Suits Blog: Stop Counting, Start Measuring: Finding the Metrics That Prove Digital Value.

By Nicolas Soum, Director of Value Consulting, Neptune Software 

The Metric Mirage 

Here’s something I see all the time: every digital transformation program starts with beautiful dashboards. But how many actually end with measurable business results? 

Not nearly enough. 

Companies track everything. Project completion rates, user adoption, apps deployed, cloud migration percentages. The slides look impressive, I must say. But then someone in the boardroom asks the obvious question: “So what’s actually changed for our business?” 

Silence. 

We’ve gotten really good at counting things, but not so good at measuring what actually matters. 

But, as we say in France, “Il ne faut pas mettre la charrue avant les bœufs.” 
One should not put the cart (dashboards) before the horse (defining impact). 

The numbers back this up. Gartner found that only 48% of digital initiatives meet or exceed their business targets (Gartner, 2024). Meanwhile, McKinsey reports that 89% of companies have digital or AI transformations underway, but they’ve only captured 31% of expected revenue gains and 25% of cost savings (McKinsey: How Top-Performing Companies Approach Digital Transformation). 

The problem? Enterprises today are drowning in data but starving for meaning. 

Measuring Progress Instead of Value 

Too often, digital transformation success is still defined by activity rather than outcome. We celebrate go-lives instead of gains, count apps built instead of bottlenecks removed, and measure adoption without ever questioning the impact. 

Most dashboards tell you what happened, but they rarely reveal what improved. 

This happens because of how we define metrics. IT reports uptime and sprint velocity. Business units track risk, revenue and costs. These worlds rarely connect, which makes it nearly impossible to show how technology creates value. 

McKinsey calls this the “execution gap,” the inability to convert digital investment into financial or operational performance (McKinsey: In Digital and AI Transformations, Start with the Problem). 

When your definition of success doesn’t match business reality, transformation becomes a reporting exercise instead of a value engine. 

From Counting to Measuring 

Transformation isn’t about doing more things digitally. It’s about making the business measurably better. 

That means shifting from tracking activities to measuring outcomes. 

At Neptune’s Value Consulting practice, we use a simple framework to help customers rethink what success looks like: 

Level	Focus	Example Metrics	What It Shows
Activity Metrics	Implementation progress	Number of apps built, percentage migrated to S/4HANA	Effort
Adoption Metrics	User engagement	Daily active users, average task time	Usability
Process Metrics	Operational outcomes	Cycle time, rework rate, automation coverage	Efficiency
Value Metrics	Business outcomes	Cost per transaction, working capital, productivity gain, customer satisfaction	Impact

It’s straightforward, but revealing. Most organizations stop at activity or adoption. Real progress happens in those last two layers, process and value metrics, where you can actually see transformation making the business more resilient, agile, or profitable. 

The Missing Link: Data, Context, and Collaboration 

Meaningful measurement needs integration. Not just between systems, but between teams. 

Finance, IT, operations, HR… everyone tracks performance differently. Definitions don’t align. Systems don’t talk. Ownership is fuzzy. Your SAP system has all the process data, but the business context and financial impact live somewhere else entirely. 

The result? Beautiful dashboards that don’t lead to better decisions. 

McKinsey puts it plainly: “Digital transformations succeed only when companies rewire their operating models, data, and talent around clear business outcomes” (McKinsey: Rewired and Running Ahead – Digital and AI Leaders Are Leaving the Rest Behind). 

To close this gap, you need to start by agreeing on the right questions. What are we actually trying to improve? What decisions should our data inform? And who’s accountable for turning digital progress into business performance?

Building a Value Measurement Framework 

Here’s a practical approach I recommend to transformation leaders: 

1. Define What “Value” Means 

Get everyone on the same page about what success looks like. For some companies, that’s faster order cycles or lower maintenance costs. For others, it’s better employee productivity or hitting sustainability targets. 

2. Align Dashboards Across Teams 

Break down the wall between process data and outcome data. SAP tells you where time and cost accumulate. Finance and operations provide the business context that proves impact. Together, they tell the complete story. 
 
3. Measure Value as You Build 
The moment a bottleneck is removed or a workflow is simplified in a prototype, value is already happening. You do not need to wait for go-live to know whether something is working. Early insight into productivity gains, reduced clicks, or faster approvals helps you prioritize what delivers the biggest impact once launched. 

This shifts the focus from producing deliverables to producing outcomes every step of the way. 

4. Measure Flow, Not Go-Lives 
Most transformation dashboards celebrate milestone completions. Phase one. Phase two. Go-live. But go-live is not the climax of value creation. It is simply the handover from build to scale. The real story is how continuously your improvements flow into operations. 

When you measure process improvement instead of project progress, you can see where value is flowing and where it is blocked. 

5. Automate Insights 

Put analytics where people already work. When insights are embedded in daily workflows, decisions happen faster and you get a stronger feedback loop between execution and strategy. 

6. Review, Refine, Repeat 

The right metrics change as your business changes. Transformation isn’t static, and your measurement framework shouldn’t be either. 

The 100 KPIs Problem 

A global energy and manufacturing company we worked with proudly tracked more than 120 KPIs across warehouse operations. Every department measured something different. Very few measured the same thing. And leadership struggled to see how all that reporting translated into performance. 

They were tracking activity, not improvement. 

Together, we applied a simple test to every KPI: 

Does this metric help us understand whether business performance is getting better? 

When we connected operational data from SAP with measurable business outcomes, five capability areas stood out in terms of improvement potential that leadership really cared about: inventory accuracy, picking efficiency, dock to stock cycle time, return resolution time, and labor utilization. 

Here is what changed once the focus shifted to value: 

Capability Area	Where They Were Before	What Improved With Neptune DXP	Measurable Value
Picking, Goods Issue and Put-away	Paper-based tasks, data errors, unreliable mobile tools	Scanning-based workflows on mobile devices	+35% process speed, -50% admin time, 95% reduction in picking errors
Internal Movements & Replenishment	Manual data entry, untracked bin transfers	Real-time stock updates and proactive triggers	Accurate real-time inventory; reduced  stockouts; improved workforce utilization
Physical Inventory	Long counts, low accuracy, high labor effort	Mobile-enabled PI with real-time validation	Reduced effort by 50%; increased inventory accuracy by ~35%
Returns Processing	Paper tags, lost records, missing traceability	Structured barcode-driven workflows	-40% return processing time; reduced  shrinkage and improved compliance
Outbound Loading	Manual tracking and double handling	App-based mass loading with traceability	Fewer mis-shipments and faster dock-to-stock transitions

When we helped the company align on just five core capability areas and value-based KPIs, the results spoke for themselves with $11M-$14M in value, across both top and bottom lines:

• Direct OpEx savings through better labor utilization, redundant task removal and reduction of manual errors 

• Working capital reduction though better inventory accuracy and lower Days Inventory Outstanding 

• Revenue uplift through better OTIF and fewer mis-shipments 

By focusing on value metrics instead of vanity metrics, the business not only simplified reporting — it uncovered millions in measurable operational gains. 

Closing Thought 

As we say in France, “Il faut choisir dans la vie…” 
In life, one must choose. 

The same is true in digital transformation. 
Choosing the right metrics makes all the difference. 

When you measure what truly matters, progress becomes visible faster. People feel the improvement in their everyday work. And decisions become clearer because the numbers finally tell the right story. 

If you are investing in transformation but struggling to prove what is moving the needle, let us talk. There is a practical, measurable path to real value, and I would be happy to help you find it.