case studies
Customer Information Systems and Sales Processes in Defence
Noel DCosta
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When defence programs ask for Customer Information Systems, they are usually asking for control. They want visibility. They want to stop chasing answers across teams. And they want systems that can actually support the pace and structure of long-cycle sales—without adding more admin overhead.
From what I have seen, these systems are not about just tracking contacts or managing a CRM database. In the defence sector, they support far more complex layers:
Multi-year sales cycles with shifting stakeholders
Export controls and compliance records that tie back to specific opportunities
Detailed alignment between capture, delivery, and commercial workflows
Internal approvals and handshakes that follow different chains of command
The challenge is rarely technical. It is more about fit. Most tools were built for fast-moving consumer models. Defence does not work that way.
And that is where the right structure—often supported by consulting frameworks—makes a difference. You do not always need a new platform. Sometimes you need to make the one you have match how your teams really operate.
This article shares what I have learned building, adjusting, and fixing these systems in real defence programs. Not theory. Just what holds up when teams start to lean on the system for actual decisions.
This project connected Microsoft Dynamics CRM, Experlogix CPQ, and SAP SD to streamline customer data, quoting, and order processing for a UAE-based defense manufacturer. The result was a more reliable, integrated workflow built for accuracy, control, and long-term scalability.
Client – Middle East Based Defence Manufacturer
1. A Manufacturer Built for Precision, Not Volume
The client is a mid-sized defence manufacturer based in the Middle East. They are not a public-facing brand, and visibility is not the focus. What matters is precision. Every component they produce ends up in military aviation or secure communications.
Their work is highly engineered. Sales cycles run long. Layers of technical validation and internal approvals shape every deal. Not chaotic, but definitely heavy. And their Customer Information Systems? Fragmented, at best.
2. When Internal Systems Stop Lining Up
Sales had one tool. Support had another. Operations leaned on PDFs or outdated exports. Everyone had information—just not the same version of it.
It functioned, for a time. But then quoting started slipping. A contract went out with the wrong spec. The same customer was entered multiple times, under slightly different names.
3. A Push for Clarity, Not Complexity
That was when I was brought in. Not to replace everything. Just to fix what had clearly become friction.
As their Digital Transformation Director, my role was to bring structure to what they already had. I focused on aligning their Customer Information Systems—not by adding complexity, but by making sure people could finally trust the data they were working with. That trust changed how teams operated. And that was the real shift.
Business Problem – Customer Information Systems Were Not Connected
The client had Customer Information Systems in place. Technically, yes. Data existed, tools were being used, and there was activity. But none of it connected in a way that supported how the business actually operated.
Sales used one system. Support had another. Operations often worked from spreadsheets, offline files, or PDFs that were already out of sync by the time someone opened them.
It looked organized on the surface. But once you tried to trace a quote through to delivery, gaps started to show. And they added up.
The impact was not always visible immediately, but it showed up in the background:
Delayed approvals and inconsistent pricing
Quotes lost in email threads
Repeated clarifications between teams
Audit gaps when compliance asked for traceability
The issue was not only about where data lived. It was about how work got done. Without alignment between systems, every step took longer. And the more complex the deal, the more fragile the process became.
Customer Information Systems should reduce friction. In this case, they introduced it. And when friction becomes the norm, accuracy, trust, and speed all start to fall apart.
1. Multiple Tools. No Single Source of Truth
Customer data was everywhere—and nowhere consistent.
Records were duplicated across platforms
Different teams updated different fields in isolation
Naming conventions varied, even on critical accounts
No one really knew which version was the right one. It made collaboration harder than it needed to be. Conversations that should have taken two minutes turned into slow back-and-forths just to confirm the basics.
There was no structured ownership of the data. And without a single source of truth, decisions started leaning more on workarounds than on the system itself.
2. Delayed Quotes, Duplicate Records, Manual Workarounds
Quoting was manual, inconsistent, and dependent on individual habits.
Some reps worked off old versions of pricing sheets
Others reused previous quotes as templates, even when configurations had changed
Approval processes varied depending on who was asking
There was no common flow. Which meant even basic quotes involved checking multiple sources, validating line items manually, or asking engineering to double-check what should have already been enforced by the system.
