Ashish Chaturvedi — Executive Research Leader, HFS Research[00:21]
At HFS Research, we recently released our Intelligent Supply Chain Services Horizons study, where we assess how enterprises are rethinking supply chains in the face of disruption and how they are accelerating their journey towards resilience through technological developments in the field of AI and automation. In this research, Mindsprint was positioned as a Horizon 2 enterprise innovator. In simple terms, that means that they are already helping clients move beyond functional efficiency into more connected AI-enabled supply chains. But they are operating in a market where most enterprises are still early in their journey. Today I’m joined by Rohit and Unnikrishnan from Mindsprint for an open, unfiltered conversation. And it’s not about Mindsprint, but about some market realities that the study revealed. And what Rohit and Unni’s reading is about where we are heading next. So Rohit and Unni, let’s have a quick 30-second introduction from each of you.
Rohit Sharma — Senior VP and Global Supply Chain Practice Leader, Mindsprint[01:19]
Thanks Ashish and thanks for having me on this platform today. It’s been a pleasure knowing and working with you on a few of the critical supply chain projects in recent past. I’m Rohit Sharma. And as a part of my responsibility, I lead the global supply chain practice in Mindsprint as a senior VP. I’ve been with the organization for very close to six and a half years and bring overall 27 plus years of experience working in different countries, geographies, and industries. All this while helping businesses to transform their supply chain to be agile and future ready to manage global disruptions seamlessly.
Unnikrishnan Sasikumar — Assistant Vice President, Mindsprint[01:59]
Ashish, thanks for this opportunity. Happy to connect with you again. At Mindsprint, I head the consulting team. We call it the business transformation services practice. Our role is really to engage with clients and understand areas where reinvention with AI and technology is possible, right? And then really put a value to that and then work with our technology teams to execute and orchestrate that value. Happy to connect and share our thoughts on how we see the client journeys evolving from just visibility, how it has been the core of the ask to more insight-led operations as we see it today.
Ashish Chaturvedi — Executive Research Leader, HFS Research[02:39]
So let’s start with talking about where enterprise demand is showing up right now. So around 60% of enterprises told us that most of their work with service providers is focused on time planning, followed by control tower provisioning, followed by supplier collaboration, followed by automated planning systems. So there were many elements of automation involved, but it has not gone to a point of fully autonomous or self-driven supply chains. Now, from what we are seeing or what you are seeing on the ground, what kind of work is actually coming your way right now? And how has that work shifted compared to 12 to 18 months ago? Rohit, why don’t you take this one?
Rohit Sharma — Senior VP and Global Supply Chain Practice Leader, Mindsprint[03:21]
Thanks for your question, Ashish. And I would say it’s spot on with one of the supply chain case studies, which highlights clearly how real time planning, visibility and supplier collaboration remains, you know, the core of the client engagements today. From my vantage point of supply chain as a supply chain practitioner and focusing on supply chain holistically, that is, you know, covering the all aspects of supply chain right from plan, source, make, deliver. The work coming our way right now mirrors that actually.
We are about 70 to 80% of projects center on supply chain visibility through AI-driven dashboard, predictive prescriptive analytics, streamlining supplier collaboration via integrated platform and enabling real-time decision-making to handle demand and supply gaps, which could be very critical to any of the organizations, irrespective of the industry they operate into, to manage their, you know, disruption. If I have to compare for 12 to 18 months ago, we are seeing a very clear evolution and change in strategy of most of the supply chain professionals. You know, back then, efforts were heavily tactical. Think manual Excel-based forecasting, siloed supplier portals, vendor-based approach, etc., etc. But now clients are pushing for more integrated tech-enabled solution, agentic AI for automated exception handling, blockchain, end-to-end traceability for global trade, and collaborative ecosystem. That is how I see a shift is being happening. And of course, data in this all playing a very vital and crucial role to bring that autonomous approach.
