Work is dead, welcome to workflows

Most contemporary pieces in the media and wider technical press that attempt to highlight the current focus on workflows and the technologies that support them start with a reference to the Wikipedia definition.

So let’s not buck that trend.

According to free encyclopedia’s current description, “A workflow consists of an orchestrated and repeatable pattern of business activity enabled by the systematic organization of resources into processes that transform materials, provide services, or process information.”

In other words, workflows define jobs.

They describe the component parts of a person’s role and make note of the actions that a human being needs to do in order to be considered productive in the workplace.

Why workflow matters

All well and good then… but where current discussion on this topic has often fallen short is in the deeper analysis of what we can gain from a more granular approach to work if we break apart the component tasks that go towards forming any given role, in any workplace.

We have used the words ‘human’ and ‘person’ already. But, as we know, the rise of Artificial Intelligence (AI) and all forms of Machine Learning (ML) have given rise to a new thrust to inject automation systems into the workplace.

Where a ‘robot’ can do the job of a human being, then it often makes sense to automate that part of the workflow. But we can’t apply that automation advantage if we haven’t defined the scope of a particular workflow in the first place.

Those robots can be real robots (or at least robotic arms or electronic vehicles), or they can be software-based chatbots or other forms of intelligence that gets delivered to users in the form of an application or web service.

Cross-fertilization

Used effectively, a digitally-driven workflow-based approach to work can deliver many efficiencies. Workflows enable jobs to be broken apart and fulfilled by multi-matrix teams where specialized individual skills and the benefits of cross-fertilization are championed.

If you work in a different department, different building, different team or different country to someone else in your company that you integrate really well with on a specific part of your role, then it doesn’t matter anymore, because workflows can connect people.

Naysayers who doubt the need to define workflows and move towards this approach should look inside their IT department. Software programmers and systems administrators have understood the importance of optimization for a long time now.

When a job (a compute function for application processing, analytics, storage etc, as opposed to real human job) needs to be done, then an efficient IT operation will look to see which technology platform, which cloud, which components (and so on) it should use for the best price/performance ratio before it is executed.

Why shouldn’t the same efficiency factor be directed at humans in the workplace? Answer: it shouldn’t.

Integrate, measure, rinse & repeat

Where workflows come full circle is in their ability to allow us to refine and get better at our jobs. We can now go through a process of job function integration and then measure the impact that that coming together of workflow components have had.

After we integrate, then we iterate, i.e., we pare back inefficiencies and we rinse out all the bad stuff, we add new augmentations and we form new connections to be able to execute each workflow more effectively the next time around.

This is why software developers talk about Continuous Integration (CI) and Continuous Deployment (CD) so often and this is the sort of approach to digital workflow adoption that is needed if we are going to feed the always-on web with everything that it demands.

The Internet is always-on… and now work itself is exhibiting many of the same always-on characteristics of the web itself. This need not be a stressful thing if we step back and define our workflows before we start.

Work as we knew it has changed. The good news is that lunch is still lunch, so go and have a sandwich.