Operational Fundamentals: Key to Digital Transformation Success

Why Operational Fundamentals Are the Essential First Step in a Successful Digital Evolution

Author: DBS Cyber [Based on the presentation by Elizabeth Stephens]

Executive Summary

In the modern industrial landscape, “digital transformation” and “AI” have become ubiquitous buzzwords. Companies are promised “smart” operations that can predict failures and maximize returns. However, many of these initiatives fail to deliver value because they skip the single most critical phase: Discovery. Attempting to layer advanced technology onto poorly understood, inefficient, or unmeasured legacy processes is a recipe for failure. A successful, profitable, and sustainable digital evolution does not begin with software; it begins with a rigorous, data-driven understanding of operational fundamentals. This paper outlines the value of using a “tried and true” operations methodology —Define, Measure, Analyze, Improve, and Control (DMAIC) —as the essential bedrock for building a truly “smart” enterprise.

1. The High Cost of “React Mode”

Many established industrial operations, from mining to manufacturing, function in a constant “react mode”. Their systems are analogous to “a car in the olden days” —they provide no warning when a component is failing or when “the oil is leaking”.

This lack of “visibility and observability” creates a cascade of costly problems:

• Expensive Dependency: Problems are only identified after they occur, forcing operators to hire expensive external specialists—like metallurgists in a wash plant—to diagnose issues. These specialists are costly to employ full-time and, when hired as consultants, are incentivized to “spend a lot of days there and hours there” to increase their own billing.
• Cascading Inefficiencies: Without visibility, resources like water, power, and chemicals are used ineffectively. Unscheduled downtime becomes a regular occurrence , and preventative maintenance is impossible.
• Significant Lost Revenue: The primary consequence is lost yield and revenue. A seemingly small, untracked inefficiency—such as a final product yield just 5% below spec—can result in millions of rand in lost revenue every month.
• Untracked Human Factors: This blindness extends to human capital. Without data, it’s impossible to identify losses caused by employees “making an extra buck” or operators driving heavy machinery “too rough,” leading to premature equipment failure.

The core issue is simple: you cannot manage, improve, or automate what you cannot measure.

2. The Solution: A Framework for Fundamentals (DMAIC)

A true digital transformation begins with a data-driven solution built on “old school operations methodology”. The Lean Six Sigma framework of DMAIC (Define, Measure, Analyze, Improve, Control) provides the structure needed to build this foundation.

This process is not theoretical; it involves getting on-site with your experts and walking through the process step-by-step.

1. DEFINE: First, we work with your team to identify and define a clear, focused problem. This isn’t a vague goal; it’s a specific target, such as, “Identify the root cause of the loss in yield and implement a solution to recover 2% of that loss within six months”.
2. MEASURE: Next, we document your actual operation from start to finish. This documentation establishes the baseline against which all improvements will be judged. We identify what data you currently have and what we need to start collecting, such as tons in vs. tons out , feed grades, densities , cyclone pressures, and water flow rates.
3. ANALYZE: With a baseline and hard data, we “audit” your process. This analysis identifies the root cause of the problem. Often, this step reveals that long-standing procedures that teams thought were adding value are, in fact, creating waste. We can pinpoint why a problem is happening (e.g., “We only see a yield drop when feed density is at X level”).
4. IMPROVE: Once the root cause is verified by data, we brainstorm, test, and implement solutions. This is where technology begins to play a role, such as creating automated control loops to stabilize processes that were previously unmanaged.
5. CONTROL: This final phase is “where you make your money”. Control is achieved by embedding the improvements into the operation. This includes new Standard Operating Procedures (SOPs) , implementing technology like real-time dashboards and alerts , and retraining operators. This retraining is vital, as it helps staff understand “how much what they do impacts your bottom line”.

3. The Result: From Solid Fundamentals to “Smart Operations”

This “Discovery” phase is the mandatory starting point for any future implementation, whether it’s new policies, digital systems, or technical hardware and software.

Only after completing this foundational work can an organization move from “react mode” to having “observability across the operation so you can make smart decisions”. This is the true definition of a “smart mind”.

The data collected and validated during the DMAIC process becomes the fuel for high-value digital assets, including:

• Predictive Maintenance Pilots for critical equipment, like trucks.
• Proprietary AI and predictive analytics engines.
• Secure Data Platforms built on a proprietary framework of data sovereignty, ensuring your competitive information is protected.

Conclusion: Your Expertise, Digitized

The ultimate goal of a digital evolution is not just to save money on maintenance; it is to take your company’s unique operational expertise and intellectual property (IP) and turn it into a product.

By starting with the fundamentals, you partner with process and AI experts to build a system that first proves its value by solving your biggest problems. That system, built on your data and expertise, then becomes a new, scalable asset—a predictive engine that can be sold as a new standard for your entire industry.

This evolution is not possible without first laying the bedrock. It all starts with discovery.