Minimising supply chain disruptions using data analytics

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Published on: 17 November 2022
Written by: Tridant

Disruptions are no stranger to the supply chain. Minor disturbances such as late supply delivery, shutdown of a production line, shortage in transportation capacity and limited supply stock levels are quite common while major disruptions such as natural disasters and COVID-19 have had catastrophic impacts on supply chains in recent years.

Survey results indicate that supply chains are facing increased disruptions over the past three years than they did previously, and the average impact of these disruptive events has also increased.

With increased access to more readily available and reliable data, organisations are looking to take advantage of analytics to sense disruption ahead of time, comprehend its impact on the supply chain, and formulate a response. To successfully minimise the impacts of a supply chain disruption, organisations must rely on strong analytics competency that combines a broad range of strategies and approaches.

The six uses of analytics in supply chain disruption mitigation include:

1. Sense

Be aware of the unfolding disruptive event

Organisations can take advantage of publicly available data to understand how disruptive events take place, as well as identify any potential for future disruptions. The earlier a disruption is identified, the easier the problem is to solve and the smaller the impact will be. Data can be provided by governmental bodies and academic institutions for free, or it can be offered for a fee by service providers.

Similarly, supply chain organisations can leverage real-time analytics using mobility and location-specific data collected by satellites and distributed sensors to identify a potential disruptive event.

2. Visualise

Envision the impact of disruption

Visualisation analytics can provide organisations with the ability to measure the impact of a disruption on the supply chain. This is critical for companies with global, complex supply chains with many suppliers for a range of parts and materials.

Foreseeing the impact of a disruption before it occurs will allow an organisation to plan in advance and make decisions to minimise the impact on the supply chain. Identifying the span of the disruptive event onto specific components of a supply chain (e.g location, specific suppliers etc.) can help identify supply chain vulnerabilities and critical risk exposure.

3. Respond

React to the disruption to minimise its impact

Organisations often use machine learning and artificial intelligence (AI) to assess their supply chain and determine the need for any immediate action. Combining machine learning and AI allows unfolding events to be identified early and a quick response to be made, therefore minimising the impact of the event.

Unlike traditional statistical modelling that relies on past data, machine learning algorithms provide forecasting and leverage near-real-time data that reflects the dynamic of an unfolding event.

4. Predict

Consider future demand and supply scenarios

Once action has been taken to minimise the short-term impact of the disruption, organisations should then turn their attention to understanding all short, mid and long-term scenarios to accurately predict the effect of the disruption on their entire company.

Predictive analytics and simulations provide supply chain leaders with expected future data and outcomes, therefore enabling organisations to be better prepared for any future needs to help mitigate disruptions.

5. Model

Evaluate alternative supply chain policies

Organisations often rely on approaches such as optimisation and scenario modelling to predict changing business needs resulting from a disruptive event, allowing for changes to be made to policies and procedures to be better prepared for any future disruptions.

By using optimisation, companies can evaluate different supply chain policies, balancing the trade-offs of managing a lean supply chain whilst building a level of resilience that allows for a quick recovery from a disruption, or even a complete avoidance of it.

6. Design

Configure supply chain resiliency and agility

Using long-range forecasting, simulations and other advanced analytics techniques allows organisations to predict the long-term impact of disruptions under a range of scenario conditions. This helps determine the required action to position the supply chain to take advantage of new opportunities, as well as leverage long-range forecasting and optimisation to increase supply chain resiliency.

Although supply chain disruptions are essentially unavoidable, organisations can use data and analytics to identify the disruption ahead of time, determine the impact of the disruption on the supply chain, and entire organisation, and respond to the disruption. These insights are crucial to helping build a resilient supply chain that can continue to operate at a high capacity in the event of a supply chain disruption.

Tridant's Sales & Operation Planning (S&OP) Application uses data and analytics to enable a connected supply chain with fast, accurate data analysis across your whole business. The solution assists businesses in achieving balance between fluctuating demand and supply as a result of supply chain disruptions though intelligent sales forecasts, ensuring efficient connection between all links within the supply chain. Find about more about the S&OP app here.

Please contact us if you would like to discuss how you can use analytics in your organisation to minimise disruptions to your supply chain. To learn how Tridant can optimise your supply chain, visit our website.

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