Data is nothing without insights

Asset-intensive organisations need to move from data-rich to insight-driven

Whether it’s coming from smart factories or digitally-connected supply chains, data is more accessible than ever before for asset-intensive organisations. A Modern Industrial Strategy is more than just a data revolution. Gathering data is not the problem, argues Kevin Bull, Product Strategy Director at Columbus. It’s about creating a data-driven strategy that turns data from numbers into real-time actionable insights. Here are the five steps asset-intensive organisations can take to take real advantage of the data revolution.

In a landscape where supply chain disruptions are increasing in frequency, skills shortages are worsening, regulations are tightening, and margins for error are becoming smaller, nearly three-quarters of UK organisations are turning to data to drive performance, innovation and real-time decision-making. But many organisations in asset-intensive industries persist with using legacy systems, creating data silos and poor-quality data. The need to turn data into a strategic advantage has never been so important.

To succeed in the digital age requires strong fundamentals: clean data, integrated Information and Operational (IT/OT) systems, solid governance, and tight security. With a firm foundation, asset-intensive organisations can unlock a clear competitive advantage in just five steps. Not having these fundamentals in place could leave organisations lagging behind competitors in the next wave of digital transformation.

1 — Turning data insights into strategic outcomes

Data is only valuable when it drives outcomes. Yet a challenge for many asset-intensive organisations is linking data insights to strategic business objectives such as cost reduction, sustainability or customer satisfaction.

At the very beginning of any data transformation journey, it’s important to establish what an organisation wants their data to actually achieve, whether this be optimised supply chain efficiency or improved product quality. This way, clear KPIs that align with business goals ensure that data collection is focused and relevant.

It’s important at this stage to look for quick wins that directly support objectives and can help demonstrate the value of data-driven decision-making early on. Don’t forget the right technology can also be an asset here as when combined with data it can support day-to-day work and decision-making. For instance, if a sensor captures a data anomaly, then corrective actions can be automatically established, and the right people and resources can be actioned.

2: Bridge the skills gap from the top down with a data-driven culture

With the UK currently suffering a major digital skill shortage that is costing the economy £63 billion per year, the challenge now is for asset-intensive organisations to cultivate a strong data-driven culture within their workforce. Employees need to trust, understand and feel empowered to work with new systems and processes to leverage the potential of intelligent data insights fully.

Any effective data-driven culture starts at the top with leadership. They need to lead by example, whether that means using the technology, communicating to employees the context behind the importance of accurate data, providing them with the correct training and tools, or involving them in the early stages of adoption and celebrating data-led wins to build employee confidence. Employees that feel seen and heard are more likely to engage with changes if their needs are met.

3 — Remove data silos to drive faster, smarter decision-making

One of the biggest barriers to effective data use is the fragmentation of information across multiple systems such as sensors, machines and ERP systems, as this can cause severe delays and provide incomplete and even misleading insights. So how can asset-intensive organisations tackle this issue head-on?

An IT/OT integration ensures different systems communicate with each other and trigger automatic action. For instance, sensor faults generated on shop floor equipment can automatically trigger actions on enterprise systems, resulting in quicker fixes and optimised processes.

What’s more, the consolidation of data from multiple sources into a central platform creates a single source of truth, which gives decision-makers complete visibility of operations and enables them to identify opportunities and improvements faster. Data consistency across systems is also important at this stage as it results in easier identification and trend analysis.

4 — In the age of cyber threats, build a security-first strategy

With more and more asset-intensive organisations turning to digital technologies to transform their business and operations, the threat of cyberattacks also rises. In fact, supply chain cyberattacks have surged by a staggering 431% in the past few years, and asset-intensive industries are being targeted, with manufacturing being the most cyber-attacked industry for five consecutive years. Without strong data governance and security, data quality diminishes and compliance risks increase with potential catastrophic results for organisations.

Yet it’s important organisations understand that cybersecurity is not an IT problem but a company-wide problem that requires a company-wide effort to fix. And that starts with building a security-first architecture that can embed secure-by-design principles into all operations and make cybersecurity a critical step when connecting new systems and tools. Going one step further, organisations can look to control data access with multi-factor authentication, role-based access and encryption to protect data.

These cybersecurity measures are only effective if employees understand best practice. This is where the human firewall comes in. At this stage, it’s critical organisations arm employees with the knowledge and skills to adapt and excel with more secure workflows.

5 — Unlock the true power of AI

Today’s digital revolution is being spearheaded by AI, but organisations in asset-intensive industries are lagging behind in their adoption! According to recent findings, over half of businesses in information and communication use AI, compared to only 13% in asset-intensive industries.

The benefits of leveraging AI are endless, whether it's to anticipate equipment failures, cut downtime and save costs with predictive maintenance, enhance quality with machine learning detecting defects more accurately than humans, or to manage inventory and logistics more effectively to optimise supply chains. AI is quickly becoming an integral part of organisations staying competitive in the digital era but it’s success hinges on a number of key rules.

All reading from the same data sheet

Before putting data into any AI tools, data must be error-free and standardised with key definitions to ensure the AI systems interpret the readings correctly. From here, organisations must define compliance rules and create a data catalogue to manage data safely and securely.

Once these guardrails have been established, organisations can integrate data from sensors, smart cameras and vibration monitors with edge computing to process data on the shop floor for faster responses, reduced latency and continuous operations. Downtime can become a thing of the past thanks to predictive maintenance tools, which identify potential failures before they impact production, machine lifespans and maintenance costs.

Get ahead of the competition and turn data into actionable insights

In today’s data-rich landscape, simply gathering data is not enough to stay competitive. As organisations in asset-intensive industries face worsening skill shortages, narrowing margins, and increasing cyber threats, true success today and in the future demands a data-driven strategy that turns raw data into real-time actionable insights.