When platforms like ERP, SCM, or any enterprise automation tools are first implemented, they become a snapshot of how the organization works at that particular point in time. However, as companies scale or encounter black swan events, these rigid systems are unable to react to these environmental changes. It is at this time when cognitive automation makes a difference.
Traditional enterprise platforms have historically focused on automating processes and wrangling efficiencies out of them. In a sense, they have locked in how a business operates in the most efficient way for that particular time.
When times were more stable, these approaches worked well. However, when the environment changes, the traditional rigid enterprise platforms have difficulty adapting to these changes. They usually require people manually dealing with these exceptions and making decisions that are outside these systems.
New platforms are emerging, utilizing data aggregation and machine learning to be responsive to changes. Rather than take a process mindset, these cognitive automation platforms are oriented around managing exceptions and making decisions, all with the underlying assumptions that things inevitably change.
At the heart of a cognitive automation platform is the harmonized data set across the enterprise and beyond. In a sense, it’s a digital twin of the organization that’s created by crawling and indexing internal, external, and physical data, and assembled into a virtual canonical data set. It goes beyond process and event logs -- this data set is a decision data model that includes transaction data, measures, and KPIs. And it’s not a static data set. It is continuously refreshed on a near-real time basis to establish an accurate data-driven background the decision makers can rely on.
Furthermore, it also records the history of decisions made in the organization to allow for future optimizing of recommendations for better decision making in the future. In essence, a cognitive automation platform learns continuously, making decisions based on the context, understanding complex relationships, and engaging in conversations with others. In this regard, cognitive automation goes beyond automating (or hyperautomating) monotonous tasks. It takes over the processes that require analytical skills and cognitive thinking.
Cognitive automation is a great leap forward compared to traditional, process-centric enterprise platforms. It goes beyond automating existing processes and is capable of mining a tremendous amount of data, making sophisticated decisions, and learning from your decision-making style continuously.
The capabilities of cognitive automation reveal their best in the changing environment, with rapidly shifting consumer preferences and black swan events.
In more stable times, automating existing processes is great for wringing efficiencies and making things go faster in general. It does allow employees to spend more time on more thoughtful, strategic issues. However, when the environment changes rapidly as it does today, it seems that people spend more time trying to go around the processes and deal with making decisions outside the system. These traditional platforms are not built to be fluid.
In these days of digital transformation, it seems that the solution proposed by traditional enterprise vendors is to undergo a complete replatforming of their solution that could take years to implement. But the problem is that, even if you had the time and resources to upgrade your ERP or SCM system, you’re just freezing your process-oriented enterprise platform to what works today.
It’s the “unknown unknowns” that these systems simply can’t handle.
Cognitive automation platforms address these challenges by focusing on decisions and outcomes rather than processes. For example, it will not simply automate the process of buying new material from suppliers but provide the logic and relevant data to drive strategic and operational decision making.
The impact of these decisions often cross technology and organizational silos and may impact multiple processes downstream. The right kind of cognitive automation platform can work in conjunction with these process-oriented solutions to “hyperautomate” the execution of these decisions. But what’s important is making the right decisions in the first place.
This is how smarter and more accurate automation happens.