That’s where we in a Mindsprint working very closely with our clients to have a dive deeper and enable this approach by having the right strategy. And just to bring an example here and perspective earlier, where multiple standalone solutions were in place to manage larger supply chain. And now what we’re working is that completely shifted from those one-off supply chain tools to full stack. You know, AI-led platform, which we named as the TradeSprint, which autonomously takes care of full end-to-end supply chain process, right from once business is being concluded until, you know, the goods being delivered or service being delivered and money being received. So that is how it is transforming the entire eco-chain or covering entire eco-chain and managing through one single platform, bringing all those data through IoTs, through SAPs or through ERP platforms and combining them together with a minimal deep human intervention, bringing all different kind of optimization which the customer is looking out for. So that’s the transformation I could really share as an example.
Ashish Chaturvedi — Executive Research Leader, HFS Research[06:13]
So on that point, it’s a nice segue to my next point of discussion where I would like to bring Unni in. And this is around enterprise spends versus technology investment realities. Now, this is another interesting dynamic that surfaced from the study. If you look at the enterprise side right now, investment is still dominated by analytics, modernization, data foundations, and cloud. Now, this is where most of their money is getting spent. But when we looked at technology and product companies likes of Microsoft, SAP, Oracle, so on and so forth. They are going all in on generative AI and agentic architectures. So their spending is on agentic and generative AI. Now, how do you interpret this gap between where enterprises are spending for today, whereas technology vendors are investing for tomorrow and keeping the future in mind? And how do you balance what’s relevant right now versus what you believe will become essential for your clients two years from now? So how are you balancing this investment in today’s technology versus tomorrow’s technology? Unni, it’s your thought.
Unnikrishnan Sasikumar — Assistant Vice President, Mindsprint[07:14]
Thanks, Ashish. Interestingly, very recently, this was a hot topic in a conversation with the CIO of a large commercial auto company here. And the problem is there because the gap exists because enterprises are really focusing on trust on the data, right? And because if you don’t have trustworthy underlying foundation, you really cannot build, innovate for future. Whereas enterprises are looking at tools and agentic solutions to be onboarded into their existing landscape, right? But for me, the way I look at it is, right, while if you look at it, it’s like the nervous ecosystem of an organization, right? The whole analytics engine could be the brain and the current invoke thing around agentic could be the hands and legs to execute, right? But if we don’t have the really data right, it’s almost like the nerves, right? If it’s not there, then the right hands and legs don’t move in the right direction, right? So hence, data is really critical. But having said that, and hence, many organizations are continuing to work on building, strengthening their data foundation. And we see that with many of our large clients who have started on this journey since three, four years back. Right. They have still not solved for that entire data authenticity or data accuracy part of the story. Right. And what they are also doing is they’re all. So in many cases, we see the tools which service providers are providing are also being used to accelerate the whole aspect around data governance, right, where some of these tools have been used to validate the data, data accuracy, and also accelerate the whole digital adoption, right? That’s happening. Now, coming back to your question around our take, right, around this and where, what is it that we are investing in? So we continue to focus on working with our clients to build that strong data foundation that has got multiple elements of that, right? Getting the whole strategy right, whether aspects like data freshness to be understood. At times, for example, if you want to put an autonomous system, which is sensing a delay in a shipment of your raw material, and hence, but then underlying data in ERP says that you have enough safety stock. And hence, you don’t order, right? But reality is you reach a stockout situation. Now, such scenarios can happen if you really want to reach an autonomous supply chain operating stage. And hence, the whole data freshness and accuracy becomes important, right? And the other aspect is conflicting truths of data. Now, on that vessel, there are two data points which is coming. One from the port terminal, you are picking some data and the vessel liner is giving you some data. Now, whose data do you believe? One is telling you that there is a delay and the other is saying a different truth, right? So hence, there are finer nuances to this to get your data strategy right. And we are working with clients to not just set up this strategy, working with them to set up really the foundation and build layers and capabilities to make sure this data is authentic. Further, I think we are also seeing that kind of why you’re building for data. We are also seeing organizational change and capability building is also very critical. So, and hence for many of the clients with different data and analytics frameworks that we have worked up on, we are also helping them set up capabilities as an organization. For example, with one of these clients, we are setting up a data and agentic AI CoE, which is helping them build the right guardrails framework to accelerate whichever parts of that data that they have already built robustness on, so that they start seeing value coming for their organization. So we see while this is happening, we are also working on some specific use cases like on our platforms like ProcureSprint and TradeSprint and Sprint AP that we have built. In many of these cases, our agentic AI solutions that we have built are also ensuring that there is, for example, the procurement data, which otherwise was not digitized completely through this procurement platform, are able to make sure that now you have great amount of data on how a supplier behavior happened during an RFQ, which is a great insight for you to run an autonomous procurement operations for your tailspin vendors in future, where you can even now start doing negotiations because you have all that data on how they behave in the past now getting digitized and captured.
