Episode Transcript
[00:00:03] Speaker A: Welcome to AINA Insights, where prominent leaders and influencers shaping the industrial and industrial technology sector discuss topics that are critical for executives, boards and investors. INA Insights is brought to you by INA AI, a firm focused on working with industrial companies to make them unrivaled segment of ONE leaders. To learn more about INA AI, please visit our website at www.ina.AI.
[00:00:40] Speaker B: Good morning and welcome to another episode of INA Insights podcast. Today we are joined by Jeff Nishandre, a seasoned IT leader and former Chief Information Officer at Harrington Process Solutions where he led the company's IT strategy and operations.
Before that, Jeff served as CIO at AmeriCare Royal, overseeing IT strategy, ERP integration driven by M and A activity and data analytics. As an expert in digital transformation and enterprise it, Jeff brings a wealth of experience across industries. Jeff, thank you for joining us and look forward to that conversation.
[00:01:21] Speaker C: Thanks for having me. Parthesh, it's great to be here.
[00:01:24] Speaker B: Awesome. So Jeff, you've left several digital transformations for SMEs, so jumping right in what should be the top focus areas when we are talking about enabling change in these organizations.
[00:01:39] Speaker C: Now, what I've learned from my experience and it is a learning experience, you get better with experience.
But I think some of the most successful transformations that I've been involved with really start with really clear business outcomes, right? Understanding what the success metrics are at the end. Is IT margin improvement? Is it to make us simply more efficient? Is it to drive scalability?
And I feel like the main things especially that I usually start with is data visibility.
[00:02:11] Speaker D: Right?
[00:02:11] Speaker C: Understanding your data, especially your master data, because you're going to need that to take advantage of all the technology that's at our disposal today. I think that the other things that SME should focus on are process standardization.
[00:02:26] Speaker D: Right.
[00:02:27] Speaker C: And really customer facing enhancements. Some of the best things that we did when I was at Amercare Royal was things that directly touched our customers and actually made it made the relationship stickier.
And one thing I can't leave out is I've learned to never underestimate change management.
It's about buy in and it's 10% it.
The rest of it is the people side. And really change management's not something that you just do once, it's something that you just keep doing daily. It's constant alignment.
[00:03:04] Speaker B: Yeah, yeah, absolutely. And especially with these legacy systems and in the industrial sector, that can be a big drag. So how do you kind of work through that? And at the same time you're layering the changes, the intelligence layer, the EMS software To kind of bring all those together to drive performance.
[00:03:26] Speaker C: Yeah, I think legacy systems are very common. You hear as 400, you even hear mainframe.
[00:03:32] Speaker D: Right.
[00:03:33] Speaker C: But the way I look at it is instead of a rip and replace, you know, I've had the most success kind of layering in and a layer around the legacy system using an APA gate, an API gateway, microservices driven approach to programming at that layer and then tools that allow for process mining such as Solanas. Because I think the most important thing is you can get the benefits of a modern architecture without upsetting the Apple cart with destabilizing your key ERP functions.
I don't think that you continue to invest in these legacy systems for 20 years, but I do think that it's a staged approach. And I don't wait to say, oh, you know, we'll drive our IT strategy once we get our ERP project out of the way. That's not something that I feel you should hold up value generation for.
[00:04:37] Speaker B: Yeah. So as you're doing this value generation, how do you measure that success of digital transformation? And in terms of measuring success, what are the metrics we should be looking out for?
[00:04:50] Speaker C: Yeah, depending on the industry. But you got whatever the key business metrics are, like in a distribution business or even manufacturing it, it has a lot to do with inventory accuracy, cycle time.
Very, very important in a distribution, especially one that does sourcing is planning, precision and more than ever, freight cost optimization.
[00:05:12] Speaker D: Right.
[00:05:13] Speaker C: So when I was at acr, you know, one of the things that, that we did was putting in a WMS with the tms. And by the way, we use the WMS embedded in our legacy software. And then we went to best of breed for TMS. We, we saw a 90% improvement in inventory accuracy to the point where we no longer needed physicals and a 22% reduction in outbound spend for freight.
So these are the metrics that from my experience, when you're in distribution and manufacturing, really show real impact.
[00:05:47] Speaker B: Oh, that makes sense. And then as these firms are doing these digital transformation, they're always, at least the tendency is to go to the latest and greatest cutting edge tech. What are the basics that they typically overlook that come back to bite them? Like talk about in terms of securing the data, securing the network, getting the foundation. Right. What's your experience in that?
[00:06:09] Speaker C: Yeah, it's a great experience. I think there's a lot of shelfware, there's a lot of vaporware and shelfware that people have paid for that they can't use.
[00:06:17] Speaker D: Right.
[00:06:18] Speaker C: Because they wanted to chase that best and brightest and be where everybody else is. On.
