Taking the Digital Supply Chain Journey: From Data Collection to Automated Systems

Bill Lam, Principal and Supply Chain Strategy Leader, Deloitte Consulting LLP
Bill Lam, Principal and Supply Chain Strategy Leader, Deloitte Consulting LLP

Bill Lam, Principal and Supply Chain Strategy Leader, Deloitte Consulting LLP

It’s no surprise that supply chain organizations today are facing new and constantly shifting challenges, leaving many of them feeling paralyzed. They are unsure about differentiating hype from what may cause disruption, how aggressively they need to act to not be disrupted, and in general, of where to start. Operating in a state of change is the new normal for these organizations.

Case in point: the work that I do at Deloitte today looks nothing like the work I delivered ten, or even three years ago, and it will undoubtedly look different in the next 12-24 months. “Tried and true” is no longer a mainstay in this environment as the rate of change in today’s technology landscape requires the supply chain to find new and creative ways to challenge industry orthodoxies and solve the most pressing business challenges. Additionally, customer expectations are rising for both B2C and B2B organizations as the personal and professional aspects of customer’s lives become more intertwined and as technology enables greater customer engagement and value-added services. Everyone wants to be the disruptor and not the disrupted. But many wonder which challenge to tackle first. As you begin your journey, I believe it demands a big shift in the way work gets done, driven by two primary forces: a drastic increase in the amount of data being produced and the subsequent need to automate and augment decision-making.

Wading through the data

Today’s supply chains are seeing a drastic increase in the amount of data being produced through sensors, devices, and systems. Data is aggregating in mass quantities from increasingly sophisticated and affordable sensors appearing everywhere along the supply chain, from mobile devices that live in the field, on the shop floor, and in the hands of customers, and from social media and other third-party sources. Data can be powerful, but companies are struggling with how to turn it into actionable and value-driving insights.

  ​With AI, one could build in the necessary data, constraints, and business rules, then track the choices made in a given set of circumstances over time 

Many supply chain organizations areundertaking a journey from disparate systems and processes that require a lot of offline data collection, analysis and communication, to integrated systems with centralized data models and optimized decision-making and scenario analysis tools, and finally to automated systems that are AI-driven, workflow-enabled and that close the digital-to-physical loop.

Advancing automation

Advanced forms of automation, such as cognitive or artificial intelligence that learn from data to make decisions, advance productivity and help solve business problems.

For example, when a customer places an order for a product that wasn’t planned for, there is a decision to make – whether to break into the production schedule to produce a product to fill that order, which will have knock-on effects to manufacturing costs, other customer orders, inventory levels and more. There are cost and margin implications, contractual implications and strategic considerations to factor in.

Today, that would require several supply planners, product managers, production schedulers, sales representatives and customer service representatives evaluating whether this would make sense, if they even have the data and agility to analyse and respond.

With AI, one could build in the necessary data, constraints, and business rules, then track the choices made in a given set of circumstances over time, so that the tool can evaluate the situation and not only select whether to fulfil that order, but then update the production schedule and send permission-driven auto-notifications to each impacted party as to the change that was made, why and how it may impact them.

Talent in a digital world

As we’re seeing a drastic increase in the amount of data being produced, it also increases the demand for data scientists and people that can make sense of the data to solve business problems.

Today’s supply chain challenges require multiple skills, backgrounds and experiences that blend strategy with functional experience and a wider variety of technical expertise (not just ERP anymore, but SaaS providers, hardware providers, analytics engines, cyber security, etc.). Organizations will need leaders that can stitch these diverse skillsets together to enable their digital organization. In today’s competitive environment, organizations are also evaluating how they can effectively enable job sharing through delivery centers, alliances and other non-traditional methods.

Further, these organizations are seeking to understand how they identify, attract, and retain talent that satisfies that intersection of technology savviness and strategic thinking. Many are challenged to look at new channels and challenge the way they typically hire and embrace new talent models to develop and retain more diversified teams.

Embrace the uncertainty

To stay competitive, supply chain organizations need to keep evolving and innovating and embrace the constant state of change. Just like our client’s customers, our clients’ expectations are rising too; they are becoming more sophisticated and are looking for what’s next.

The pace of change is only getting faster and if you’re not staying ahead, you are behind. All of this is to say: be curious - increase your tech fluency, explore emerging technologies and solution providers, and connect with other professionals, who are almost always willing to share.

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