It slowed things down. Not drastically all at once, but often enough to lose momentum. For a business with long sales cycles, those small delays made a big difference.
Project Objective – Build One Reliable Customer Information System
The goal was not to overhaul everything. It was to bring clarity to something that had gradually become unclear—Customer Information Systems that no longer supported how the business actually worked.
There were too many tools. Too many versions of the same customer record. The quote-to-order path had drifted across functions, and no one really trusted where the information came from anymore.
We needed to reconnect the dots.
The aim was straightforward:
One place to see the full customer profile
A shared view across sales, support, and operations
No re-entry, no guesswork, no chasing approvals across email
Customer Information Systems are meant to support flow. In this case, they had been working against it. So the work was not about adding features. It was about building one structure that teams could rely on—one that would hold together, even when things moved fast.
It started with mapping where the data lived. Then identifying where processes broke down. Then gradually layering the systems into something dependable. Not perfect. But solid.
1. Integrate Sales, Support, and Operations into One View
Each function had its own version of customer data. Some used CRM. Others worked from SAP exports or internal trackers. None of them matched.
Integration was not just technical—it was operational. What mattered was giving all teams access to the same truth, without forcing them to change how they worked overnight.
Once the systems started to reflect the actual business flow, things began to align. Meetings moved faster. Support needed fewer follow-ups. Sales had fewer corrections. Small signals, but they added up.
One shared view changed how people made decisions.
2. Eliminate Friction Across the Quote-to-Order Process
Every quote used to be its own manual effort. Pricing, configuration, validation—handled differently depending on who was involved.
Fixing that meant creating a path with fewer handoffs. And fewer opportunities for things to get lost.
The focus was on:
Validating configurations earlier
Reducing approval bottlenecks
Automating data flow into SAP for clean order creation
Customer Information Systems only help if they reduce hesitation. Here, the friction was mostly procedural. Once quoting became structured and connected, it stopped being a bottleneck. It became part of the flow.
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Tools Implemented – Microsoft Dynamics CRM, Experlogix CPQ, SAP SD
Fixing Customer Information Systems often begins with a decision: replace everything or stabilize what is already there. In this case, the smarter path was to build around platforms the client could grow into—without asking every team to relearn the way they worked.
Microsoft Dynamics CRM became the foundation. It gave us a reliable place to structure the customer record and unify sales data. From there, we layered in Experlogix CPQ to bring discipline to quoting. Finally, SAP SD, already in use, was integrated properly—removing the need for manual re-entry and stitching the process together end to end.
Each tool solved a different problem:
CRM gave visibility
CPQ enforced structure
SAP SD delivered execution
But none of it worked in isolation. The value came from how these tools were connected. That is what turned the Customer Information Systems from fragmented to functional.
1. Why Microsoft Dynamics Was the Foundation
We needed a place where customer data could live—accurately, and with full context.
Microsoft Dynamics CRM offered that. It allowed us to centralize the customer record, tie sales activity to actual accounts, and slowly pull in support and operational views.
Flexibility mattered. So did familiarity. The platform did not feel foreign to users. It just needed to be shaped around real use cases. Once people saw the same information, in the same way, across teams—it started to click.
This was not about features. It was about trust in the data.
2. Experlogix CPQ – Enforcing Structure, Reducing Errors
Quoting had become overly dependent on memory and manual edits. The risk was not just slowness—it was inconsistency.
Experlogix CPQ introduced logic into the quoting process. We configured it to reflect real-world complexity:
Product variants
Military-specific pricing
Validation rules based on contracts
At first, some users found it restrictive. That was expected. But once the structure held, quoting became repeatable. Errors dropped. Engineering had fewer corrections to make.
And quotes that used to take days to finalize were going out in hours. Sometimes less.
3. SAP SD Integration – Cutting Out Manual Handoffs
Before integration, quotes were handed off manually. Sometimes retyped. Sometimes pasted. Errors crept in that no one caught until late in the process.
Using SAP CPI, we connected Experlogix CPQ directly to SAP SD. Customer data, line items, pricing—everything flowed straight through.
