The Digital Thread: Unlocking Supply Chain Insights

Data has become one of the most valuable commodities for today’s businesses. In their modern-day drive to digitalisation, exponential amounts of data are now being produced within their supply chains. Yet despite this, why do so many opportunities to release or create value remain untapped? And why are many manufacturers letting their greatest resource gather digital dust?

Because data is a commodity which is not necessarily valuable in and of itself, the key to unlocking supply chain insights is to connect the product and contextual data running through the value stream.

Following this ‘digital thread’ allows businesses to integrate and transform disparate data into actionable information, refining efficiencies and reducing costs.

Within this context, it’s vital that information is actively managed across the thread in order to prevent leakages, where potentially valuable stakeholder information gets lost somewhere in the value chain.

So, just how can manufacturers manage the digital thread to avoid inefficiencies and excavate actionable insights?

 

Securing Sales & Operational Planning

Tightening the digital thread doesn’t always start with improving the external supply chain. In fact, the functional barriers within an organisation are as much a factor in market competitiveness as those barriers between organisations in the external supply chain.

There is a naivety around the impact that siloed sales and manufacturing functions can have, with many sales professionals believing ‘if I sell it, you should be able to make it!’. In reality, many companies find it impossible to forecast accurately due to inaccurate data flowing into the business through the sales channel. Combine this with weak supply data coming via procurement/supply chain and the result is easy to predict – poor performance towards the customer and over/under stocking which affects working capital, cashflow and profitability.

Companies should look to connect their functions and improve data sharing, ultimately recognising the view that wider company goals take priority over divisional or departmental aims. Sales & Operational Planning (S&OP) isn’t necessarily a hugely expensive technology driven process. It’s often about the heads of sales, production, procurement and supply chain sitting down together and sharing a common dataset.

The real barriers to this efficient data sharing include poorly integrated systems where data is not shared effectively, as well as misaligned KPIs for those roles that play a key part in effective S&OP. A classic example is where procurement managers/buyers are incentivised on achieving the lowest unit price and therefore buy in large volumes; whereas manufacturing can only consume products at a rate which leaves stock on the shelf, which results in misused working capital and lower profits.

 

Easing the flow of data

When it comes to the external supply chain, the timely sharing of demand data is critical to success. Yet for many businesses, an array of disconnected systems operating in silos, with multiple data replications across the enterprise are acting as a major roadblock. And this lack of agility to adapt to the connected world is ultimately slowing down time to market and organisational efficiency.

These challenges can be addressed by a digital thread, and a connected enterprise must be geared toward tapping this continuous stream of data throughout the value chain to glean actionable, real-time insight. This has been facilitated by the advent of digital platforms which allow the use of open architecture and API connections between ERP/CRM/PLM systems across different organisations. Creating an integrated model-based enterprise platform allows data relating to everything from modelling and inventory to traceability and deviation handling to flow seamlessly across the chain.

 

Adopting Artificial Intelligence

Despite these technologies, it’s where data meets people that true friction occurs. Human responses can reduce speed when reacting to demand signals, which translates into lost sales and extra costs to ‘catch up’ to stay competitive. But rather than supplement workers with technology, businesses must evaluate where human beings best fit in to complex supply chains undergoing digital transformation.

Whether we’re talking about Robotic Process Automation (RPA), drone deliveries, robots/cobots or chatbots there are two competing fears. Either robots will take over and remove the need for human beings altogether, or AI technologies are so far-fetched that they will never deliver the value envisaged by ardent technologists.

The truth, of course, lies somewhere in between. Whilst AI is not a universal silver bullet, it can perform highly repetitive tasks with unerring accuracy at a speed at which humans can only be amazed. Deploying AI to react and respond to insights from the digital thread can facilitate a plethora of efficiency-enhancing solutions, from automated inventory management to deterring security intrusions and anticipating consumer purchases.

Importantly, however, humans still have a clear role to play. Adopting AI should mean that humans are no longer needed to do boring, repetitive work, but rather to add value and make decisions where technology cannot. This may be about understanding the subtleties of conflicting priorities and negotiating the ‘best’ outcome in a complex, nuanced situation. In this context, the digital thread fosters not only AI analytics, but adds human value.

 

Conclusion

Leveraging and sharing information across a digital thread allows for closer cohesion across the complete product lifecycle and throughout the supply chain. Internally, a single point of digital reference allows businesses to break down organisational siloes, greatly increasingly a company’s aptitude in the full spectrum of goals and objectives.

Externally, an end-to-end integrated view of an asset’s data through various isolated functions facilitates collaboration and excavates actionable insights. This real-time data view fosters AI analysis, adds value to human input and ultimately enhances operational efficiency.

 

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