PODCAST: COVID 19 | Redefining Digital Enterprises
Episode 6: The Impact of COVID-19 on Supply Chain Management
Listening time: 13 minutes
The Impact of COVID-19 on Supply Chain Management
In this episode of AI to Impact podcast, Arun Krishnamoorthy, VP, Supply Chain Practice at BRIDGEi2i, discusses how the pandemic has affected the Supply Chain ecosystems throwing their sourcing network, lead times and data pipelines off balance. In the post-COVID era, they can be empowered with a high standard of data and analytics sophistication to cope and thrive. By allowing that, they could have a steady demand forecast based on sensing algorithms and react faster to such events.
Anushruti: Hello, everyone. You are listening to AI to Impact by BRIDGEi2i, a podcast on AI for the Digital Enterprise. My name is Anushruti, and I’m part of the CEO’s program office at BRIDGEi2i and the custodian of data around the sales pipeline. The COVID-19 pandemic has hit global trade and investment at an unprecedented speed and skill.
And over the past few weeks, on our AI to Impact podcast, we’ve been chatting with reputed AI & analytics leaders, digital transformation advisors and BRIDGEi2i business heads to gather their point of view on the current crisis challenges that enterprises are facing and some strategies to manoeuvre the COVID-19 situation.
Today we have with us Arun Krishnamoorthy, who leads the supply chain practice at BRIDGEi2i. To introduce him better, he has been a supply chain analytics professional for over 14 years. He has delivered hundreds of millions of dollars of impact to his clients in High-Tech CPG and Manufacturing Industries, particularly in the areas of demand forecasting, inventory and procurement planning.
Thank you so much for making the time, Arun. Welcome to our podcast.
Arun: Thanks for having me, Anushruti. Always a pleasure.
Anushruti: That is very kind, thank you. And I know it is a very difficult time for all of us. And it is even more difficult to encapsulate the effects of the crisis on supply chains. The urgent need to design smarter, stronger, and more diverse supply chains have been one of the main lessons of this crisis. So, let me get straight to the question that is on everybody’s mind. How bad is the situation?
Arun: Well, my reading of the situation is that it is not uniformly good or bad. I think to frame the vulnerability of a company to the economic fallout of this health and social crisis based on three different dimensions.
The first one is geographical dependence, which is essentially the concentration of their manufacturing and sourcing networks in a specific region around the globe. The second dimension is their lead times to go from materials to product and to revenue. And the third dimension is their data and analytics sophistication. So, you know, each time something like this has happened, you know, the High-Tech value chain, for instance, that is characterized by a largely Asian sourcing manufacturing network is characterized by long lead times and relatively low data and analytics sophistication that they are the slowest to react and the last to recover fully.
Anushruti: Interesting… very interesting to think about these three parameters and then consider the various industries. So, if I’m reading this right, CPG companies are a bit better off in comparison?
Arun: Relatively speaking, yes. You know, they have a fairly distributed global supply chain manufacturing and sourcing network. They have relatively short lead times to their customers and therefore, can react to changes from a demand standpoint quite quickly and relatively. They also have better data and analytics sophistication like third party aggregation of data and a fairly well laid out analytics stack. But they are seeing, you know, challenges of their own. product segments that have historically clocked five percent growth year on year are now seeing a 200 percent growth. You know, their distribution channels, especially in growth in emerging markets, are severely strained economically because of their size. If you look at a sub-segment of food companies, they are seeing major shifts in their demand patterns as well. So, a lot of even these companies will have to re-engineer their analytics to reflect this new market reality.
Anushruti: Right. So, whether they have it good or Bad, data and analytics is going to incrementally become a big focus area for companies across industries. Right?
Arun: That is very correct. Yes, analytics sophistication is absolutely central to decision making in the post-crisis era, especially for supply chains. You know, I often use the simile of a prancing horse and its reins. You know, the prancing horse represents an ambitious company which is intent on making giant leaps and winning against competition while the reins
represent the supply-chain organization. You know that gives it direction, method, and control in achieving its ambitions. It is even more essential now that supply chains are empowered with a high standard of data and analytics sophistication to be able to cost-effectively serve the company’s purpose and combat risks at the same time.
Anushruti: Perfect. Love the simile, by the way. When I listened to I think one would definitely wonder: What can companies do in such a situation? And do you think analytics could have predicted this crisis?
Arun: Well, by predicting the crisis if you meant if it could have predicted the health crisis? Absolutely not. Could it have predicted the economic fallout and the depth of it? No. Could it have predicted the duration of the crisis? The intensity of it? Absolutely not.
But what data and analytics could have helped companies to do is to react much faster. As the crisis evolved. From a supply chain perspective, per se this crisis is not unprecedented completely. You know the markets shake and the accompanying Swine Flu epidemic of 2015 and 2016, the Japanese tsunami and the Thailand floods in 2011 that shook up the high-tech value chain quite a bit, the great financial crisis and the accompanying H1N1 outbreak in 2008-2009, MERS and SARS before that in 2003. These are all data points for supply chains to estimate the scale, depth, and duration of their vulnerability. You know, just think about how the company 3M kept up with the production of the N95 mask demand during this very time, right? They did not predict the outbreak. They couldn’t have. But they were still able to triple their capacity two weeks from the Wuhan outbreak. And that’s what reacting fast is. That’s what a quick supply chain really looks like. You know, essentially, supply chains react. That is their nature. How much and how fast is something that analytics can tell.
Anushruti: Absolutely. It’s fascinating that you pointed out so many crises that have happened in the past, that could be good cues as to what to expect now. What would you advise your peers managing supply chains?
