Supply Chain Technologies and Digital Transformation

Eighty-two percent of CEOs in supply-chain-intensive industries plan to increase investments in digital capabilities across their enterprise. Why? To support new business, improve supply chain process efficiency and productivity, enhance decision making and improve resiliency/agility amid ongoing supply chain disruption. This puts chief supply chain officers (CSCOs) under tremendous pressure to digitalize the supply chain.

Unfortunately, CSCOs often struggle to translate their digital supply chain vision, ambitions and business objectives into an understandable, easily communicated and business-aligned digital transformation roadmap. In fact, less than half of CSCOs have defined or plan to implement a supply chain digital transformation roadmap. Of the digital supply chain roadmaps that do exist, only 32% are aligned under a single governance process and to common business goals.

Many supply chains have been too slow to react and are still developing the foundational physical capabilities required to compete today, let alone develop, test, deploy and scale digital innovation effectively.

Supply chain digital transformation is proven to mitigate supply chain risk and optimize supply chain cost, but it requires strong alignment between business and supply chain strategy to succeed. It also requires technical skills like supply chain analytics, business skills like cross-functional collaboration and data-driven decision making, and behaviors/traits like adaptability and risk taking.

Start leveraging supply chain digital technologies to increase business performance by first building a multiyear, integrated digital transformation roadmap that addresses both short-term improvements and a strategic long-term vision. Effective roadmaps for supply chain digital transformation consider redesigning the supply chain planning organization, centralizing the supply chain analytics team and building supply chain talent for the future. Then establish oversight of the roadmap to maximize returns on your digital investments. Review vendors, consolidate decision-making models and inventory the processes that can be automated or augmented.

The global chief supply chain officer (GCSCO) community wrestles with evaluating, selecting and implementing end-to-end supply chain technologies that foster competitive advantage. What supply chain technologies are most important to the success of supply chain transformation?

A recent Gartner survey about supply chain transformation drivers and best practices revealed that supply chain leaders need to prioritize investments in technologies that can enable supply chain strategy.

The survey found that established applications like enterprise resource planning (ERP), supply chain planning (SCP), procurement, omnichannel and logistics have played a significant role in driving supply chain transformations over the past three years.

ERP, in particular, is a critical foundational enabler for an integrated supply chain. Seventeen percent of supply chain professionals in non-C-suite roles ranked ERP the No. 1 most essential technology to supply chain transformations, and those from organizations at a Level 3 supply chain maturity ranked it No. 4.

New digital technologies, on the other hand, were deemed less important to the success of supply chain transformation by supply chain leaders responding to the survey. To be clear, supply chain digital twin, augmented reality and control towers have delivered significant benefits for some, and advanced supply chain analytics (as well as artificial intelligence [AI], machine learning [ML] and other related technologies that help organizations make better decisions) ranked the No. 2 most important technology. But most say they have yet to derive the value anticipated from their digital investments.

To succeed in the future supply chain, Gartner recommends that GCSCOs include enterprise applications in their digital supply chain roadmaps and explain to stakeholders — especially senior executives — the critical role more traditional technologies play in supply chain transformations.

Over the next 10 years, demand from machine customers will become increasingly relevant, generating more than 20% of revenue. According to Gartner research, only 15% of supply chains are ready today to respond to that demand. 

To handle automated buyers, the supply chain operating model must evolve. Supply chain leaders must prioritize digitally integrating the ecosystem, using secure and unbiased data, and automating.

Technologies like artificial intelligence (AI), machine learning (ML) and blockchain support the evolution toward a more holistic, integrated, sustainable and autonomous supply chain.

• AI in supply chain leverages computers and machines to mimic the problem-solving and decision-making capabilities of supply chain employees, and to adapt more quickly to the dynamic environment in which businesses operate. This adaptability is supported by supply chain planning to supply chain execution.

• ML is an advanced analysis and logic-based technique for interpreting events, supporting and automating decisions, delivering experiences and taking actions. Supply chain ML technology can create additional agility and resilience through data diagnostics, demand forecasting, demand sensing and inventory optimization. 

• Blockchain in supply chain impacts ecosystem management because it offers the ability for broad collaboration but allows control through data access rights.

Additionally, supply chain digital twin has the potential to transform the supply chain’s ability to mitigate risk, manage supply and demand, and enhance customer experience. Gartner recommends that supply chain leaders accelerate investment in supply chain digital twin and engage in its development.

Supply chain organizations must leverage the opportunities that strategic and emerging technologies offer and manage the impacts of these decisions on the business. Start with a no-risk data-driven use case before extending the program to one of the most common supply chain planning use cases. Further expand on use cases as data becomes available and the operating model matures.

Supply chain cybersecurity today involves diagnosing a vendor’s cyber posture against specific cybersecurity controls. But these audits are difficult to scale, and breaches may occur anyway.

Going forward, tools for automation and scale, talent programs, and education and evangelism will be used in conjunction to provide a holistic, effective defense. 

Expanding the use of automation and tools: Because it’s difficult to scale audits, companies are investing in process automation. Solution providers now offer governance, risk and compliance (GRC) tools that verify threats and create alerts. But companies are still looking for technologies to help with continuous and predictive threat monitoring, as well as tools that take cyber-risk mitigation deeper into supply chain operations.

Cybersecurity talent: Competition for talent in cybersecurity is fierce and made worse when looking at the intersection with supply chain expertise. As such, supply chain organizations use a range of strategies for staffing supply-chain-related cybersecurity roles, starting with external consultants and transitioning to an in-house team. Cybersecurity talent often comes from outside the business (e.g., former government/military or security specialists). Like other highly technical roles (e.g., data scientists), these employees need grounding in the business and in supply chain contexts to build proper defenses.

Embracing, evangelizing and educating about cybersecurity: It is critical to provide education about cyberthreats and mitigation approaches, and work to put protection in place inside and outside your supply chain organization. It should not fall to a supply chain function or business unit leader to work with smaller and less established partners that do not have the time, resources or skill sets for proper cyber hygiene.