This was not about fancy automation. It was about removing places where mistakes tend to hide.
Order accuracy improved. Entry time dropped. And users, particularly in operations, finally stopped needing to double-check every transfer.
The workflow moved faster because it was finally clean.
Breaking it down further...
It’s hard to point to a single turning point. There wasn’t one tool or decision that fixed everything. It came together gradually—one layer at a time. Each part solved a piece of the problem, and honestly, we didn’t get it all right on the first try. But once the pieces were in place, things started to move more easily.
The focus wasn’t on reinventing the way people worked. It was on clearing the friction. Making sure the right systems were connected. The right data was trusted. And the right people had what they needed—without chasing it down.
A. Microsoft Dynamics CRM
We started with Microsoft Dynamics CRM. Not because it would fix everything, but because it gave us a place to start untangling the data.
Customer records were centralized. That part was expected. But what made the difference was how it began to pull teams together—sales, support, even ops—around a shared understanding of who the customer actually was.
We integrated it with Outlook, service channels, and a few internal tools. Some of it felt routine. Some parts were more involved—especially where manual workflows had quietly become the default. Still, the end result was real visibility. And more importantly, trust in what people were seeing.
B. Experlogix CPQ
Before CPQ, quoting was a mix of best guesses and memory. Reps used past quotes, spreadsheets, emails—whatever got the job done. It wasn’t reckless, but it definitely wasn’t scalable.
Experlogix changed that. It gave structure. Rules were embedded. Product configurations followed logic instead of instinct. And while it did feel limiting at first (some weren’t shy about saying so), it also cut out the ambiguity.
We customized it heavily—military-grade configurations, contract-driven pricing, layered validation. It didn’t all land perfectly the first time. But after a few cycles, the feedback shifted. Quotes became faster, more consistent. People stopped double-checking things manually, which was kind of the point.
C. SAP SD Integration via SAP CPI
The integration between CPQ and SAP SD was handled through SAP CPI. That piece mattered more than most people expected.
Before, moving a quote into SAP meant a second round of data entry—or worse, reformatting. It introduced errors, slowed things down, and honestly, felt like busywork. With CPI, the handoff became automatic. Quotes pushed straight into SAP. Customer and order data synced in near real time.
It wasn’t glamorous, but it was the connection point that let everything else hold together.
D. Security & Compliance Alignment
Security drove every technical decision. There wasn’t a lot of room for shortcuts—not in this environment.
Access controls were tightly defined. We set role-based permissions across all key functions, with audit trails capturing quote creation, approvals, and changes. Not every user loved the guardrails, but they were necessary.
We also addressed data residency upfront. Nothing left the region. No exceptions. That conversation happened early and often—for good reason.
E. Deployment Approach
We didn’t roll it out all at once. That would’ve backfired.
It started with a pilot—small group, specific use cases. We tested edge scenarios, surfaced gaps, and made a few changes before scaling. Training was kept practical. Short sessions, targeted materials.
SAP CPI handled the integrations. Where we hit limitations, we added custom logic. Not elegant in every case, but it worked.
Looking back, it wasn’t perfect. But it was grounded. It respected how people worked—and gave them something better to work with.
Delivery Approach – Layered Rollout with Early Validation
We did not try to roll out everything at once. That would have broken too much, too fast.
Instead, we built the Customer Information Systems one layer at a time—testing as we went. Not because we lacked confidence in the tools, but because in these environments, process changes ripple out fast. You fix one thing, and suddenly ten others feel off.
The structure was simple.
Start with a small group
Limit the process scope
Make feedback part of the build
We picked one part of the quote-to-order flow and ran it through live. It showed us what held and what cracked under pressure.
More importantly, it gave users space to adjust. That part often gets underestimated. People do not change how they work just because the system says so. They change when it starts helping them—without getting in their way.
This wasn’t about speed. It was about sticking the landing. And for Customer Information Systems, that usually means getting trust back, one phase at a time.
1. Start Small, Prove Value, Scale from Success
We did not try to prove the whole program in one go. Just a piece. One quote flow, one product line. Enough to feel real.
