By Matthew Clemente, EVP at Lemongrass Consulting
People used to go to offices and ‘do’ work. That core business reality does still exist, but much has changed in the last quarter-century as a result of the deeper penetration of digital platforms, the arrival of cloud computing and the new application of intelligence accelerators.
In the new world of work, people still go to offices (social distancing notwithstanding), but where we once saw ourselves ‘do’ work, we now more widely ‘exist and engage’ inside so-called workflows.
Whether workflows are captured and defined on basic spreadsheets or more formalised Human Capital Management (HCM) and Business Intelligence (BI) systems, their presence enables us to start building data-driven businesses.
Driving the data-driven business
As the data-driven business now exists online, we are able to harness artificial intelligence (AI) and machine learning (ML) and bring its intelligent automation to bear upon business workflow systems that may not have been reinvented for decades.
The AI and ML adoption curve has been comparatively flat over these first couple of post-millennial decades, but the spectrum of workplace application use cases that these technologies have now been validated for widens every day. Where people perhaps just a decade ago still dismissed ‘robotics’ as a fanciful notion best confined to the movies, a tangible awareness of software robots (often simply just called bots) has now proliferated.
Automation power from software bots in the form of robotic process automation (RPA) can provide us with efficiencies that help manage and direct workflow systems for improved performance, all while lowering the total cost of ownership.
In the current era, we can now work to deliver customised implementations of these tools across the whole transept of an organisation’s operational base. Digital automation used prudently enables a business to utilise the same tool for a wide range of data and situations, which will all derive different results.
Orchestrated, automated and accelerated
As an illustrative real-world working example, if we look at automation efficiencies inside an ERP system like SAP, we can see a large number of diverse automations all being executed concurrently. There is some fairly complex orchestration behind this type of deployment, but these systems thrive on this kind of augmentation.
Well-engineered AI refines the strength of the digital DNA being woven at any given point in time throughout an organisation’s IT stack. We can now use AI-driven and ML-steered controls to provide intuitive acceleration created from patterns observed over time, thus broadening the functionality of the total system, system suite and application use cases in question.
Organisations who adopt this orchestrated, automated and accelerated approach can start to create new streams of autonomous advantage across all departments. Tasks that could be performed by software bots are taken away from humans, freeing up time inside the same digital workflows for more creative, higher-value, innovative work.
In our SAP example, we can also orchestrate elements of the workflow to happen at more cost-efficient times of the day. The business can move database-centric batch jobs to the evening so that higher priority, intensive jobs can be performed during the workday.
Human hand-off control
All of this happens under human control and observation, on our ‘watch’ throughout. We decide what happens when, where and how. Human operatives are needed to perform ‘hand-off’ functions where AI software doesn’t know what to do next. Although AI engines will learn more each time, they only know what they know based upon what data they are exposed to, obviously.
This is not some dystopian rise of the robots. This is a far more utopian view of the rise of software robots and the automation advantages that come with it.
Staying in our SAP systems administration environment, these benefits mean that system administrators and other operations engineers can spin up cloud services and start up systems in an automated way to perform auto-healing actions related to a variety of ERP system events. These could be security provisioning issues, maintenance tasks, data deduplication processes, or other forms of standardised system patches and fixes.
First steps to automation
Above all, intelligent automation must always be seamless and non-disruptive; applying these technologies based upon robust, tightly defined best practises by working with established partners who have experience across a variety of transactional and analytical use cases, is an important first step.
Innovative automation technology should be capable of shouldering the ‘grunt’ work (donkey work, if you prefer) that can lead to human error, workflow inefficiencies and ultimately result in the production of lower quality products and services.
Understanding that this opportunity exists is sometimes the hardest part; there is a cultural shift needed here among C-suite management and throughout departmental divisions all the way down to the most junior employees. As an overriding principle, the business must realise that automation efficiencies should not be driven from a sole point of top-down edict. This is because bottom-up workflow aspirations and goals from worker stakeholders must form part of every organisation’s wider automation strategy.
People will still go to offices and workflows will continue to evolve, but user experience (as a precursor and conduit to customer experience) must now be part of every organisation’s operational strategy. If automation can improve any aspect of that total process, then it should be brought online.