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We live in an increasingly volatile and interdependent world. Global factors such as COVID-19 shocks, trade policy shifts, workforce scarcity, the energy transition and the unpredictability of global superpowers have created an unstable environment. While the first priority is to ensure the health and safety of people directly affected, global leaders must also consider how these factors will indirectly impact those down the line. Indirect consequences include the current inflationary surge and the frequent scarcity of critical supplies. The operational shortcomings are impossible to ignore and carry the potential to create their own crises.
To survive in this environment, business leaders need to reassess their existing operating models to predict shocks, react quickly and reduce risk. Many organizations have deepened their understanding of their supply chains and deployed new value creation tactics – but more can be done.
There are digital solutions available that meet these needs, beat the competition, satisfy customers and reduce risk. While they are typically integrated across organizations through IT initiatives, we encourage function leaders to take some ownership over transformation and deliver outcomes faster.
In fact, according to a 2020 Accenture study, “future-ready” organizations see an average of 2.8x corporate profitability. Yet, few corporations meet this designation. While futureproofing and transformation may feel overwhelming, the following offers four priorities for companies to build the foundation and prepare for whatever may come next.
Connect and enrich data
As companies have developed and adapted to digital over time, leaders often find data is distributed and inconsistent across functions because of different systems and manual entries. The result? Slower access to critical information for decision making due to bottlenecking, manual retrieval, human error, etc. In a rapidly changing global landscape, employees should have immediate access to relevant, clean and enriched data to make mission-critical decisions just as quickly. This is important across functions, from sales and marketing to procurement or finance. At Aligned Automation, data is essential to our everyday work. That’s why 75% of our employees have advanced or higher-level abilities across Data & Analytics skills, in addition to industry and subject matter expertise.
Data enrichment, such as classification of purchase orders, sales orders, service agreements, and contracts into taxonomies, uncovers important hidden information within data. We also perform communication data enrichment, such as transcripts between customer and technical support teams, to provide decoded inputs for decision science. This variety of enriched data improves decision making for sourcing managers, contract managers, buyers, operations and customer facing teams.
Reevaluate – and then optimize – processes
It is common in workplace cultures to follow certain processes as they are decreed. However, rapidly evolving technology have made it possible to not only change the way companies approach data, but also how employees work day-to-day. According to IBM, a leader in the process mining space, “process mining applies data science to discover, validate and improve workflows.” The benefit? A more data-driven approach to internal decision making and resource allocation.
Leaders should evaluate and revamp processes to match new systems and technology capabilities. Where a document or action may have had to pass through several hands for approval in the past, it may now be streamlined or automated entirely.
Not sure how to start? Choosing the right partner and tools is critical. For example, we partner closely with Celonis in many client engagements for process mining and process improvements. A global leader in “execution management,” Celonis solutions have proven success across industries and supply chain operations, streamlining processes and allowing companies to work smarter – not harder.
One Aligned Automation client applied process mining to their procure-to-pay (P2P) process to improve the overall efficiency, eliminate rework and identify workflow automation opportunities for purchasing, ordering, invoicing and payment. The solution uncovered many opportunities for automation and simplification. It resulted in a 43% efficiency gain and 30% reduction in rework, which saves time and opens employees up to higher value work.
Utilize AI and ML capabilities
Companies that aren’t already applying intelligence to their data, processes and solutions are already behind. By 2024, Gartner projects 75% of enterprises will shift from piloting to operationalizing AI. And while 27% of those surveyed could attribute more than 5 percent of EBIT to AI initiatives, many more were seeing significant gains through cost savings across functions. Furthermore, the AI higher performers tended to see overall more efficient spending and had higher EBIT attributed to their AI initiatives. The predictive powers of artificial intelligence and machine learning offer leaders the potential to forecast issues before they become visible. While we cannot predict everything, we can minimize operational impacts, making it well worth the investment.
At Aligned Automation, we have developed collaboration predictions to help technical support teams decide when and why they should collaborate with peers for faster troubleshooting technical issues and reaching to quicker resolution. This solution is one example of many for how AI and ML can transform business operations for the better against unpredictable market conditions.
Start small, scale fast and sustain long-term
Oftentimes, enterprise organizations will take on transformation as a large-scale overhaul managed by the IT department. Another common pitfall is “paralysis by analysis,” or organizations that get stuck in pilot mode with too many solutions available. Because transformation is not an exact linear process, it may feel sprawling and unfocused if not properly prioritized.
Our engagement model takes an iterative modular approach to build confidence, focus and momentum from the ground up. For example, a manufacturing client desired a $100M value realization in one year. Using that macro vision of success as our North Star, we can help break this goal down into multiple targeted initiatives, chosen for potential value, speed and ability to scale. The organization is then primed for multiple outcomes: small failures allow teams to move on quickly with minimal losses and small wins build the momentum necessary to scale and see larger success. Scaling quickly is critical: it means the opportunity to capture more value and change in less time, enhancing resilience measures in our rapidly changing economy. Additionally, we take special consideration into long-term efficacy of our solutions to sustain success through whatever comes next.
Across all functions, leaders are dealing with the some of the most challenging situations of their careers, including recovering from a global pandemic, the war in Europe, workforce shortages and inflationary pressures. Building resilience through business operations not only decreases risks and improves business outcomes but may also protect jobs and enhance a sense of stability for employees.
Not just surviving but thriving in today’s world requires the digital transformation of operations including reliable long-term planning, supply chain modeling, deeper insights into supplier economics and real-time collaboration across functional teams with an ability to adopt and scale with proven technologies.
Be prepared for what comes next. Contact our representatives to learn how to you can futureproof your operations.
About the Author
Yuvaraj Pawar is a ML/AI Practice Lead at Aligned Automation with nearly 20-years of experience in developing complex solutions for the high-tech, oil and gas, banking, and pharma industries. He leads data engineering, ML and AI solutions design, development and process change.
The Aligned Automation ML/AI organization consists of more than 20 professionals who develop solutions using algorithms such as regression, decision trees, neural networks, deep learning, NLP and computer vision. The technical solution development team and data scientists design, develop and deploy solutions on multiple cloud and on-prem environments.