Data & AI Strategy | Nick Lachniet
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Future-Proofing the Enterprise with Data & AI

A modern transformation strategy must be grounded in a deep understanding of how data and AI can augment human talent, unlock new efficiencies, and create an enduring competitive advantage. I don't just follow trends; I build the playbooks that turn emerging technology into a core enterprise capability.

My Playbook for AI Adoption

Successfully adopting any new technology requires a deliberate strategy to guide people through the change. My approach is a three-stage playbook for moving an organization from scattered experimentation to widespread, impactful adoption.

Inspired by concepts from "AI Enabled Leadership" and "The Daily AI Podcast".

Diffusion of Innovation overlaid on AI Adoption
1

Pilot & Prove

Begin with a focused pilot within the Transformation team to create "lightbulb moments," prove value quickly, and build a data-driven case for broader adoption.

2

Scale & Socialize

Broadcast the pilot's successes and provide hands-on, high-value services to other teams, organically positioning the Transformation team as a strategic partner for innovation.

3

Institutionalize

Use the results and momentum to build a formal AI Center of Excellence, standardizing best practices and creating an enduring enterprise capability with clear ROI.

My Approach in Action: From Tactical Problem to Transformative Business Case

Often, the most significant transformation opportunities are hidden within what appears to be a small, tactical problem. My approach is to look beyond the immediate issue and reframe it as a chance to build a lasting enterprise capability. The following business case for a logistics client illustrates this thinking.

THE INITIAL ASK: "Fix Our Bad Data"

The client's immediate problem was that manual data entry errors were hindering their new AI initiatives. The initial request was for a simple training program—a temporary fix with limited scope and ROI.

THE STRATEGIC REFRAME: "Build an AI-Powered Data Engine"

Instead of a bandage, I proposed we use AI to solve the AI-readiness problem. This reframed the project as a foundational investment in a permanent, self-sustaining enterprise capability.

Building the Business Case: Unlocking Value Across the Enterprise

Operational Efficiency

By automating data validation, we could dramatically reduce operational costs and free up hundreds of hours for the operations team to focus on high-value work.

Workforce Empowerment

This wasn't just a technical fix; it was a human-centric one. By eliminating tedious, frustrating tasks, we could directly improve employee satisfaction and morale, a key priority for their HR leadership.

Unlocking Future Funding

Most importantly, I positioned this initial project as a pilot that would create a reliable, high-quality data foundation. This "win" could then be used to unlock funding from other departments for more ambitious AI, machine learning, and advanced analytics initiatives, turning a small investment into a strategic growth engine.

Data & AI Strategy in Action

Abstract data visualization

RRD Motif (for Apple): A Data-Driven Product Launch

The Challenge

When Apple decided to sunset its native photo book application, I led the program to build its replacement, Motif. The core challenge was to create a "magical" user experience that could intelligently auto-flow a user's photos into a beautiful, print-ready book. This required a sophisticated data strategy to analyze photo metadata—like timestamps, subjects, and even whether people were smiling—to make smart design choices on the user's behalf. All of this had to be delivered on a hard deadline for a feature at Apple's WWDC.

My Key Actions:

Led the 0-to-1 product launch, from initial concept to international rollout.
Defined the data strategy for leveraging photo metadata to power the "auto-flow" feature.
Bridged the gap between strategy, design, engineering, and on-site print operations teams.
The Outcome
WWDC
4.6 ★
100k+
Featured at Apple's WWDC
App Store Rating
Downloads
Lasting Impact

The platform I launched became a primary revenue driver, responsible for nearly 40% of the client's annual segment sales. The success of the data-driven "auto-flow" feature set a new standard for intelligent, personalized product creation in the industry.

A person using a phone with a loyalty app

Wendy's: Building a Data-Driven Engagement Engine

The Challenge

Wendy's needed to launch a net-new loyalty program on an aggressive 90-day timeline to coincide with their national breakfast launch. The goal was to build more than a simple "earn-and-burn" program; it needed to be an engagement engine that could capture and leverage customer data to drive repeat visits and increase lifetime value.

My Key Actions:

Led the cross-functional teams to design, develop, and launch in under 90 days.
Owned the end-to-end product strategy, including the data model for capturing customer preferences.
Oversaw major integrations with their POS and marketing platforms to enable data-driven personalization.
THE OUTCOME
0-to-1
New
Successful 0-to-1 Launch
Channel for Personalization
LASTING IMPACT

The loyalty program became a core part of Wendy's digital ecosystem, providing a rich source of first-party data that continues to fuel their personalization and marketing strategies today.