Ashish Chaturvedi — Executive Research Leader, HFS Research[12:08]
At the start of your answer, you were mentioning about technology landscape. So let’s focus on the technology landscape right now. The study also revealed a very clear technology landscape where SAP and Microsoft emerged as the top two technology stacks used by enterprises with a noticeable gap to Oracle as a distant third. At the same time majority of the enterprises in fact 60% of enterprises told us that they are also leveraging supply chain focused startups and scale-ups right now especially in the areas of niche planning, visibility, risk and sustainability. Now I would like to bring Rohit here. How are you right now thinking about your partner strategy in a world where still SAP is dominating the core, but now innovation is increasingly coming from a growing ecosystem of startups and specialist firms?
Rohit Sharma — Senior VP and Global Supply Chain Practice Leader, Mindsprint[12:58]
Well, I would say it is indeed very interesting. And this is actually a very powerful and thought-provoking question towards, you know, finding out the right balance between market-dominant ERP players or leaders and the specialist startups adding a lot of speed and agility through the out-of-box innovations. And that’s where I believe it becomes very critical to develop an ecosystem to reap the benefits which these startups have got to offer by bringing new technologies and solutions, along with the stability which market-dominant ERP players could provide and then both of them to be the part of this combined ecosystem to maximize the potential. And, you know, in this hybrid market, our partnership strategy is all about, you know, finding right balance between the reliability of SAPs, Microsoft, oracles of the world as an ERP dominance perspective. And at the same time, on board with the agility of specialist startups to deliver rapid innovation as a wraparound and bolt-on solution to such an ERP and naming few of them, like maybe OpenTags, ServiceNow, KYP.ai, etc., etc. If I look at the part of my core approach, I would say we prioritize deep integration such as, for example, via SAP BTP, enabling seamless stitching to startup capabilities with ERP environments to real-time visibility and AI-driven optimization in supply chain, procurement and logistics. However, this also mirrors enterprise trends where 56% of enterprises are increasingly blending with specialist startups with their own ERPs to have larger benefits without disrupting their current ERP or the investment they have already made into the technology as highlighted in recent ecosystems analysis. For example, again, one of our flagship procurement platform taking care of end-to-end source to pay seamlessly with few of the specific and niche capability brought in by specialist startups to provide unique and wholesome experience in every component of the larger supply chain or larger procurement sourcing organization with a very competitive environment such as supply scouting, risk and compliance, contract lifecycle management, spend analytics, etc., which could be, you know, a long-drawn solution when you deal with those market-known ERP products. To cut short, I would say key pillars here, it could be more about co-innovation focus, where I would want to invest in hackathon and modular app development on SAP ERP marketplace to develop hyper-hybrid solutions, ensuring startup scale within our controlled ecosystem and bringing supply chain resilience and second thing is about Microsoft synergies where again leverage joint initiatives like RISE with SAP or Microsoft cloud for accelerated cloud ERP migration incorporating Azure AI to enhance analytics while onboarding scale-ups to domain specific intervention and I think that’s where the select partner based on proven ERP interoperability, starting with pilots in, for example, tailspin management and control towers, and then expanding to full deployments. I think that’s the strategy what we built into our day-to-day execution and ensure we have those partner as a part of our own ecosystem, wherever we balance with both the benefits coming out for both market leading products versus the startups and to bring that combination together to our customers and the client.