The point was not perfection. The point was proof. Could the system hold up under live conditions? Could users rely on it without needing five follow-ups?
We caught issues early—some config gaps, some approval quirks—and fixed them before the process expanded. That saved time later.
And once people saw it working in a real setting, their posture changed. Less pushback. More buy-in.
2. Aligning Security and Compliance from Day One
Security shaped this program from the start. It had to.
There were concerns. Where does the data sit? Who has access? What gets logged and reviewed? These came up early and often—and for good reason.
We set role-based access clearly. Tracked approvals. Designed around data staying in-region. Some of those decisions slowed us down in the beginning, but they prevented heavier issues later.
Compliance is not a toggle you add later. In defence, it is part of the architecture. And the earlier it is in place, the more stable the system becomes.
Results – Faster Quotes, Fewer Errors, Better Collaboration
Not everything changed overnight. The systems were ready before the behavior was. But as people started using the tools in live scenarios, the results became clear.
Customer Information Systems are only valuable when they reduce hesitation. That was the real shift here. Teams stopped second-guessing each other. Sales did not need to double-check with engineering. Support no longer chased old spreadsheets.
Instead of working around the system, people started working through it.
Here is what improved:
Quotes went out faster and with fewer steps
Errors in pricing and configuration dropped off
Internal alignment picked up because the data matched across teams
Audit readiness no longer felt like a scramble
These results were not just byproducts. They were the point. Once Customer Information Systems stopped creating friction, delivery speed and confidence naturally followed.
1. 35% Reduction in Quote Turnaround Time
On average, quote turnaround dropped by 35%.
It did not happen in week one. The early cycles still had back-and-forth. But once product rules and pricing logic stabilized, quoting moved faster.
Representatives did not need to chase approvals or correct old templates. The system handled more of the logic, which meant fewer dependencies and fewer delays.
That saved hours across the sales cycle. In some cases, it shaved off days.
2. Accuracy Gains in Complex Product Configurations
Complexity used to create errors. Especially when quoting high-spec or variant-heavy products.
With CPQ validation rules in place, quotes had to follow configuration logic. That structure did not just catch issues. It prevented them.
Engineering flagged fewer mistakes. Sales stopped tweaking based on memory.
Accuracy improved quietly. Not always dramatic, but consistent. The fewer reworks, the more time teams could spend on actual delivery.
3. Real-Time Visibility Across the Customer Lifecycle
For the first time, sales, support, and operations shared the same view of the customer.
It was not just a CRM update. It was alignment—quote data flowing into SAP, support tied back to the original deal, financials linked to the same customer record.
You could track the full journey. Start to finish. That visibility did not just help reporting. It helped decisions. Teams worked with more clarity, and fewer surprises.
Related Articles: SAP Integration and Governance for Defense Projects
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Lessons for Future Projects – Build Around the Way Teams Work
One of the clearest lessons from this project was that success had less to do with tools and more to do with how teams actually work.
Customer Information Systems can be technically sound and still fail in practice. Usually because they ask users to change more than necessary, or make assumptions about how work flows on the ground.
In this case, we spent almost as much time aligning the process as we did configuring the platforms. And that turned out to be the right call.
Here’s what stood out:
Teams needed time to adjust, even when the system made their job easier
Integration logic mattered more than feature lists
People trusted what they helped shape—not what was handed to them
Customer Information Systems only become reliable when users stop bypassing them. That happens when systems reflect the actual rhythm of the business—not an ideal one.
1. Alignment, Not Just Technology, Drives Success
Getting the right tools in place is only half the work.
The real shift happens when sales, operations, and support stop working in parallel and start working together—because they trust the system in front of them.
That level of alignment takes effort. It is slower in the beginning. But without it, most deployments stay surface-level.
2. Integration Details Matter More Than Features
Features rarely break a system. Broken handoffs do.
We saw early on that even small integration gaps—like inconsistent material codes or mismatched field mappings—led to confusion.
Users noticed. And they adapted, sometimes by avoiding the system altogether.
Precision in data flow matters more than what the brochure promises. If integration fails, adoption follows it.
