PC-OCT22-PG50.1_Layout 1 05/10/2022 16:04 Page 50
SUPPLY CHAINS
THE ROLE OF DATA IN SUPPLY CHAIN PLANNING Jim Bralsford, Industry & Solutions Marketing at Kinaxis, says data is playing an increasingly important role in supply chain scenario planning
give businesses the best chance of finding a solution that works.
This is why speed is of the essence when it comes to global supply chain disruptions. The longer a disruption is allowed to run across a chemical supply chain, the more detrimental its impact on customer satisfaction, delivery speeds, and – ultimately – a business’s overall revenues. For supply chain planners, the pressure is on to quickly get ahead of problems.
Nobody knows for sure what the next big global supply chain disruption will be, nor when it will happen. But what is beyond doubt is the key role that data-driven, technology-enabled scenario planning will play in helping to build agility and resilience. Image source: Pixabay
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upply chain scenario-planning has rocketed in almost all industries since the Covid-19 pandemic, continuing a trend that started before the viral outbreak. With China, the workshop of the world, adopting a zero-Covid policy, the ability to plan for a range of scenarios remains an important capability, further emphasised by the Suez Canal blockage. Recently, the Russian invasion of Ukraine has added another far-reaching set of disruptions, including the imposition of stringent sanctions by the EU and US. Energy price volatility and shortages of commodities and skilled labour add to the complications of running a future-proof supply chain. So, where does this leave the chemical industry? The Chemical Business Association’s most recent Supply Chain Trends Survey revealed that the UK chemical supply chain is continuing to encounter serious issues, jeopardising future sales and margins. While there is no magic bullet to fix the challenges, planners can benefit from building more meaningful scenarios for the short, medium and long-term, based on a robust, real-time view of data.
While Covid did have a major impact on economies worldwide, the rate of disruption across supply chains has been growing exponentially for decades. As businesses become much more reliant on a greater scope of global suppliers and manufacturers, scenario-focused supply chain planning has come to the fore as the best (or only) means of having full transparency over what is happening outside of an organisation. The pandemic only catalysed this trend away from silos and towards the need to leverage concurrent scenario planning across the
50 OCTOBER 2022 | PROCESS & CONTROL supply chain.
In the face of persistently volatile market conditions, current labour shortages represent yet another complicating factor. Figures from the national Labour Force Survey show that nearly all companies across the industrial sciences sector currently have vacancies that are difficult to fill due to skills shortages. The need for more advanced scenario planning solutions to provide a single source of truth for more accurate evaluations across the supply chain is more pressing than ever.
To balance the need to optimise costs in the short term with the need to create more resilient and agile supply chains to respond to future uncertainties, many businesses are turning to scenario planning to exercise more control over their destinies. And there are two approaches when it comes to scenario planning: known and expected challenges and completely unknown disruptions. For the known and expected challenges, effective scenarios are created with multiple potential options and well-defined KPIs to ensure that the chosen solution still meets the minimum requirements. Combining these options with dashboards and scorecards that clearly articulate the expected outcomes of each choice can enhance decision-making, giving businesses a clear understanding of the impact of successive changes. But in the case of completely unknown disruptions, easily identifiable options do not exist. With so many tweaks and variables needing to be considered, supply chain planners need the ability to quickly eliminate those choices that are not going to meet the KPIs. The faster scenarios can be run, the more options can be attempted, piece-by-piece, to
In the past, supply chain design was excessively focused on optimisation – both in terms of costs and efficiency. The race to chase down the perfect plan, or flawless 100% forecast accuracy, meant many practitioners failed to build enough agility and resilience into their supply chain. It would take hours or even days to calculate a plan, causing them to completely miss the boat when fast- moving disruptions such as Covid occurred. Fortunately, this is changing, as the chemical industry realises the need to achieve deep visibility to improve speed, agility, and efficiency in complex global supply chains. The sector is now turning to technology to ensure the right balance is struck between agility and optimisation – and advanced analytic techniques are offering a way forward.
Data plays an increasingly pivotal role in effective supply chain scenario planning. It provides businesses with an end-to-end picture of their supply chain – not just within their own four walls but across any partners, third-party suppliers, and even the changing needs and orders of customers. Data insights are crucial in giving planners the visibility and transparency needed to run effective scenarios.
But it is not enough to just collect data and have “visibility”. The data needs to be of a high enough quality to help, rather than hinder, decision-making across the supply chain. Without consistent, correct, and up-to-date data, the outcome of a scenario will be fundamentally wrong. Therefore, an effective scenario must be founded on a solid understanding of exposure, inventory, and the true nature of demand – whether it is driven by panic or longer-term trends, for example. Recent advances in artificial intelligence (AI) and machine learning (ML) are helping to drive the trend towards more data-driven scenario planning. These technologies augment the work of humans by offering up insights that they perhaps would not have found on their own. AI, in particular, can efficiently process data and pass on key insights to human supply chain planners, allowing them to review the insights and formulate the strongest possible “what-if” scenarios.
Kinaxis
www.kinaxis.com
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