Connecting Forward Deployed Engineers (FDEs) into the end-to-end product lifecycle - how IFS does it

• Summary:
• How closely should product developers work with the teams that look after implementation, service, support and customer success? And where does the role of FDEs fit in the product lifecycle? We speak to IFS about its unified approach.

People and businesses buy products to achieve an outcome. So why has it been so rare for a tech vendor's product developers to work alongside implementation, customer success and ongoing service teams? After all, these are the people that are in close touch with the customer's actual experience of using the product and its ability to deliver the outcome they bought it for. Yet product and customer experience teams typically report into entirely different management lines.

Despite this divide, there have been moves over the years to at least get these functions to work more closely together. The long-established notion of value engineering started out as a means of building the budget justification for technology investments, but in the hands of some vendors it has become the mechanism by which they set the KPIs used to measure how well their solution meets the outcomes the customer expected.

This approach dovetails with the emergence in recent years of the Customer Success function, most noticeably in the SaaS industry. Initially this was limited to monitoring how successfully the customer was adopting the vendor's product, but has since matured into a role that helps the customer achieve their desired business outcomes. In most vendors, however, there's been limited contact from the customer service and success teams back to the product development teams — they've been missing out on the opportunity to collect findings from the customer experience and close the feedback loop back to product developers, so that future iterations of the product can better serve customer outcomes.

I was therefore intrigued last year to see that enterprise applications vendor IFS has created the new combined role of Chief Product & Customer Officer, appointing Cathie Hall to be responsible for the end-to-end process of product ideation and platform development all the way through to solution delivery, support and customer success. When I last spoke to Hall a year and a half ago in her then role of Chief Customer Officer, we discussed how IFS carries out a Business Value Assessment to define the customer's goals and then builds dashboards so the customer can track progress towards them, supported by the vendor's customer success team. But when I spoke to Hall recently, a new factor dominated the conversation.

Enter the FDE

The rise of AI has brought with it the somewhat novel role of the Forward Deployed Engineer (FDE), again focused on customer outcomes, but this time almost a mirror-image of what went before. Instead of getting feedback after the product has been designed and delivered, the FDE goes out to customer sites to work with users to establish the business need, and only then design the agentic AI processes that will best serve that outcome. While at first glance this might seem to be the best way to match the resulting product to the customer's desired outcomes, there's a risk that it encourages custom engineering that might create unforeseen issues. The link back to product teams is just as valuable here to ensure that customer needs are satisfied in ways that still respect priorities for a robust, solid product. As Hall explains:

Sending an engineer in isolation can develop a solution, but is that solution really enterprise-grade? Is it really supportable? Is it really operable? Can we really roll it out globally? By bringing together both teams, we're able to answer all those questions in one. We see more and more customer engagement where we're bringing different people from across the team to engage and solve the customer's problems... in a way that, and [with] a depth of understanding that we just wouldn't have been able to do before, when we were working across different teams.

The feedback loop from customer service and success remains important to ensure that product developers understand where the product is failing to deliver the expected outcomes long after implementation. Customer support teams may discover user experience issues that are leading to incorrect usage or lack of adoption, while field service reports might surface poor-quality parts or design issues that lead to avoidable maintenance issues during a product's lifetime. Finding out about changing usage patterns or requirements and reporting those back to product teams may also help shape future innovation and modifications. But the rise of agentic solutions along with the FDEs that deliver them brings an entirely new set of co-ordination challenges across the entire product lifecycle.

Hall's role at IFS now manages all application and product development — "understanding what the customers want, understanding what the pain points are, the jobs to be done, and ... building the applications that respond to that" — along with technology research & development, security, cloud and AI operations, and the entire unified support function, along with consulting and success services. Bringing product and customer teams together requires a strong focus on a shared strategy, as she explains:

Both of these parts of a typical organization like ours are very large parts, and organizations at some point need to be divided up in order to get work done. That's how things work — in some respects, there's still pillars. I have a product pillar, a technical technology pillar, a success pillar under global delivery, and a unified support pillar. But the process I've taken is then to have these strategies that go horizontal, across the business that are owned by different leaders. So whilst we're still managed in groups, which explain the key skills of those groups, the strategies really force us to work in a different way.

