Process Design

Sumesh Menon

Process Design and thinking have made profound changes in the past few years after AI made its journey into existence. Companies used to have independent systems for operating their business functions and their systems were designed in an era with trends in operational efficiency not knowing on how the future is going to take the turn for these systems to step up with the AI transformation.

With ERP systems taking the market companies started to rethink their system operations and started to have their business operations implemented with big shops like Oracle and SAP with their product offerings. These systems offered many high-end solutions and complex business processes for different industry requirements to be implemented with much ease with their vanilla offerings.

When the operations where more complex these ERP systems were tailored to do many process changes as the need of time for the businesses, and it offered much more at the time where the business could rely on these systems to generate automated reports, alerts for failures, closing the businesses month end operations with posting to General Ledger.

With the advent of AI and machine learning the perspective of process thinking and design have now changed a lot more variant. This creates new insights that help improve supply chain decision-making, all the way from the improvement of front-line operations, to strategic choices, such as the selection of the right supply chain operating models and right supply chain for the product or service.

The business processes which were earlier built on these ERP systems and internet technologies can now with AI bring a complete set of process re-thinking for companies to start look at their processes; and how this can now change to be more efficient from the previous version. AI and machine learning can do things which the ERP systems alone could not offer to do on their own.

Artificial intelligence and machine learning with big data analytics can help business to inform and optimize design choices with cognitive thinking making humans smarter with planning and decision-making process faster and more efficient. With Blockchain technology and big data, supply chain analytics can be more proactive and responsive that help business to get a wholesome picture of each entity within the supply chain to realize the solutions that can be customized and tailored for the customer needs.

Some of the technological areas where AI can really transform business operations and lead to process re-design are with the Vision systems, speech systems, natural language processing, expert systems, machine learning and Robotics process automation. Also, this can help with better planning and scheduling of operations in manufacturing and warehouse functions.

While the automation can replace all the repetitive tasks with robots that operate with a pre-defined set of rules engines, AI can further enhance ERP processes with operational data to learn from and be cognitive enough to help make better operational decisions with machine learning techniques.

AI combined with ERP system with operational data managed by Big Data analytics can reshape the companies today in their process redesign thinking and application to a greater level of re-engineering. Banks, Health care, Insurance companies are some of the verticals which are already using AI to do some of their repetitive tasks and with Chat bots to interact with humans to provide answers to frequently asked questions or problems making customer service faster and more efficient.

While this brings a fear of the jobs being replaced by AI but the other good that we can see from AI is same personnel can focus on other activities within the organization to be more productive and help AI with providing more information to make and build it more robust each day to help these AI systems function more seamlessly.

Creativity comes with “just connecting things”; many smart business moves come from linking products or services that seem independent from one another. Once we identify which combination of activities can help make it more meaningful and better in value then we should combine those to make a better deliverable product

IOT can help provide more value to AI by having connected systems talk to each other. Systems generate huge data which can be used to learn the patterns of their behavior, and these can further be tailored by AI for the operational decision making by making meaningful cognitive inferences to help business function more effective. The Internet of Intelligent Things makes IoT applications realize their full potential. Artificial intelligence and machine learning bring more detailed data insights to the table at a faster pace. Enterprises are looking forward to making use of internet of intelligent things to reap the benefits

With AI and IOT companies now need to re-think on how their end-to-end process can be transformed which now operates on just the transactional processes and operations to a much bigger transformation; that can help more strategically while operating and making use of the connected systems.

Greater Operational Efficiency

Predictions made through artificial intelligence based on the patterns learnt are highly useful in terms of increasing the operational efficiency of the business. Combined in-depth insights obtained through artificial intelligence can be used to improve the overall business processes, which can result in increased operational efficiency and decreased costs.

With accurate predictions based on the patterns, you can get insights about cost and time-consuming tasks in your business and automate them to increase efficiency levels. Moreover, for companies working on a big scale with high automotive and engineering, the insights obtained through IOT and AI systems combined can help them to re-design their processes, improve equipment setups, replenish stocks ahead to save on unnecessary fixed costs.

Greater Accuracy Levels

Human brains are limited to perform certain tasks at a certain rate, and when the minds are not operating at the same levels, which is not the case as with memory of systems, we are even more prone to making errors.

The Internet of Intelligent Things has the power to break down large quantities of data coming and going through devices. The best part about this is that since the whole process is machine and software-driven, it can be performed without any human intervention, which makes it error-free and improves accuracy rates.

For example, banking and online purchase transactions are prone to high risks of fraudulent activities. With the combined power of human understanding and IoT machine learning and RPA techniques of artificial intelligence, potential frauds can be foreseen in advance, thus preventing any losses.

Prescriptive and Predictive analytics for better Analysis

IOT combined with AI will allow machines to perform predictive analysis. Predictive analytics refers to a branch of analysis that looks at existing data, and based on the outcomes, it predicts possible future events. IoT and AI can help make this predictive outcome and this can be further gone down with prescriptive analytics to deal with outcomes or how to select the best outcome which the company would want to infer.

Companies will be able to detect possible mishaps and failures in advance and work on their maintenance. Due to this, the chances of losses are decreased highly as conditions are being detected even before failure. This will add up huge benefits in saving costs of big companies and helping them to avoid setbacks in their business.

Airline systems can use predictive analysis to see the pattern of system functioning and even before the alert happens it can foresee ahead for the backups to avoid any failures that can cause downtime in the operations.

Increased Customer Success and Engagement

Customer satisfaction and engagement are the goals for any corporation. Companies are realizing the power of AI by enabling chatbots for interacting with customers. The customer data with their learning patterns can be used to provide them with a more personalized experience as per their choices and solving their queries accordingly.

Process Analysis can further be more effective once we focus on the right approach:

Contrast. One should identify—and challenge—the assumptions undergirding the company’s or the industry’s status quo. This is the most direct and often the most powerful way to reinvent a business or process as it always sees what next and what can be done to make it better

Combination. Creativity comes with connecting disparate systems to have connected to communicate to make it more powerful

Constraint. One should look at an organization’s limitations and consider how they might actually become the strengths.

Context. If you reflect on how a problem similar’s to yours was solved in an entirely different context, surprising insights may emerge which helps to uncover new ideas that can further be pursued for innovation or to strategize the facts for existing problems to resolve

Drones and robots are being used to automate human repetitive functions and processes and help shorten the cycle time and empowering them to drive the change. To fully utilize the benefits of AI, companies should rethink the process design and process improvement activities with AI into consideration. Product Managers and Functional owners should combinedly work together with the relevant business stakeholders in this transformation journey. This should start with high level design followed by detailed process flows and improvement metrics to show the cost and time efficiency prior and after the transformation design. AI is a means to sail through, it’s a beginning to a new era for transforming your business.

Article written by Sumesh Menon

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