I said it earlier and I cannot say it enough is master data. Your items, customers, vendors, spending the time to get them organized and having a clean way of entering and maintaining their cleanliness is absolutely critical. And with that master data cleanse, there's really not much that you can't take advantage of even when you're constrained by legacy technology.
So in my mind, you know, it's a hybrid.
[00:06:52] Speaker D: Right.
[00:06:53] Speaker C: But the, the so, but the key is when you have your arms around your master data, you can be syndicating that from one source. So you don't need to be giving access to all these cloud, cloud data, cloud systems, talking to this system and that system to pull different things right off the bat. It's, it's about not exposing the data as much as possible.
You know, it's critical to have your basics right.
[00:07:19] Speaker D: Right.
[00:07:19] Speaker C: You have to have, you know, your, your email gateway security, your endpoint protection and, and a, and a strong network.
And I do think that one thing that, that I learned through experience is those APIs and that and that integration. Don't forget security when it comes there.
[00:07:39] Speaker D: Right.
[00:07:39] Speaker C: So that's something that you really have to go in on early when you're architecting. And that's something, you know, that I did learn a little bit the hard way years ago. But at one company, you know, we, we really went all in at acr, we went all in on cyber security. And it really does pay dividends not only in our audits, our annual audits for compliance, but more so in savings around cyber security, insurance and things like that.
[00:08:07] Speaker B: Yeah, definitely. I think all relevant and well said points. Thanks for that. So, Jeff, I'd like to shift the conversation and put the spotlight on you and your career.
So looking back at your career, what are the biggest shifts you have seen in IT systems and capabilities?
[00:08:27] Speaker C: Yeah, I'm a product of, I grew up in the 80s and the 90s and when I played video games, we had Atari and Colecovision. Right. And one thing I've learned is that we were very structured in our thinking. If this, then that and everything had to follow a right way. Like if you did, if you wanted to level up in our video games and you got killed, you had to start back at square one.
[00:08:53] Speaker D: Right.
[00:08:53] Speaker C: So for me, I think that that's been a seismic shift in where we see IT systems is that they become much more fluid, not so linear.
And I really do think though, that another major shift is that we went from.
It has really taken a different seat at the table. When I started in it, it was in the 90s, I was in supply chain and I moved into it.
We were purely a back office utility.
[00:09:23] Speaker D: Right.
[00:09:23] Speaker C: But now it is really becoming more of a strategic business partner. We used to look at our metrics like our SLAs, our uptime, our, you know, for like it could be a recovery point objective, a return to operation metric. But now it's really shifting and expected being more around agility, integration and driving innovation which I gave that example of the customer facing apps@amercare, amicare royal and that that's a big deal. But data is not just a reporting tool, it's now a strategic asset.
It's the key to everything. So I think there's real three things. I think that becoming definitely less linear and being able to be asynchronous in how we think about systems. Really being that partner and then going all in on your data, that's a.
[00:10:18] Speaker B: Great set of guidance and kind of developing the, changing the mindset and adapting now along with that though, how do you stay ahead of the tech changes or follow the tech changes?
[00:10:33] Speaker C: Yeah, I, I stay curious like a little, a little old school, right. But just using Google alerts and just following certain industries, trying to be connected and, and read daily, starting my day off by reading what's going on.
AI as you know is, is evolving at such a fast pace. It, it's, it's fascinating. You really have to stay on top of it daily to really see where it's, where it's moving. But really working really closely with vendors and their teams has always served me well in my career really going into that true partnership. Because when you're in a role of a cio, which I've been a long time, you kind of get used to your company and what you're dealing with. Really talking to these vendors and teams that have exposure to so many different industries, you learn from them, right. It keeps you growing and it keeps you seeing different perspectives.
And I do think that always evaluating new tech based on its potential to solve problems.
[00:11:33] Speaker D: Right.
[00:11:33] Speaker C: It's not about chasing the latest tool, it's really about staying really relevant to your business.
[00:11:41] Speaker D: Right.
[00:11:41] Speaker C: So I think that's really how I.
[00:11:44] Speaker B: Do it makes sense.
And then going back to industry trends, how should industrial leaders think about adopting cloud based systems?
[00:11:58] Speaker C: In my opinion, cloud, it's something that you can ignore. It offers agility, it offers scalability, but you need a strategy, right. So I usually start with analytics Or CRM in the cloud. Something that is almost an expectation like that, that's a standard way to do it. Like salesforce.com change that. CRM is cloud now.
[00:12:23] Speaker D: Right.
[00:12:23] Speaker C: And then keeping ERP hybrid.
[00:12:26] Speaker D: Right.
[00:12:26] Speaker C: It's great to be aspirational for cloud. If I was doing a greenfield, of course I would do cloud. But if you have something that's already on prem, you know, keep it going and take a hybrid approach until you really mature your workflow. Those.
[00:12:40] Speaker D: Right.
[00:12:41] Speaker C: In my mind it's about really balancing that agility with the operational stability.