AI enthusiasm and caution

The perceived potential of AI is generating enthusiasm for the technology that has to be tempered with caution about how it is delivered. She goes on:

Customers get very excited about Industrial AI, the ability to boost profits. We already know about 88% of industrial organizations report that they're seeing these boost by AI. But a lot of the discussions we're also having are about the governance, the trust, the transparency, the explainability, the understanding of what's happening, how are we preparing for the EU AI Act and so on and so forth.

For support teams, one way in which generative AI has created new challenges is in the flexibility it brings to the user experience. This makes it much harder for a support agent to understand the issue a user is reporting. Hall explains:

With the result of AI, generative user experiences are really easy to deliver. But unless you fundamentally change the way you deliver support, that's no good. You can imagine every support call that comes through, nobody can replicate any defect. Nobody understands where anyone's clicking on the screen.

On the other hand, AI tools can accelerate the process of finding defects and writing code to resolve them. She goes on:

We're not really far off solutions being able to self-heal, to be able to understand what's wrong with them. When we get much more sophistication in that, then it becomes easier to say, 'Okay, we can have very tailored, generative user experiences.' But the two really have to come together.

Combining the support, platform and product teams makes it easier to balance all of these factors. She says:

By bringing the organization together, bringing the leadership together, we're able to start to have those discussions and debates as well about the future and where we see the vision going. The technology and the product people [are] pushing and saying, 'Ah, we can do this [or] we can do this.' But then the more operational, customer-centric people say, 'Okay, we can do that, but it needs to come with these safeguards'... We're replicating, in some ways, the structure that our customers are asking for, because we're bringing together all the people that have the fantastic insight, the fantastic ideas, with the people that have that domain knowledge and experience and understanding of the customer, with the people that really know how to operate safely this type of technology.

Co-innovation

Hall's teams also work closely with the separate Nexus Black team, which was formed last year specifically to co-innovate new offerings with customers. That initiative has led to the creation of two new products that are now rolling out. One extends the vendor's existing scheduling and demand planning technologies to help streamline the flow of materials and products through the manufacturing process, while the other uses generative AI to assemble and analyze maintenance documentation and logs to help field technicians keep equipment running. Hall says:

We see increased collaboration between my team and the Nexus Black team as we look and say, 'Okay, to solve this problem for a customer, here's how we can work together to get the absolute best result.' I think, when we look at Nexus Black, their ability to think differently and solve differently, because they've not had the constraints within IFS of managing a huge solution, it's very easy to just go and have the freedom to innovate around a very kind of particular pain point for customers.

Rolling out such products beyond the early adopters takes a concerted effort across the full spectrum of Hall's various teams. She says:

When we're building new capabilities, we're working with the success team, we're engaged directly with a number of customers building out that capability. We've got full-stack engineers in there, product people, design people, so that we're really able to build what customers want and build something that we can adopt [as a product]. There's a phased handover over those first few customers, where the product and technology teams remain very much engaged to do refinements, to make sure that everything's working at scale. But we've also got the operations team, the success team, in there to make sure that knowledge is transferred. So that as we move forward to customer 20, 30, 40, there's an operation behind it that's very efficient, very slick, and able to deliver en masse to customers. That kind of approach was very difficult before, just because of the way that the teams were structured, but now we're able to pull people from those to focus on getting the job done for the customer.

My take

While the Forward Deployed Engineer may be quite a recent addition to the tech industry lexicon, the role it describes has been with us for some time. It's more than 15 years since Salesforce formed what it called its Innovation team to help discover with customers how they could use its platform to solve business problems. But this discussion with Cathie Hall at IFS surfaces some of the new complexities that agentic AI brings to the task of managing the product lifecycle.

There are new challenges in supporting products that have such diverse user experiences, in avoiding the creation of custom solutions that introduce unwanted scope creep, and in maintaining customer trust as the pace of technology innovation accelerates. At the same time, it's still important to remember that the lifecycle doesn't end when the FDE has completed the implementation — ongoing customer success management remains crucial to ensuring that the product continues to deliver the right outcomes for the customer as their needs and what the technology is capable of continues to evolve.