It has been advocated that ‘supply chains compete, not individual firms’ for over 30 years, but this often fails to be the case in practice. Jan Godsell, Professor at the University of Warwick, asks why this is so difficult to achieve, and why advances are on the horizon
Supply chain productivity is important because it is one of the keys to unlocking the ‘productivity puzzle’ that has faceda number of developed economies over the past decade.Developed economies (such as the UK) have recovered post global economic crisis, but productivity has flatlined. This is significant, as productivity (measured as the amount of work produced per working hour) is the main driver of long-term economic growth and higher living standards.
Productivity is typically measured at a company level, and is more commonly known as efficiency. Within a firm this is usually monitored at the level of functional efficiency, supported by a range of functional targets and metrics. Perceived good management practice suggests that these metrics should be SMART (specific, measurable, achievable, realistic and timely), which limits their scope to within a function, driving silo-ed thinking. The end result (at best) is likely to be of efficient functions, but within an inefficient organisation overall.
This inefficiency is amplified as the supply chain reaches out to connect with its customers, suppliers and beyond. With poor visibility of data across the end-to-end supply chain and a historic paucity of analytics and decision support tools, it has been difficult to move beyond this functional silo-ed view.
However, over the past five years the situation has changed. Digital technological solutions have emerged that have the potential to address both these challenges. We are on the cusp of the next stage in our industrial evolution, one where a step change in productivity will be realised, as supply chains truly compete and not individual firms (Martin Christopher in Logistics and Supply Chain Management).
But how ready is industry for this change?
Supply chain digital readiness in Europe
In 2018, the Warwick Manufacturing Group (WMG), the University of Warwick, in conjunction with JDA (a software company), conducted a study to understand the supply digital readiness of 179 major manufacturing companies in Europe. Digital readiness was defined across four levels.
The study found that only 13% of companies were at level three readiness, in which dynamic end-to-end supply chain optimisation supported by an advanced analytics capability is starting to leverage machine learning (ML) and artificial intelligence (AI). Fifty two percent were at level two readiness – leveraging some specialist analytics tools to support functional optimisation. Thirty five percent were still trying to get visibility of data, and were using simple analytics tools (e.g. spreadsheets) predominantly for reporting.
By 2023, level three readiness is predicted to more than double, to 31%. However, the average level of readiness is only predicted to increase by half a level from 2.3 to 2.8. On the surface this represents a relatively modest improvement. In reality it reflects the difficulty companies face in overcoming entrenched ways of working and legacy systems. It reflects the change from a functionally silo-ed organisation to one with an end-to-end supply chain perspective.
Four strategies to improve supply chain digital readiness
There is no single bullet to improve supply chain digital readiness. A multi-stranded approach is required, which considers the level of technological innovation and size of impact, and is designed to manage risk
Source: Godsell (2018)
1. Optimise core supply chain processes
Supply chains consist of five core processes: planning, procurement, manufacturing, logistics and return (according to the industry standard: Supply Chain Operations Reference model). In reality, many organisations have failed to use the data they currently have to optimise these core processes.
This begins with building the data infrastructure, which usually exists in the form of an Enterprise Resource Planning (ERP) system. The critical step is to recognise the importance of this data and develop governance processes to maintain its integrity. The next step is then to improve data capture, in those areas where having that data could make a difference. Advanced analytics and decision support systems can then be utilised to improve efficiency. This enables organisations to make the most of what they currently have to sustain their legacy business. It builds a bedrock of operational excellence, freeing up cash to enable the business to invest in new ways to compete.
2. Adopt a supply chain business process orientation
The second stage is arguably the most difficult, but is the most crucial for organisations to move beyond functional optimisation. It requires organisations to give equal importance to managing the supply chain, as an end-to-end business process as they do to new product development (NPD) and customer relationship management (CRM). This requires a change in organisational structure, to overlay a business process perspective over the classic functional or matric structure.
A study in 2016, Supply Chain Segmentation: A Window of Opportunity for European Manufacturing, by the WMG, University of Warwick and JDA, found that only 17% of organisations in Europe had a business process orientation reflected in their organisational structure. This is critical as, whilst they draw on functional resources, they break down organisational boundaries, as they seek to optimise the business around strategic, rather than functional, goals.
3. De-risk supply chain digital technology pilots
There are numerous technologies that companies can use to improve individual aspects of their supply chain. It is important to create safe spaces in which these technologies can be trialled. Good research can limit failure, but organisations should not be afraid to ‘fail fast,’ as long as they have good processes in place to capture the learning. One way to de-risk the digital technology pilot is to be clear on what is being piloted.
To minimise risk and maximise learning, current capabilities should be developed in a step-by-step way. Apply new technology to an existing process or a new way of working with existing technology, but not both simultaneously. In this way if the pilot succeeds or fails, the reason is clear. It also provides a pathway for moving up the learning curve for new technologies (eg, blockchain or distributed ledger technology) where applications that provide benefit over current technologies are currently limited. It will help create first-mover advantage when beneficial applications for the technology become evident.
Source: Godsell (2018) after Ansoff (1957)
4. Explore new business models
We are in a transition point between two stages of industrial evolution. At times of transition there are significant opportunities to redefine the way in which value is created and delivered. The economic benefits of consumption-driven growth are beginning to be outweighed by the environmental and social costs. Responsible consumerism, urges us to buy less, buy green and buy fair. This is redefining business models, to encourage greater sharing and consideration of how ‘stuff’ can be retained in its highest possible value state for as long as possible. It is seeing a shift from the provision of products to services, and is supported by a shift in the design of supply chains.
Digital technologies are a key enabler to these new business models. Business models that are disruptive and often in direct conflict with the legacy business model upon which the short-term success of their organisation depends. This is a great time to be a small organisation, that can leverage the benefits of a more agile organisation structure. For large legacy businesses, consider setting up a separate organisational entity that has the freedom to explore the art of the possible, and build the business model of tomorrow.
We are on the cusp of a change – and one that is hopefully one for the better. This will see the intelligent use of digital technologies enabling supply chains to compete to support new models of economic growth and productivity.
Attribute to original publisher/ publishing organization: Jan Godsell is Professor of Operations and Supply Chain Strategy at the Warwick Manufacturing Group, University of Warwick, https://www.quality.org/knowledge/thriving-digital-age-four-strategies-enable-supply-chain-productivity