Over the last ten years I have been fortunate enough to have a ring-side seat to the changes in Supply Chain brought about by technology that is finally maturing from tentative use cases to first useful products and on into mainstream. Likewise, I have been a witness to how companies are struggling with the changed reality.
It is no secret that for many manufacturing companies, for a long time investing in supply chain was not seen as a priority. Focus was given to customer front-end stuff at the cost of the operational, behind-scenes nuts and bolts of a company. The truth these companies started recognising is that systems and data management is the life-blood that enables a company to grow, and these cannot be implemented or changed overnight. Likewise, skilled staff is an issue in a discipline that suffers from “Image Problems” and a history of lack of recognition.
So, what are the main areas that need addressing?
1) Demand Side – Cycles are becoming shorter and customer expectations regarding reaction times is shortening significantly. Products and parts that used to take 3 years from inception to series production are now expected to turn around in 18 months. This speeding up requires Supply Chain responsiveness behind it, and this can only happen when there is shared data, visibility and agility.
2) Planning & Data – If a company is not already looking into IoT sensors, Predictive Analytics, Machine Learning, and Supply Chain Visibility tools, then it is already significantly behind the curve. Data is King, the situation at Tesla has shown everyone in the automotive business this. Planning is currently still an area for horse-trading rather than making decisions supported by sound analysis and data. The role of Materials Planner is set to change from reactive to proactive, from manager and fire-fighter to optimiser and decision-maker
3) Aligned systems from customer through to sourcing - Too many organisations have a patchwork of MRP/ERP systems that “talk” to each other through multiple bespoke portals or links, frequently as a result of M&A activity. Where this happens, data is held in silos and not easily accessible or usable by different elements in the supply chain. One would question whether the classic ERP has had its day, and in its space a web of cloud-based specialist tools with data kept in a common “data lake” is the way to go.
4) Standardised Master Data - A classic example is the differing nomenclature for part numbers and master data – in some companies each site can have a different nomenclature leading to serious issues when it comes to regional planning, or supplier loading calculations. Aside from this, it will prove to be a challenge if DLT (Distributed Ledge Technology) becomes a significant way of conducting business, where zero-trust contracts require a common terminology to work (See Lora Cecere’s and her Network of Network’s work on the subject)
5) Training – Supply chain is a complex discipline and getting more so with each passing year. It is not a place to put people who don’t fit anywhere else in the organisation. Correspondingly, staff should be trained and developed to become owners of their part of the supply chain – treated as adults, not bossed around like children. I have seen factories transform and do amazing things once their Supply Chain Departments we trained and empowered – stunning realignments around data-driven material flow. But it does start with the people knowing what they are doing and their part in and responsibility to the whole.
This is by no means a complete list but does show the key areas that need addressing. The question is how?
1) Digitization vs. digitalisation vs. digital transformation? The first will just make bad processes in the company digital. The second, uses digital technologies to change the business model to gain new value and revenue gaining opportunities. The third, is a fundamental holistic change in order to serve the customer – it’s the most painful, but it is also the one that sets the company up for long-term success, if done well. Digital transformation aligns systems to serve customer demand and ease the flow of data through the organisation.
2) Address the Demand Uncertainty Information Gap. This means the ability to make sense of data, lots of it. At present companies have formatted data, but frequently it is unformatted data that can add uncertainty Supply Chain activities – social media feeds, a change in weather, a competitor’s special promotion, Brexit news etc. Tools are becoming available to evaluate unformatted data and the effect that it can have. Scenario modelling capabilities are improving, leading to a better understanding and decision-making process, but it is far from easy.
3) Address Production Uncertainty Information Gap. Capacities and production/material availability is the internal Achilles Heel of the supply chain. IoT sensors combined with Predictive Analytics and Machine Learning (ML) are a powerful combination in bridging the gap to make machine availability and output visible in real time. This is progressing apace, even down to the first few examples including DLT-supported replenishment processes (see Azhos as an example)
4) Synchronise the information flow to remove uncertainty – This is at the core of supply chain. If the information does not flow, is subject to interpretation and is not visible to all relevant parties in the chain, planners will “assume” in order to bridge the gap. A game of “Chinese Whispers” ensues. Zero-trust technologies, such as DLT have significant potential in ensuring that there is a single version of truth between all parties. However, the big caveat is that true multi-party blockchains are still a way off, whatever the media hype might say.
5) Address the Education Gap – the speed at which Supply Chain is changing is fierce, and the skills that are currently being used will be obsolete with the advance of Machine Learning. This means that staff will need different skills more aligned with interpreting scenarios, understanding systems, dealing with outlier situations and so on. This needs training to be consistent and part of the value proposition that the company offers each employee.
So, if you want to “get there” from here: love your data, people and systems
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