[00:12:47] Speaker B: That makes sense. And then following the cloud based systems. How should industrials look at adopting the generative AI tools and technology and what data safety considerations should these companies keep in mind?
[00:13:03] Speaker C: Yeah, so when you read a lot of.
Because I do it all the time. I mentioned earlier, when you read about AI, you'll, you'll hear people that tell you, oh, you should be looking at these prompts.
[00:13:14] Speaker D: Right.
[00:13:15] Speaker C: And I, I keep going back to when I learned erp. I was a business guy, I was a supply chain leader and they moved me into, into it. When I was at News Corp and we rolled out an ERP system throughout the corporate corporation. What my manager, who's still my friend, told me at the time, she said, you need to understand how this system thinks.
[00:13:36] Speaker D: Right?
[00:13:37] Speaker C: And I did. Right. So I understood the table structure, I understood the program, I could read a program. I knew what the inputs were, the outputs were, I knew what it was doing, I knew what parameters were passing at runtime.
I think that really to understand the safety and data concerns with gen AI, I do think that you need to spend some time to really understand what's going on under the hood.
[00:14:01] Speaker D: Right.
[00:14:01] Speaker C: So I've been doing a lot of that lately and it's fascinating because when I was just reading those articles about, hey, you prompt this and you prompt that.
Now I'm learning, you know, how it ingests images, how it learns and really getting into its brain to figure out what it's doing. It's much easier on the, on the data side, the graphical side, to do that than it is on the, on the pure data. But I do think that you got to understand how it thinks. But then you have to understand what data you're exposing, right? And validate those outputs.
And you have to implement governance. It's just like anything else. Just like you have governance for master data, you have governance for close and financial data.
You know, you have to have those controls in with these tools. I do think AI should be a Co pilot, not a decision maker at least now, especially in a regulated or IP sensitive environment. I was in one meeting and one of the leaders was talking about how they were using ChatGPT and feeding in all this data and it was amazing because they were able to understand all this different equipment. And the point I made was yeah, but then that's out there, right? If you're not using it in a secure model, the competitors can find out that what you're doing and immediately you'll lose your secret sauce.
[00:15:19] Speaker D: Right.
[00:15:19] Speaker C: So that's my, my take on, on data concerns.
[00:15:24] Speaker B: No, absolutely. Those are all industrials especially live and breathe that and that's a big challenge. Now, along staying with the industrial theme, besides AI, what technologies do you see have created the most value in the industrial and manufacturing space?
[00:15:45] Speaker C: You know, I'll start with the, the oldies but goodies.
[00:15:48] Speaker D: Right.
[00:15:48] Speaker C: So there's something to be said for you know, a fine tune electronic data interchange. It's still out there, it's still used.
[00:15:56] Speaker D: Right.
[00:15:57] Speaker C: So I see, I feel like really having really good data exchange whether it's via an API or whether it's old school edi. I think that that's definitely a table stake.
[00:16:07] Speaker D: Right.
[00:16:07] Speaker C: At least in consumer goods manufacturing or sourcing.
Warehouse automation I think and transportation management continue to pay dividends and labor optimization and frankly in inventory turns and how you move.
But then more on the modern side I think that process mining is a game changer and I think now supplementing that with the power of AI that's available now and process mining, I've used a product called Salonis and basically process mining is a great, great thing because it takes your transactional data, it reverse engineers the business process and it tells you where things are being held up, where you're, where you're driving delays.
And I think it's a, it's essential to actually figure out where to fish to know where you should apply the, the AI and, and, and the machine learning. And then lastly I think AP API platforms are, I think they, that started right in the early 2000s but now I think where they are they're a must have. So I think they're really the ones that I think are the highest impact.
[00:17:25] Speaker B: Jeff, this was super insightful. In closing, what advice would you have for first time CIOs leading a digital transformation?
[00:17:35] Speaker C: I would start by listening. We all like to jump right into solutioning and I've been guilty of that in my career and it's, I'm a recovering addict but it's something I always have to keep my eye, my eye on. But start by listening and then building the trust. Because through listening and relating with others, you build the trust, have a high level roadmap and prioritize quick wins.
[00:17:59] Speaker D: Right.
[00:18:00] Speaker C: And I think that what I've learned that communicating process progress constantly and aligning with the, with the overall business strategy, it's critical because it's really not about knowing it all. It's it's all about really empowering your team and your stakeholders, in my opinion.
[00:18:21] Speaker B: Well, thanks a lot Jeff for your time and all the insights and knowledge that you've shared. Appreciate you coming on our podcast and good luck to your future endeavors.
[00:18:32] Speaker C: Thank you. I appreciate it. Partesh. Have a great day.
[00:18:35] Speaker B: You too. Take care.
[00:18:41] Speaker A: Thanks for listening to INA Insights. Please visit INA AI for more podcasts, publications and events on developments shaping the industrial and industrial technology sector.
[00:18:57] Speaker B: SA.