Arun: Well, that’s a loaded question, and I’ve got quite a few, you know, advice for my peers. But I’ll go over the big ones here in the interest of time? I think the first one is something that we are all seeing Anushruti. I think supply chains need to observe channel shifts as they are happening right now, and are likely to stay that way for a long time. You know, think about, you know, the movement from, you know, retail to e-commerce, specifically from e-commerce to all the digital channels. And that’s an important dynamic that’s happening right now. The movement from direct to distributor channel, when it comes to the high- tech industry, these are all channel shifts that are likely to sustain for a fairly long period of time, even post-crisis. What that essentially means is that the supply chain complexity just exploded three times and their demand and inventory planning must reflect this new reality. So that’s one.
The second is the value chain is made up of extremely large companies and pretty small players as well. We saw this happen in the 2011 Japanese tsunami when, for example, niche, custom silicon makers, and product designers were significantly strained, and actually finally drowned in the economic aftermath. Small distributors in the CPG value chain, for instance, that get you to the remote corners of the world, are similarly vulnerable because of the economic fallout. So, supply chains have to think about, you know, funding some of these small players and sustaining them through proper operating processes. You know, when this whole thing just plays out.
You know, one other advice I would give is to really forecast better, right. And I’m specifically talking about demand forecasting here. In the twelve-year bull run that preceded this crisis with short secular uptrends; statistical forecasting models could not really be differentiated from high powered causal machine learning models. You know, in terms of performance, at least. But now this will all start to make a big difference. So, my advice would be to focus their efforts on getting a strong demand forecast based on sensing algorithms for at least the top 20 percent of their portfolios.
For the other 80 percent, I would recommend that they elevate their forecasting time window and decrease their review period. Basically, they have been forecasting on weekly buckets, then it’s probably a good time to elevate it to a monthly level and then if they had been doing it at a monthly level, then it’s a good time to do it at a quarterly level, but keep their review frequency of their forecasts against demand as low as possible, as long as their supply chain processes allow them to do.
Simultaneously, another advice is really to stop buffering your demand signal unscientifically, you know, and please don’t go back to the safety stock formulae that so many systems are accustomed to using. They have been rendered quite useless at this time. Of course, in the interest of time, I can’t get into the details. But, yeah, that would be my big advice for my peers in supply chain.
Anushruti: Well Arun, I’m sure you have good reason to believe that the traditional ways of setting inventory targets will fail. And I’m also sure that a lot of listeners would like to know why. And folks, if you do, then please leave a comment and we will get back with the next level of discussion on it, with Arun of course. And I think your pointers are very helpful, Arun. I really liked how they vary from sustainable business strategies to review frequencies of the forecast. And I’m sure our listeners will benefit from this. There is no doubt that sophisticated analytics capabilities will continue to be a key ingredient for the Supply-Chain industry. Though come to think of it when do you think this will be over? When will supply chains go back to the normal rhythms?
Arun: Well, this really depends on how real the second wave of this crisis is going to be, how deep the economic fallout will be, and I think it is also important to think about what we define as normal. You know, some of these changes and shifts are tectonic, they are permanent, and there is probably a new norm in play. You know, Chief Risk Officers, for example, will no longer be confined to the credit industry. The risk will become a core Supply-Chain function and will be monitored very closely by the upper management.
But if you know, if I were to hazard a guess based upon the three dimensions that I mentioned, I think CPG companies would be the first to recover and get back to a sense of normalcy. And I see that happening before the end of this year. But high-tech companies, I think they’ll have to reconfigure their supply chain networks a little bit. And, you know, get to a sense of normalcy potentially around the second quarter of next year.
Anushruti: Honestly, it is heartening to see some light at the end of this tunnel, Arun. And our sincere thanks to thousands of supply chain professionals around the world who are tirelessly making life-saving products available to people where they need them. You guys are heroes.
And Arun, this was great. We will try to keep picking your brain from time to time. Thanks a lot for connecting with us today.
Arun: It’s my pleasure, Anushruti. Thanks.
Anushruti: And thank you so much for listening to this episode of AI to Impact podcast. That was a very interesting conversation with Arun, VP, Supply Chain Practice at BRIDGEi2i. If you found this interesting, do subscribe as we will continue the conversations with business experts and thought leaders in the upcoming episodes. They will be discussing the business impact of COVID-19 on various industries and how this journey looks for them in the future. Once again, thank you so much for tuning in. Bye-Bye. Stay home. Stay safe.
2020 will long be remembered for the pandemic that wreaked havoc on the global economy and disrupted communities and businesses in unprecedented ways. In our latest podcast series: COVID19 | Redefining Digital Enterprises, we will be interacting with several thought leaders, BRIDGEi2i Business Heads, Domain Experts, and reputed AI and analytics leaders to understand the various challenges emerging out of this crisis and the way forward for enterprises in the new world order. Tune in to know more!
Arun Krishnamoorthy is VP, Supply Chain, leading the supply chain and pricing analytics practice at BRIDGEi2i. In a career spanning over 14 years as a supply chain professional, Arun has delivered hundreds of millions of dollars of impact to his clients in the high-tech, financial services, and manufacturing industries through optimally leveraging data assets. At BRIDGEi2i, his mission is to develop cutting-edge frameworks for tackling new-age demand planning, inventory, and pricing challenges. He is Six Sigma Green Belt certified and has led several transformation efforts, particularly in demand forecasting and planning.
Arun is a mechanical engineer from Osmania University, Hyderabad, and has an MBA in Operations Management from K.J. Somaiya Institute of Management Studies and Research, Mumbai.