3. Support and Training Sustain Adoption Over Time
Training was not a one-time event. It unfolded over months.
Some users picked it up quickly. Others needed repeat sessions, short videos, or just someone to ask.
We kept support available in the background—not a help desk, just a person to reach out to when something felt off. That one decision probably did more for adoption than anything else.
Systems land better when they come with someone who stays close.
Can This Customer Information System Model Be Reused?
The short answer is yes. This model was not designed as a one-off. It was structured deliberately—with reuse in mind.
Customer Information Systems tend to break when each business unit creates its own version. Different fields, different workflows, and eventually, disconnected data. We avoided that by anchoring everything to standard platforms and scalable patterns.
What made this setup reusable had less to do with the tools and more with the structure underneath:
Clear field definitions across CRM, CPQ, and SAP
A consistent quote-to-order flow
Data mappings that supported multiple product types and approval layers
It was modular by design. The core could stay the same. What changed was the context—new products, new teams, maybe even a new region. But the foundation held.
For other organizations with similar needs, this Customer Information System model offers something practical:
not just stability, but repeatability—without rebuilding from scratch.
1. Scalable for Additional Units or Regions
This design does not lock you into one business unit.
Whether it is a second product line or a region with different compliance rules, the core system still applies. You extend it—you do not duplicate it.
That means less risk, fewer setup decisions, and lower integration overhead.
Each rollout brings its own details, yes. But the heavy lifting around structure has already been done. And that is where most projects lose time.
2. Built on Standard Platforms, Ready for Extension
The system stack was built on enterprise platforms—Microsoft Dynamics, Experlogix, and SAP. That mattered.
Because each layer was already designed to scale, we could focus on business logic, not platform limitations.
CRM could handle more records and new roles
CPQ could manage more complex configurations
SAP SD accepted new inputs without core redesign
This model is not just extensible. It is stable enough to grow without constant rework. And in most environments, that is rare.
Interested in Fixing Your Customer Information Systems?
If your Customer Information Systems feel like they are working against you instead of supporting you, it is probably time to take a closer look.
You do not need to commit to a full project right away. Sometimes the value starts with a short conversation—looking at how your systems are behaving today, and where that friction is showing up.
I work with clients mid-flight. During rebuilds. And occasionally just as a sounding board when internal teams need a second view.
We can start light:
Look at what tools you have
Where the process breaks down
Whether the current model can scale
Customer Information Systems do not fail all at once. But they usually show signs. If that sounds familiar, let’s map it out and see where things could be adjusted.
Let’s Talk – See Where We Can Start
This is not a pitch. It is a working session. One where we walk through what is in place, what feels off, and what could work better.
Whether you need CRM consultation, integration help, or system cleanup support, we can figure out the starting point together. No prep needed.
You show me what you are seeing. I will tell you what I would look at first.
15-Min Call to Review Your Setup
If you want to start with something simple, book a short call.
Fifteen minutes. One system. One flow. We can walk through what you have and I will give you a quick assessment on where the biggest constraints probably sit.
No pressure to move forward. Sometimes clarity is all that is needed.
If you have any questions, or want to discuss a situation you have in your SAP or CRM Implementation, please don't hesitate to reach out!
Questions You Might Have...
1. Why was Microsoft Dynamics CRM selected over other platforms?
Microsoft Dynamics CRM was chosen primarily for its ability to manage the full customer lifecycle—from lead generation to opportunity tracking, through to post-sales engagement. The client needed a system that could support structured sales processes, while also adapting to the long, complex deal cycles typical in the defense sector.
Dynamics provided robust functionality around opportunity management, contact tracking, and workflow automation. Its compatibility with existing Microsoft tools (like Outlook and Teams) also helped with user adoption. Customization flexibility, security controls, and future scalability were additional deciding factors.
2. What role did Experlogix CPQ play in the solution?
Experlogix CPQ addressed the core challenge of manual, error-prone quoting. The tool enabled sales teams to configure complex defense products with built-in business rules and validation logic.
