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10 Ways Machine Learning Is Revolutionizing Supply Chain Management

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Machine learning makes it possible to discover patterns in supply chain data by relying on algorithms that quickly pinpoint the most influential factors to a supply networks’ success, while constantly learning in the process.

Discovering new patterns in supply chain data has the potential to revolutionize any business. Machine learning algorithms are finding these new patterns in supply chain data daily, without needing manual intervention or the definition of taxonomy to guide the analysis. The algorithms iteratively query data with many using constraint-based modeling to find the core set of factors with the greatest predictive accuracy. Key factors influencing inventory levels, supplier quality, demand forecasting, procure-to-pay, order-to-cash, production planning, transportation management and more are becoming known for the first time. New knowledge and insights from machine learning are revolutionizing supply chain management as a result.

The ten ways machine learning is revolutionizing supply chain management include:

  1. Machine learning algorithms and the apps running them are capable of analyzing large, diverse data sets fast, improving demand forecasting accuracy.
  2. Reducing freight costs, improving supplier delivery performance, and minimizing supplier risk are three of the many benefits machine learning is providing in collaborative supply chain networks.
  3. Machine Learning and its core constructs are ideally suited for providing insights into improving supply chain management performance not available from previous technologies.
  4. Machine learning excels at visual pattern recognition, opening up many potential applications in physical inspection and maintenance of physical assets across an entire supply chain network.
  5. Gaining greater contextual intelligence using machine learning combined with related technologies across supply chain operations translates into lower inventory and operations costs and quicker response times to customers.
  6. Forecasting demand for new products including the causal factors that most drive new sales is an area machine learning is being applied to today with strong results.
  7. Companies are extending the life of key supply chain assets including machinery, engines, transportation and warehouse equipment by finding new patterns in usage data collected via IoT sensors.
  8. Improving supplier quality management and compliance by finding patterns in suppliers’ quality levels and creating track-and-trace data hierarchies for each supplier, unassisted.
  9. Machine learning is improving production planning and factory scheduling accuracy by taking into account multiple constraints and optimizing for each.
  10. Combining machine learning with advanced analytics, IoT sensors, and real-time monitoring is providing end-to-end visibility across many supply chains for the first time.

Read more at 10 Ways Machine Learning Is Revolutionizing Supply Chain Management

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Data Lake vs Data Warehouse: Key Differences

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Some of us have been hearing more about the data lake, especially during the last six months. There are those that tell us the data lake is just a reincarnation of the data warehouse—in the spirit of “been there, done that.” Others have focused on how much better this “shiny, new” data lake is, while others are standing on the shoreline screaming, “Don’t go in! It’s not a lake—it’s a swamp!”

All kidding aside, the commonality I see between the two is that they are both data storage repositories. That’s it. But I’m getting ahead of myself. Let’s first define data lake to make sure we’re all on the same page. James Dixon, the founder and CTO of Pentaho, has been credited with coming up with the term. This is how he describes a data lake:

“If you think of a datamart as a store of bottled water – cleansed and packaged and structured for easy consumption – the data lake is a large body of water in a more natural state. The contents of the data lake stream in from a source to fill the lake, and various users of the lake can come to examine, dive in, or take samples.”

And earlier this year, my colleague, Anne Buff, and I participated in an online debate about the data lake. My rally cry was #GOdatalakeGO, while Anne insisted on #NOdatalakeNO. Here’s the definition we used during our debate:

“A data lake is a storage repository that holds a vast amount of raw data in its native format, including structured, semi-structured, and unstructured data. The data structure and requirements are not defined until the data is needed.”

Read more Data Lake vs Data Warehouse: Key Differences

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Why Supply Chain Risk Management is Key to Supplier Management

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While brand damage can be quite costly to the businesses whose sales rely strongly on the customer loyalty they generate from their brand strength, cost volatility and supply disruption is very costly to all manufacturers. In fact, in the latest 2015 study by the Business Continuity Institute, supply chain disruption is double in priority relative to other enterprise disruptions and over three-fourths of respondents cited that they had at least one recent (significant) disruption. The same percentage didn’t have full visibility of their supply chains.

