It has been a huge logistical effort worldwide.
Organisations, from government agencies to pharmaceuticals retail chains have managed to quickly scale up their distribution presence to make sure shots get into arms as soon as possible.
Today’s urgent global focus on COVID is just one, albeit critical, element of a broader requirement impacting enterprises, which the pandemic has thrown into sharp focus – the need to reimagine workflows in a more agile data-rich, and actionable in order to expedite the delivery of real value into people’s lives.
The pandemic hit businesses hard in the Spring of 2020, disrupting processes and continuity across the board, and enterprise workflow management was one such piece of these strategies radically impacted. All of this begs the question: How has COVID-19 inspired enterprises to refine and redefine those workflows to be flexible, smarter, and richer in data? And what kind of value can these reimagined workflows bring to the table?
In the industrial world, organisations rely on a complicated integration of business processes to execute big objectives. Trying to streamline this process with new data workflows often runs into problems. The data that would be fed into those workflows is spread out across distinct, unlinked systems, from legacy data management solutions to paper sheets. Some of the programs most constrained by this fact are people-centric initiatives, like Health, Safety, Security, and Environmental (HSSE) activities.
COVID-19 exacerbated this problem but also highlighted the importance of fixing it. The pandemic meant it was suddenly both business-critical and critical for public health to be able to track COVID-19 cases across the organisation, if and when they emerged, and feed that data into HSSE) protocols accordingly – a sort of internal contact tracing programme. For enterprises that had already created these kinds of workflows, this became a validating use case, allowing business leaders to quickly notify other employees about exposure within the organisation and plan work shifts accordingly.
However, for enterprises that didn’t have these kinds of workflows in place, COVID-19 showed how crucial it is to tightly integrate people, data, and workflows into an automated digital process.
Ultimately, the need for specific COVID-19 contact tracing hopefully won’t be necessary – but the workflows that that application was built on will continue to remain business-critical.
Not only has the pandemic exposed how enterprises are, or aren’t, bridging the gap between people and process in their works, it has also exposed how efficiently or inefficiently resources are being managed across workflows. COVID-19 changed how organisations manage resources for the better, impressing upon them the need to create more agile enterprise workflows that can allocate resources in a more dynamic and responsive manner.
In a COVID-19 specific context, that use case looks like tracking employee trends on cases, hospitalisations, and recoveries, and building customised triggers that respond with specific, targeted business actions based on employee conditions, such as automatically reassigning job duties to others based on the times that given employees or contractors may be absent for COVID-19 related reasons.
This kind of agile enterprise workflow management is vital for remaining flexible in an environment where adapting to a rapidly-evolving situation is key both to business continuity and employee health. However, the logic underpinning these workflows goes beyond COVID-19. If anything, these contact tracing and work-shift planning use cases highlight the kind of enterprise workflows that organisations should be modelling moving forwards.
That model should be able to: rapidly allocate resources to HSSE initiatives based on employee information received in real-time and also aggregate both site- and enterprise-level reporting on employee statistics. It should also be capable of configuring and managing new workflows based on workplace conditions as they evolve and capturing and integrating information generated across a diversity of data sources, feeding that data into higher-level decision-making processes.
Agile, flexible enterprise workflows need to move beyond the limits of traditionally static reporting systems. Those workflows didn’t work in a pandemic, and industrial organisations shouldn’t feel like they need to go back to them post-COVID-19.
For as disruptive as COVID-19 has been, there have been minor silver linings, lessons to be learned for the future. Refining and redefining agile enterprise workflows to ingest more dynamic, high-value data from industrial AI and machine learning models is the way forward for making faster, more adaptive business decisions. This new approach to enterprise workflows was tested with COVID-19 and passed with flying colours. Industrial organisations should map these new models of enterprise workflows across the board.
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