I interviewed Lalit Panda who discussed Big Data and the Supply Chain.

 

 

 

 

 

 

Before we start, can you provide a brief background of yourself?

 

Sure. Great to talk to you, Dustin, again. After two decades of supply chain, my last three assignments have been in the C-suite, heading the IT function in global multinational companies. These are multibillion-dollar companies in various industries, ranging from consumer electronics to agrochemicals, to mining. It’s been an interesting journey, and it’s nice to share some of the perspectives I have gained through this multi-industry experience. The topics that we’re going to talk about, I think we’ve had some opportunity to think through some of the issues in these various industries, so I’m happy to share the learnings with you and your audience.

 

What are the data points with big data analytics that are used for coming up with useful conclusions in supply chains?

 

Yes. Big data is the topic of the day, as you know. There’s a lot of discussion going on because the whole concept of data analysis has gone from descriptive to predictive, to prescriptive now. Big data itself has multiple meanings for different people, so it’s used to mean what people want it to mean.

 

Most of the work in terms of analytics around big data has happened on the customer side of the equation. On the operations side, I think the penetration of the capabilities that big data has brought to the table has been somewhat limited. As you know, in supply chains, there are tons of data points that get acquired as the operations move. For instance, if you take an example of a chemical company. There are plant-control systems that generate something like 7,000 to 25,000 data points a second, so huge streams of data that come through. On the distribution side, location and movement details of each individual SKU and product through the supply chain, and that’s a lot of data points as it moves through the supply chain, especially long supply chains like consumer electronics. There’s a ton of data out there that now we have the technology to be able to capture and store and analyze.

 

What happened is I think the technology has gone ahead of the ability to construct models of how to utilize these vast troves of data that are being captured and how technology can help accomplish that. Supply chain’s a great source of details on the actionable data, and big data analytics has immense applications in that area just as it is being done on the customer side and the outward facing part of the organization.

 

What can technology do to help facilitate decisions?

 

Well, the first thing is now that you have so much data points to be able to access that and make meaningful conclusions out of them, whether it is through actionable conclusions coming out of heuristics or statistics or just text-based queries, there’s a lot of technology out there that can help interrogate the data and draw conclusions so that organizations can respond effectively.

 

For instance, the example I was quoting before of the data points being captured in a chemical plant, for instance, the ability to react with that so you optimize the flow of material or the consumables into the plant is, I think, very integral to the optimal performance of the plant itself. In terms of taking the data and being able to put in the decision rules and the analytics that help drive deviations from the norm and highlight that to the individual operator so they can make the necessary adjustments I think is a very topical way of using big data analytics.

 

I think the bigger question in supply chain is the fact that in terms of optimizing the flow of product across a supply chain, being able to take the decisions at the right time based on detailed information. I think it’s a very critical element, as any supply chain manager knows. I think the key here, and this may be something to consider, is how you develop the capability to analyze that data that technology is now able to capture and provide in a platform.

 

How does this big data revolution translate into supply chains?

 

Like I said, supply chain, I think, has tremendous applications of the analytics around whether it is customer demand or product flow or manufacturing choices that people make. The integrated business-planning suite, which manages most of the area around supply chain, is a great source of detailed transaction-level data. In order to be able to query and analyze whether it is a straight textbook query or whether it is something where you look for deviations from the norm, I think that’s where the application of big data analytics becomes very useful. I think the key is being able to construct the right type of questions in order for that data to deliver the maximum amount of value for the organization. I think the interpretation of the data that’s available is going to be the key in the supply chain area to maximize the utilization of the data and its value.

 

Do you have any recommendations?

 

Yes, Dustin. I think the key recommendation I would make for organizations thinking about big data in the supply chain is to ensure that there’s a pool of talent not only to manage the data, but be able to query and interpret the data. I think the key is the understanding and analytics and being able to use the data.

 

The platform itself will, I think over time, become more of a commodity service, just as we have networks out there. Network providers provide the network, or communications capabilities are provided by outsourced software providers, infrastructure providers, but the key is for the organization to have the right talent within the supply chain to be able to ask the right questions with the data.

 

The ability to query the data for deviations for things that are out of the ordinary or things that need to be managed in order for the supply chain to be operating efficiently or in terms of discovering hidden patterns withinthe data. I think the key in big data is obviously pattern recognition, and that’s a different sort of skill than managing the flow of products through the supply chain. I think the key recommendation I would make is that organizations invest in the training & development of people to be able to utilize the big amount of information that’s available and make the right decisions.

 

Thank you, Lalit, for sharing.

 

You’re welcome.

 

 

 

About Lalit Panda

 


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Lalit Panda


Chief Information Officer

Tronox

 

LinkedIn Profile