While category management can address and even reduce supply chain risk by ensuring a chosen strategy has the right level of resiliency, prevention and agility, it cannot prevent risk or do much to eliminate the source of risk once something has happened. That can only be done by each party in the supply chain doing everything they can to eliminate the risk. In particular, a supplier needs to do all they can to minimize the risk on their end.

However, not all suppliers are as advanced in supply chain management, and in particular, risk management as the buying organization. That’s why good supplier management combined with SCRM is key. Good risk management is a combination of risk prevention and risk mitigation when a risk is detected. Risk prevention involves selecting suppliers, products and services that are low risk and risk mitigation involves taking action as soon as an indicator is detected.

A supplier is not always good at mitigating or even detecting risk in its supply chain, or may overlook an obvious sign that an observant buyer would not, which is why proper supplier management is key. This begins even when qualifying suppliers. Including risk criteria related to the supplier and supplier location gives a good indication of a supplier’s the risk level. Besides the supplier qualification criteria, supply location-related risks provide an overview on potential threats like natural disasters, political situation, sanctions or economic risk. This gives buyers the chance to take preventive actions.

Read more at Why Supply Chain Risk Management is Key to Supplier Management

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Visibility Is Key when Driving Supply Chain Performance

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At its heart, supply chain management requires a balancing of operational efficiency, customer satisfaction and quality. Managing the true cost to serve for each and every order is the aspiration to allow better negotiation and value creation across the supply chain. Customer- and consumer-centricity helps anticipate product and service requirements. Supply chains are becoming more extended and complex with a consequent increase in risk and the need for resilience. There are multiple data sources making it difficult to manage and measure end-to-end processes and metrics. Aligning priorities through integrated planning remains pivotal, but there is an explosion of data available that needs to be incorporated and the value extracted to understand how supply and demand issues impact profit and revenue targets.

New technology provides greater supply chain transparency. Strategic supplier engagement continues to be important as a way of reducing costs and mitigating risk. Effective supply chain management can be either a compelling competitive differentiator or, conversely, a source of risk, cost and poor customer service.

Organizations are looking to enable better and more consistent decision-making across complex processes with diverse systems and data. Many are leveraging business intelligence (BI) platforms to give them the capability to make decisions across the organization, including environments in which mobility and access to decision-critical information on the go is crucial. Putting the information in the hands of the people on the front line—those managing supply chain processes—is key to enabling decision-making at the point of decision. But this requires synchronizing an enormous amount of data that comes from many systems and sources in a way that it can be easily consumed by people who need to act on the insights.

Read more at Visibility Is Key when Driving Supply Chain Performance

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6 Steps To Supply Chain Risk Management Success

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6 Steps To Supply Chain Risk Management Success

Lean production may traditionally be considered the linchpin that holds successful supply chain management together, but reducing your exposure to risks is becoming a key priority for maritime companies.

Our dependence on, and partnerships with suppliers, whether it be via outsourcing or mitigating stock opens up a whole world of exposure for marine businesses and their procurement teams. That’s why risk management is so crucial to the supply chain.

Navigating risks really is the key to management success. With the global expansion of supply chains comes ever more complicated business structures and so countless issues can arise causing disruption, delays and ultimately money going down the drain.

Both buyers and suppliers can be hit by a number of unavoidable problems. From natural disasters to terrorism or cyber attacks. Each problem can have big effects on both upstream and downstream partners.

So what can you do to mitigate risk?

The best way to reduce exposure is to make sure you and your company keep up to date with developments in the maritime sector. And to follow a few key steps…

1. Choose your suppliers carefully

Conduct audits of your suppliers on a regular basis and if necessary, inspections to make sure they are committed to risk management like you are.

2. Authenticate suppliers’ insurance cover

It’s worth remembering that a certificate of insurance is only evidence of the insurance cover as it was when it was written.

3. Clearly define contract scopes and draft contracts

Be careful when defining contract scopes and draft contracts.

4. Understand the extent of your exposure

How much risk are you and your business exposed to?

5. Put a plan in place

Identifying risks is the easy part, now you have to get an action plan in place.

6. Lower the threat of risk by purchasing the right cover

Making sure your policy covers your company’s specific exposure mix and risk tolerance is important.

Do you have any ideas to add regarding risk management in supply chain? Share your opinions in the comment box or send us a message for discussion.

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