency.

Effective automated workflows, allow businesses to for example:

  • Assign and apportion tasks to workers while giving provision to monitor and track the state of all assignments,
  • Send notifications when material is modified and
  • Confirm that documentation has been reviewed and approved by appropriate workers before it’s published

Through SMAC technologies, business processes are transformed from being ends in themselves to being a means of providing a more sophisticated system of engagement.

In essence, SMAC technologies allow businesses to understand how workers connect, share and interact with data, their coworkers and their customers. Therefore, data and process are interrelated and management should be about both.

When an organization uses workflow management to understand data and its stakeholders, (including how the data is used to make informed decisions; easily, rapidly, measurably and routinely) business rules and processes can then be adapted almost instantaneously to provide better customer experiences.

Data analytics, the cornerstone for automatic workflow management

By analyzing collected data, rules can be developed and these rules are the basis for developing intelligent business processes that allow for better execution of interactions with customers in social, mobile and cloud environments.

In essence, since information is used to make decisions in workflows and processes, big data analytics is fundamental in filtering the information and adding value to it especially in the decision steps of business processes.

For example, it is only when data from social media is processed through data analytics that it begins to make more sense and allows for business rules and processes to be executed. Without the insights from analytically supported business processes, all that you have is an unfiltered disparate data repository that can hardly be used to understand the customer or take appropriate action.

Which technologies and assets are used in workflow management? 

In as much as most organizations have gone digital, workflows are still quite manual. For example, documents are still manually uploaded to the cloud and then manually attached to emails for sharing.

Tools like SharePoint and Office 365 are shaping the future of workstyles in a world of mobile, and are helping to bridge this gap. However, there is still a lot of room for tools to bring such technologies together for a more streamlined workflow.

A good workflow management suite or BPM suite can vary considerably according to the technologies and assets that a business decides to integrate. However, typically, most BPM suites are used for digital workflows, system monitoring and reporting.

Capturing data from social media, bar codes, digital forms on websites, emails and line-of-business software’s, (e.g. accounting software’s), IOT devices, among other sources will determine the breadth and scope of the process automation.

All these technologies are touchpoints for how data is gathered and then analyzed in order to develop processes, adapt them and use them to gain insights to serve customers better.

Conclusion

When social, mobile, on premise, and cloud technologies are put through the lens of streamlined data analytics, workflows can be more easily automated. Through workflow automation, businesses can efficiently and effectively connect their workers to any job or project that needs attention, in order to deliver the best results to customers.

Through streamlined data analysis, better processes can be put in place to take advantage of workflows that bring all stakeholders together, through several different devices, across diverse networks, traversing different locations and all this happening almost instantly.

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