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When facing the challenges of digital transformation, companies must focus on meeting customer needs in real time. Adopting technology that can unlock the power of their data—rather than simply expanding access—not only allows enterprises to be agile, but prevents the “brain drain” that comes along with a volatile employment market.
To do this successfully, business leaders are learning to move past mere artificial intelligence into the new world of cognitive automation.
1. Identify and codify business goals and the data to support them
To support managers who need to make decisions on the fly, relevant real-time data is critical—and that includes data that goes well beyond inventory.Labor r is also a primary resource, and making solid hiring decisions quickly is essential to the business. Having real-time data on people, constantly changing human resource laws, and even market demand predictions can make a huge impact on hiring decisions that are made.
Before establishing a live data-capture system, organizations need to know what they are using cognitive automation for. What decisions are they trying to improve? What typically makes the most impact? Mapping live data supports and feeds into the use of cognitive automation to enable rapid and intelligent decision-making.
A cognitive automation implementation specialist can help guide this process and help make a list of key data sources that are needed to carry the project forward. This might include Google Trends, weather feeds, commodity prices, or other external data.
Once the system is ready to map live data, it sends out crawlers that continuously search for and extract the data. It can pull from multiple sources at once-- like the cloud, ERP systems, or CRM. Next, it structures the data for an analysis that is easily communicated to business leaders. It uses a high-performance data engine along with unique algorithms to interpret information in order to reveal trends and other key metrics.
2. Build trust in the data and decisions
The C-Suite, pressed for time and responsible for hundreds of macro- and micro-decisions every day, can rely on cognitive automation to accurately communicate the “why” of decision recommendations. Being able to trust the technology to make the best possible decisions—for example, canceling an inventory order—frees up leaders to focus their intellectual energy on growth.
Cognitive automation technology presents recommendations and what-if scenarios in a way that’s easy to understand and provides support so users can always drill down on the “why.”
For example, if an enterprise relies on cognitive automation to schedule employees, it might receive a prompt to send home half of the workforce early during a holiday weekend. This might seem counter-intuitive, leaving leaders to question the validity of the recommendation.
Instead of just making the suggestion and giving the user an option to accept or reject, an intelligent system will present an option to view all of the data used to make the decision. This could be a graph showing consistent historical trends of sales declining and labor costs increasing during this particular weekend for the past ten years. This could also allow users to drill down further to see vendors or products that are typically affected.
In addition to suggestions, cognitive automation gauges the risk associated with a recommended course of action.
Advanced and sophisticated systems based in cognitive automation make it easy for humans to trust the decisions, thanks to a built-in natural language component.
If a decision is made to remove half of the workforce from the schedule, a manager can accept the option within the system with the click of a button or a few spoken words. With these simple and intuitive actions, all employee schedules will immediately be changed and employees notified.
3. Cognitive Automation at scale provides continuous learning
To truly create a sustainable future for businesses, cognitive automation technology must continue to grow smarter and make better decisions at scale without companies having to constantly reinvest more time and money,
The more decisions businesses make using their cognitive automation systems, the more data they have as a foundation for future decisions.. The technology learns by tracking the decisions that are accepted, rejected, and even contemplated. It breaks down each user’s decisions to uncover and connect trends.. This might include certain inventory order thresholds that are never crossed or certain times of the year that price discount suggestions are usually accepted.
As the marketplaces and societies we live in grow ever more complex and interconnected, the ability to automate decisions intelligently will be a key factor in enterprise success.
With the ability to rely on cognitive automation to drive and make decisions in real-time, based on concrete data, leaders are free to apply their human creativity and intelligence to the work only humans can do, all while trusting that their systems and processes are finely tuned to the needs and demands of their customers.
Early adopters will have a winning start in the race to the future.
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