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The Value Engineering Approach to Data & AI

By Raivis Mackevičs, Head of Operations, The Infotrust

Why “Value” Shouldn’t Be an Afterthought in Your Data & AI Investments

Every technology project begins with excitement.

A new analytics platform. AI. Better dashboards. Faster reporting.

Yet, somewhere along the journey, an uncomfortable question inevitably appears:

“What value did this investment actually deliver?”

Unfortunately, by the time that question is asked, it is often too late.

The platform has already been selected. The implementation is underway. Finance is asking for ROI. Business users are still trying to understand how this changes the way they work.

During our recent podcast with Rudi Pasternak, Strategy & Value Advisor at Qlik, we discussed a different way of approaching technology investments—one that starts not with software, but with business value.

One statement from the discussion particularly resonated with me:

You cannot buy competitive advantage with a tool. You create it by the way you use that tool.

That idea sits at the heart of Business Strategy & Value Engineering.

Start with the business—not the technology

Many organisations already have data.

They already have dashboards.

Many even have AI initiatives.

Yet they still struggle to answer simple business questions:

  • Which business problems matter most?
  • Where are we losing money?
  • Which opportunities are worth pursuing?
  • Which investment will create the biggest business impact?

The framework reverses the traditional implementation process.

Instead of beginning with software selection, it begins with understanding how the business creates value.

It asks questions such as:

  • What external forces are putting pressure on the business?
  • Which KPIs are affected?
  • Which processes create the biggest friction?
  • Where are the largest opportunities for improvement?

Only after those answers become clear does technology enter the conversation.

As Rudi explained during the podcast, the framework gives organisations visibility into the impact of change before a single tool is deployed.

Value isn’t only about ROI

One of the biggest takeaways for me was that organisations often reduce value to a single number.

ROI matters.

But it is only one dimension.

The framework evaluates business impact across three perspectives:

  • Top Line – increasing revenue and improving commercial performance.
  • Bottom Line – reducing cost and eliminating inefficiencies.
  • Operational Scalability – enabling existing teams to accomplish significantly more without proportional growth in headcount.

This broader perspective fundamentally changes investment discussions.

Instead of asking “How much does the platform cost?”, organisations begin asking:

“How much business value can we unlock?”

Technology becomes the enabler—not the objective

The framework perfectly illustrates this idea.

Strategy.

Business goals.

Pain points.

Data.

Value drivers.

Only then:

Solution scope.

Investment.

Business outcomes.

ROI.

Success.

That order matters.

Far too many projects start from the bottom of the list and try to work backwards.

Business Strategy & Value Engineering does the opposite.

It creates alignment between executives, business teams and IT before implementation begins.

The result is a shared understanding of why the investment exists—not simply what is being implemented.

Culture matters as much as technology

The podcast also highlighted something we often underestimate.

Successful transformation isn’t just about platforms or architecture.

It is about mindset.

Rudi described three common organisational approaches:

  • Transactional — focused on solving today’s problems.
  • Strategic — improving processes and efficiency.
  • Value Driven — aligning the entire organisation around measurable business outcomes.

The organisations that consistently outperform are those that move beyond departmental optimisation and start making decisions together.

Technology enables that collaboration.

Leadership creates it.

What implementation really looks like

The customer example discussed during the podcast made this very tangible.

The organisation didn’t begin by building dashboards.

It first identified more than twenty cross-functional pain points, prioritised them according to strategic importance, quantified their business impact, and then built a phased roadmap around the highest-value opportunities. Data quality, integration and process redesign came before advanced analytics.

Only after that foundation was established did the analytics applications begin delivering measurable business outcomes.

The result wasn’t just a successful implementation.

Business adoption increased by approximately 600%, because employees finally had tools that helped them make better decisions—not simply more reports.

The real question every project should answer

Economic uncertainty, supply chain disruption, inflation, AI, new regulations—change is no longer the exception.

It is the operating environment.

The organisations that succeed won’t necessarily be those that buy the newest technology.

They will be those that understand exactly where value is created, how to measure it, and how technology can accelerate it.

That’s what Business Strategy & Value Engineering is designed to achieve.

It shifts the conversation from software features to business outcomes—and gives both business and IT leaders a shared framework for making better investment decisions.

Because value shouldn’t be something you calculate after implementation.

It should be something you design from the very first conversation.

Watch the full interview:

Contact our High Value Analytics team>


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