AI Trinity [Data * Design * Security]
Growth Strategy with a customer-centered supply chain
September 07, 2020
Supply-chain disruptions can be minor delays caused by a production glitch — or a big jolt from a global pandemic. Businesses are increasingly turning to technology to deal with such interruptions.
Companies are cutting supply chain complexity and accelerating responsiveness using the tools of artificial intelligence. Through AI, machine learning, robotics, and advanced analytics, firms are augmenting knowledge-intensive areas such as supply chain planning, customer order management, and inventory tracking.
Today, optimizing the supply chain is about much more than operational efficiencies. Indeed, the supply chain has proven to be a key driver of new business value and growth at the likes of Amazon and Walmart – provided it is entirely focused on hyper-relevance and customer value. That’s a tough proposition for businesses encumbered by fragmented legacy technologies and outdated one-size-fits-all supply chain models. With many processes still siloed and under-optimized, as well as over-reliant on manual activities and proprietary assets, today’s supply chains are not keeping up with the pace of change. Significant opportunities for improvement, optimization, and innovation are being missed.
In this era of constant change, customers are becoming the undisputed center of attention. Business growth is now about outsmarting the competition through speed and hyper- relevance, enhancing both customer experience and customer loyalty. It’s about developing the intelligence and agility to continuously adapt the whole value chain to what customers expect today – and what they’ll want tomorrow.
A modern operating architecture is essential for supporting the customer- centered supply chain and unlocking new growth. But it takes more than simply transitioning to a new ERP platform for instance.
Rather, it needs a complete customer-centric transformation of the whole supply chain. Creating a genuinely customer-centered supply chain means embarking on a journey of disruptive transformation.
With the transition to a more modern architecture providing the ideal opportunity for a radical reimagination of the end-to-end value chain, now is the time for enterprises to be reconfiguring their supply chains around the real- time needs of their customers.
- First, we need to be sure we’re headed in the right direction. That means setting a North Star vision to guide the transformation, articulating the customer experience we aim to provide, and defining the strategy, value case, and roadmap that will help get we there.
- Then, we need to radically rethink operations from siloed work to interdisciplinary collaboration across the value chain. That means taking a sledgehammer to any functional or organizational walls and siloes that are holding us back. It means organizing around the needs of the end-customer and driving toward the efficiency and agility needed for rapid customer delivery. Build the capability to dynamically micro-segment customers, supporting multiple flexible and sustainable supply chains that leverage external partners to share ownership of physical assets. Leverage analytics and “what if” scenario modeling to enhance operations and add value for the customer. Develop an “experiment on the go” approach to drive innovation in each segment’s supply chain.
- From experience-based, leader-driven decision making to data-driven decision making at the front line is another critical element. By blending the best of the human workforce with smart new technologies, you can help drive up the use of hyper-efficient automation such as “supply chain as-a-Service” mentality (plan, source, make, deliver) to refocus the business on growth through a dynamic, intelligent operating model and data-led adaptable workforce. AI has the biggest impact when it’s developed by cross-functional teams with a mix of skills and perspectives. Having business and operational people work side by side with analytics experts will ensure that initiatives address broad organizational priorities, not just isolated business issues. Diverse teams can also think through the operational changes new applications may require—they’re likelier to recognize, say, that the introduction of an algorithm that predicts maintenance needs should be accompanied by an overhaul of maintenance workflows. And when development teams involve end users in the design of applications, the chances of adoption increase dramatically.
- The supply chain is and always has been a people business. We’re moving toward a world where humans and machines are collaborating, not just coexisting. The result will be an efficient, sustainable supply chain that delivers better business outcomes. Hence, in this new environment, both machines and humans are essential: By collaborating in roles such as supply chain planning and inventory management, the combined power of humans and machines will create new sources of value for businesses. We’ve explored the nature of the new value-enhancing roles that will emerge and identified three new categories of AI-driven jobs:
- Trainers who help AI systems learn how to perform, which includes everything from helping natural language processors and language translators make fewer errors, to teaching AI algorithms how to mimic human behaviors.
- Explainers who interpret the results of algorithms to improve transparency and accountability for AI decision making and processes.
- Sustainers who ensure intelligent systems stay true to their original goals without crossing ethical lines or reinforcing bias.
- make more forward-looking, strategic decisions and spend less time on reactive problem solving. These planners will lead the charge in moving away from a traditional supply chain operating model, which is inflexible and slow, to a new dynamic model with true end-to-end segmentation. That means planning multiple supply chains that meet the needs of specific customer micro-segments as well as managing business relationships and exceptions. Concurrently, a new digital engineer role will emerge: a highly analytical, digitally savvy data scientist who manages, models, and tweaks the algorithms, alert protocols, and parameters guiding the automated decision-making planning systems. The importance of strong analytical skills will grow with the demand for human workers with a digital engineer’s skill set.
Anticipating unique barriers to change
- Successful transformations to the customer-centered supply chain follow a clear path with meticulously planned objectives. By establishing a phased approach for harnessing the power of a platform for the customer- centered supply chain, we can potentially guide an enterprise from initial roadmap and business case, through prototyping new solutions, to scaling them across the enterprise.
- By investing in a digital core an enterprise can acquire the ability to accelerate innovation, drive up personalization, shift from a process-driven to “event-driven” supply chain, and create exceptional experiences that retain the best customers and talent. And that hinges on pivoting your strategy: keeping one eye focused on core functional excellence and mastering the basics, while allowing the other to look toward the new capabilities and growth bets that will create future customer value propositions. Building blocks of the hyper-relevant enterprise at the core. Every journey to greater customer-centricity will be unique. No two organizations will have identical goals or operate in precisely the same business context.
- The potential rewards are huge. With flexible supply chain solutions, cost-effective on-time delivery, and new value-added services, the customer-centered supply chain provides a license for accelerated growth and enhanced customer trust. The impact? A $10+ billion company for example can potentially boost sales up to $100 million, enterprises can help pivot their supply chains wisely and plot out a roadmap to the simplified, flexible architectures that will support winning customer experiences – the source of future business growth and competitive advantage.
Organizing for scale
Finally, it is about placing innovation bets on which customer-centered supply chain networks are created. The top of the list is a ‘visionary budget’. The goal is here to have a budget to improve ‘time to value & results.’ We cannot see this as a tactical initiative designed for a narrow purpose but an opportunity to reimagine our business and implement the ‘accelerant’ tools like AI sooner than later. This will give us the license to differentiate, grow and take market share from our competition. Think big but start small by mapping opportunities to integrate AI with existing technology solutions. Until now, robots, big data, analytics, and other technologies have been used in parallel with people, but in isolation. Their role: improve process efficiencies. Now, with AI systems that can sense, communicate, interpret, and learn, all that changes. AI can help businesses move beyond automation to elevate human capabilities that unlock new value.