Lassonde

Igor Mitrovic

Business Technology Integrator

Igor Mitrovic is a data and technology leader focused on advancing transformation through stronger collaboration, trusted data and practical AI adoption. His approach emphasizes aligning people, processes and technology to build scalable data foundations and deliver measurable business value.

Making Transformation a Team Sport

Traditional software development often treated technology delivery as a transactional process between business teams and their IT service providers. Business teams expressed their needs to IT, which gathered requirements, analyzed them, developed solutions, tested them and managed implementation.

By the time a solution reached the business, however, the original need may have changed considerably, requiring another round of modifications. Several iterations could follow, consuming time, resources and money without necessarily producing a solution that the business accepted or used.

Agile development began bridging that gap by breaking projects into smaller sprints and bringing IT and business teams closer through daily collaboration. The approach reinforced an idea that has continued to shape my thinking. People and processes need to come first, with technology following.

In our field, every decade brings another leap in capability, speed or scale. Fundamentally, if the people and process components are not figured out, technology simply brings old problems to the surface faster.

Transformation is a team sport. It is not transactional, and business and IT need to work as one toward a single objective. Organizational change management needs to happen at the same time.

Everyone wants change, but those willing to change are a much rarer breed. Transformation goals need repeated communication, while successes need recognition and lessons learned need to shape the next cycle.

Transformation is not a side project that can be completed in one's spare time. Organizations either commit to it fully or accept the risk that competitors may begin doing things better and faster.

For me, transformation comes down to humility, adaptation to change and building trust through consistent delivery and meaningful partnerships. Humility means asking questions that may seem obvious to someone else and remaining willing to speak up.

Adaptation is paramount in a connected world where professionals need to remain comfortable dealing with issues outside their comfort zone and sphere of influence. Trust comes from delivering on commitments and building partnerships where old divisions between IT and business become obsolete.

Making Data Governance Part of the Business

Building trust in data starts with clear ownership and clearly defined business rules and measures that keep information trustworthy. Organizations need tools that make those rules and measures visible and actionable.

  Transformation is a team sport. It is not transactional, and business and IT need to work as one toward a single objective.  

Data governance needs to become part of existing strategic and operational meetings, placing it within discussions about business strategy and organizational performance. When leaders already examine company performance, traceable and trustworthy numbers make governance more than just another compliance checkbox.

The goal is to make governance a mechanism for delivering reliable, timely and accurate insights and KPIs. Success becomes evident when the business stops asking where its numbers came from and starts bringing problems that require help solving.

Building a System-Agnostic Data Foundation

Modernizing data across complex and fragmented environments requires a shift in how organizations approach integration. Rather than focusing on the number of systems requiring integration, organizations should build a system-agnostic layer containing key information used by the business.

Business teams generally do not concern themselves with which system or physical database table client information comes from. Data teams should take the same approach while maintaining cleanliness, accuracy and harmonization through a centralized structure.

Once the layer is established, the next ERP implementation or merger and acquisition integration becomes much more straightforward. The organization already has a repeatable playbook for bringing information into the common layer.

Connecting AI Investment to Business Value

A two-speed approach can help organizations connect AI investment to measurable business outcomes. Initial AI initiatives should focus on back-office automation and productivity gains that allow teams to learn through practical applications.

In parallel, organizations need to ensure their data is clean enough to support advanced data science, machine learning and AI use cases. Both efforts can progress simultaneously without requiring the organization to complete one before beginning the other.

AI adoption depends on more than introducing new technology into existing operations. It requires strong underlying data and an organizational ability to translate technology into practical business value.