This reduced the dependency on engineering for basic quote creation and ensured pricing remained consistent across configurations. It supported military-specific logic—such as contract terms, tiered pricing, and configuration restrictions—within a structured, auditable workflow.
The result was faster quote generation, improved accuracy, and less back-and-forth between departments.
3. How was SAP SD integrated with CRM and CPQ?
SAP SD was integrated using SAP Cloud Platform Integration (SAP CPI). SAP CPI served as the middleware, managing real-time data exchange between systems. Once a quote was finalized in Experlogix CPQ, the information was passed through SAP CPI into SAP SD as an order.
This eliminated the need for manual re-entry and reduced the likelihood of data discrepancies—particularly in configurations, pricing, and delivery terms. SAP CPI also enabled customer and order data synchronization between Dynamics and SAP, ensuring consistency across both platforms.
4. What were the biggest challenges during implementation?
Several challenges emerged, most notably around data fragmentation and integration complexity. Customer data was inconsistent across departments, requiring significant cleanup before CRM could be adopted as the source of truth.
Integration between three major systems—Dynamics, Experlogix, and SAP—introduced mapping challenges, especially with product configurations and pricing structures.
Additionally, aligning stakeholders across departments (sales, engineering, IT, and finance) required time and effort, particularly when redefining ownership over parts of the process.
5. How was data integrity ensured across systems?
Ensuring data integrity was a key part of the project. First, customer records were consolidated and cleaned before being migrated into Dynamics CRM.
Standard data models were created to maintain consistency. Integration logic within SAP CPI included validation rules to prevent mismatched data during sync.
Experlogix enforced configuration accuracy through built-in rules. Together, these elements helped establish a more reliable, trusted dataset that could flow cleanly from CRM to CPQ to SAP SD without loss or distortion.
6. Was security and compliance part of the core design?
Yes, it was built into the solution from day one. The client operates in a highly sensitive industry, so every component—CRM, CPQ, and SAP—had to comply with both internal security policies and national regulations.
Role-based access controls were enforced across all systems, limiting visibility and actions based on user roles. Full audit trails were enabled for quoting, approvals, and data changes. Data residency was also a concern; all data remained within the designated region (UAE) in compliance with defense-sector regulations.
7. How long did the rollout take?
The rollout followed a phased approach over roughly 6 to 8 months. It began with a pilot—limited users, predefined scenarios—focused on CRM and CPQ adoption. After gathering feedback and refining workflows, the solution was extended across departments.
Integration with SAP SD via SAP CPI was implemented midway, once the upstream systems had stabilized. This helped prevent early-stage issues from cascading downstream. Training, support, and system tuning continued throughout the rollout.
8. How was user adoption managed?
User adoption was approached practically. Teams received tailored training sessions, including live demos, Q&A workshops, and short how-to videos. Documentation was created specifically for the internal use cases.
Feedback was actively collected during the pilot phase, and small enhancements were made before scaling. Importantly, the systems were designed with usability in mind—CRM integrated with Outlook, CPQ used guided workflows, and approval steps were embedded into natural working paths.
Adoption wasn’t perfect at first, but steady support and visible benefits helped overcome early hesitation.
9. Can the same solution be scaled to other business units?
Yes, the architecture was designed to be reusable. With SAP CPI serving as the integration layer, additional business units or regional offices can connect to the same CRM–CPQ–SAP framework with minimal modification.
Product configurations and pricing logic in Experlogix can be extended or adjusted without rebuilding the entire setup.
CRM entities are already structured to support multi-division views. Future expansions—whether in terms of geography or additional product lines—can follow the same integration and data flow model.
10. What measurable improvements were seen?
Quote turnaround time decreased by approximately 35%, mainly due to reduced manual steps and fewer revision cycles.
Quote accuracy improved significantly—errors in pricing and configurations dropped noticeably.
A 360-degree view of the customer was established through Dynamics CRM, giving teams better insight into customer history and engagement.
Order processing errors declined due to the elimination of re-keying and manual data handoffs.
And collaboration improved: sales, engineering, and finance began working from the same data and within a shared process—something that hadn’t existed before.
Let me know if you’d like these repackaged into a formal FAQ document or formatted for web or slide content.
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