Ashish Chaturvedi — Executive Research Leader, HFS Research[16:47]
One of the more candid messages from enterprise buyers in the study was that they want in the areas where they want their service providers to improve. And the top one was be more innovative and do a much better job of tying innovation to business outcomes with clearer roadmaps, milestones and ownership. From your perspective, where do service providers, including firms like yours, most need to pull their socks up if they want to stay relevant in the market, which is moving from efficiency towards intelligence. And this one is for Unni.
Unnikrishnan Sasikumar — Assistant Vice President, Mindsprint[17:20]
Yeah, so I think we rightly said last few years, I think there were a lot of AI pilots happening. Some of them have really not scaled. I think the narrative in many companies is now shifting towards AI, for AI is definitely not going to work just for the sake of doing AI, right? Companies definitely are looking at AI to deliver business outcomes. It could be outcomes like how do you improve your working capital? How do you improve your gross margin? Right. Or improve your customer experience and thereby you improve your sales and revenue. Right. These are the kind of broader themes that we see. Companies are really questioning every single AI based project. And in our own many of our projects, we see clearly that ask coming and also means that the tech service providers would need to build holistic business and domain understanding, not just be people who are giving few FTEs as on T&M basis, right? If they really need to be there and work with the client to reinvent and drive value for the client.
Broadly today, the way the Mindsprint is looking at it is we are definitely taking a very value focused approach at most of our projects and we are able to do it through maybe I could say maybe three basic capability interventions that we have led, right? One is really the whole consulting led engagements for our clients and for example my team would get into conversations with clients to do a whole envisioning exercise to look at how will that North Star look when you want to leverage some of these technologies, including AI autonomous ways of working, and then build a whole roadmap considering their current maturity and where they are, right? And put critical milestones with the whole value narrative around it. Now that, while a business consulting team is able to do it, there are many cases where we are driving these assessment also with our proprietary tools like for process assessments, right? So for example, we have QIP.ai, which can go very granular and also understand exception scenarios, right?
For example, if we were to do a whole invoice touchless automation, through this tool, we are able to map most of the edge scenarios. And hence, we can commit to some number in terms of outcome. With a client, which is an airport operator in Asia, we took on a project to significantly drive value in their AP process. We could commit to almost 95% touchless happening and a significant cycle time optimization. And we were able to give that commitment because of some confidence in the process assessments that we did. That’s one of the whole assessments as a narrative. The other one is around the whole AI pod model that we are working. Rather than saying for a client that we will give you a few headcounts, we are saying that we will work on a sprint-based model. For every sprint, there will be clear outcomes that our AI pod will deliver. With that, we will validate those outcomes. And that’s how we move to the next sprint, right, with our specific pod.
And the kind of people that we bring into this pod are a mix of very business, technology, data scientists, right? Essentially, and we keep increasing or reducing the capacity to meet outcome requirements for a specific sprint. And the last one, we value really in our service architecture itself, right? For example, the whole services offering that the process services offering that we do today is no more saying that we take 10 FTEs of yours and manage it with five, right? The whole narrative is shifted from saying that today, what is the cost and service levels and timeline for executing a particular process at your organization? And how do we do it better? And also have a roadmap to really take it to the next stage over a couple of years after we take over that, right? Really transition the process, transform and commit to some outcomes in this whole as a part of our service delivery. And we see more and more organizations will have to do that if they have to really survive and win in this new world.
Ashish Chaturvedi — Executive Research Leader, HFS Research[21:46]
Thank you both for a very open and grounded conversation. If there is one clear takeaway from the study and also from this conversation is that the market is moving forward. Everybody agrees to that point, but it’s not moving forward in straight lines. So most enterprises are still focused on getting the foundations right. At the same time, if we look at the technology investment trajectory, it’s clearly pointing towards more autonomous and AI-driven supply chain kind of work. Thank you once again for sharing what you’re seeing from the front lens.
Unnikrishnan Sasikumar — Assistant Vice President, Mindsprint[22:16]
Thank you, Ashish.
