Why Your Industrial Data Strategy Needs a Master Plan (Not Just More Sensors)

We’ve all heard it: “Data is the new oil.” And it’s true: data has the potential to transform industrial operations. But for anyone who’s tried to unlock that potential, you’ll know it’s far from easy. To paraphrase Clive Humby “if data is the new oil, then a strategy is the refinery”.

Accessing the right data is tough. Security concerns are ever-present and justifying the investment can be an uphill battle. In response, many operational teams default to tactical fixes—buying new sensors here and there, rolling out point solutions that don't require integration with the broader business.

It feels fast. It looks innovative. But it’s not strategic and that’s the problem. If you really want to turn industrial data into a strategic asset, you need more than a handful of disconnected initiatives. You need a master plan—just like you would for any other long-term capital investment.

Where to Start? Borrow from ISO 55000

Here’s a powerful way to frame your approach: treat your data like any other critical asset. ISO 55000, the international standard for asset management, offers a proven methodology for doing just that. At the heart of it is the Strategic Asset Management Plan (SAMP)—a guiding document that links asset management activities directly to the organization’s strategic goals. We can adapt that thinking to industrial data.

Key Elements of a Strategic Industrial Data Plan: How to build a data strategy that actually delivers value:

🔍 1. Understand the Role of the Master Plan

The master plan should clearly articulate how industrial data will drive your organization’s strategic goals. Start by reading your company’s annual report and risk register—then show how data can address those priorities. You’d be surprised how few investment proposals from factory teams actually make this connection.

🌍 2. Define Your Organizational Context

Know the internal and external factors that shape your strategy. Internally, get the Information Security and IT teams on board early. Externally, frameworks like Porter’s Five Forces still offer a useful lens for understanding competitive dynamics and how industrial data can defend against them.

🎯 3. Set Strategic Industrial Data Objectives

Your data goals should tie directly to core business outcomes: uptime, productivity, carbon reduction, quality, and waste minimization. If they don’t move the needle on those, rethink your plan!

📏 4. Define the Scope (and Keep It Focused)

Avoid analysis paralysis. Don’t start by trying to integrate every system under the sun. Instead, focus on one area where you can generate actionable insights quickly. Think evolution, not revolution. I spoke with one food group recently who wanted to jump in one move from no integrated industrial data strategy to full AI control of their production facilities – there’s a lot of intermediate steps on that journey!

🛡️ 5. Align with IT and Security Policies

Build your industrial data policy in lockstep with existing IT and InfoSec frameworks—especially ISO 27000. This ensures you're speaking the same language when you ask for support (and funding).

🛠️ 6. Define the Delivery Approach

This is where things get real. Lay out:

• Your governance structure
• How you’ll choose your data platform
• Criteria for prioritizing deployments
• Your resourcing model
• How you’ll ensure you deliver ROI, not just deploying science experiments

📊 7. Link to Performance Metrics

What KPIs will your strategy impact? Be specific. Tie it back to business performance to gain traction with execs.

⚠️ 8. Identify Risks and Opportunities

Include risks at both the factory and corporate levels. And don’t forget to reference the corporate risk register—you’ll need it to align your strategy with board-level priorities.

📋 9. Set Governance and Review Processes

Who owns the plan? How often will it be reviewed? Build in mechanisms for continuous improvement.

📣 10. Communicate, Evangelize, Iterate

A strategy that sits on a shelf is no strategy at all. Keep it visible, keep it relevant, and make it easy for everyone involved in data to align their work with the master plan.

The Payoff

Building a strategic industrial data plan is hard work. It requires cross-functional alignment, stakeholder engagement, and long-term thinking. But once it’s in place, it becomes far easier to win executive support, secure investment, and most importantly—deliver value.

Want help building your data strategy?

At Two6 Services, we specialize in developing industrial data strategies and Strategic Asset Management Plans tailored to real-world operational challenges. Get in touch if you'd like to explore how we can help.