At a glance
- Turn data into decisions with practical strategies that boost business growth for asset-centric organisations
- Streamline operations and improve service by identifying trends and inefficiencies
- Avoid costly missteps by focusing only on relevant, reliable, high-quality data
- Explore a clear data analytics framework tailored for asset-intensive industries
Ever wondered how some asset-centric organisations consistently outperform their competitors? The answer lies in data. This article discusses how to use data analytics to boost productivity exploring how industries such as transport, mining, utilities and defence can all benefit. I share actionable steps to collect, analyse, and utilise data, helping you make smarter decisions, avoiding unexpected downtime, improve customer experiences, and achieve remarkable results.
Why Data Analytics Is Essential For Asset-Centric Organisations
When reliability matters we cannot operate in the dark. So to start us off I want to share five ways data analytics can pin point key trends, optimise business processes, and personalise customer experiences:
- Improved Decision-Making: Data analytics provides the tools to make informed decisions for asset-intensive businesses, based on evidence rather than assumptions.
- Enhanced Customer Service: Analyse customer data to understand preferences, personalise interactions, and improve overall satisfaction.
- Boost Productivity: Identify bottlenecks, optimise workflows, and automate tasks to improve efficiency, reduce operating costs and reduce the risk of unexpected downtime.
- Uncovering Opportunities: Identify new market segments, develop innovative products, and expand into new markets.
- Competitive Advantage: Gain a competitive edge by using insights based on data to make smarter decisions faster than competitors.
A Simple Framework for Using Data Analytics
So we all agree data is important. But structure and process are essential to make sure we extract what we need, when we need it. Data must be trusted. After all, decisions made on unreliable data can cost organizations in mining, transport, utilities, and government significant downtime, not to mention the risks of non-compliance, safety incidents, and penalties.
I’ve worked with data for decades, and I remain a fan of keeping it simple. Here is the five-step framework I recommend.
1. Define Your Goals and KPIs
What exactly is your mining, transport, utilities, government organisation to achieve? You need to identify KPIs to measure this progress. For example, in asset-intensive industries like mining, KPIs could include asset utilisation, maintenance costs, and equipment downtime. Defining targets that are meaningful to your organisation, especially cross departments, makes sure your data analytics aligns with your business objectives to deliver meaningful results.
2. Conduct a Data Audit and Map Your Data
Map your data across all systems (like ERP, EAM etc), and including unstructured data sources (like text documents, images, sensor readings etc). I know this can be a huge task in its own right, but you need to have a holistic view of all types of data you have. And if this defence organisation can do it, so can you - just look at those numbers! This comprehensive data audit will form the foundation of your project, and you’ll understand both the types of data available and identify gaps and inconsistencies (some of which may identify the need to modernise how you collect your data in the first place).
3. Clean and Organise Your Data
Data quality is non-negotiable. Without it you can't trust your data, and lack confidence and buy in to make both strategic and operational asset and organisation decisions. In fact, it’s the cornerstone of any successful data project. Cleanse your data by removing duplicates, inconsistencies, and inaccuracies. Structure your data effectively using databases, spreadsheets, or data warehouses. The result? Organised asset and organisational data that allows you to have confidence with step 4! And if you need help - talk to us.
4. Analyse Your Data for Actionable Insights
Now it’s time to use specialist analytics tools to uncover hidden patterns and trends in your data. Having set up your KPIs (for assets or the organisation) in step 1 will make this step easier and impactful. Identify areas for improvement, such as optimising maintenance schedules or pinpointing underperforming equipment.
5. Implement Data Driven Changes
It’s now possible to translate your data-driven insights into actionable plans. For example, a business could adjust maintenance schedules based on equipment usage patterns to extend equipment life and minimise maintenance costs.
Focus on the Right Data to Drive Growth
The success or failure of data analytics in asset-intensive industries depends on capturing the right information. Without structure, companies often drown in irrelevant or low-quality data. Poor data quality slows analysis, creates misleading insights, and drives poor operational decisions.
Take maintenance planning as an example. If equipment condition data is incomplete or inaccurate, work orders may be scheduled too late or on the wrong assets. The result is higher downtime, increased safety risk, and wasted spend. By contrast, when asset data is accurate and aligned to business goals, teams can prioritise critical equipment, reduce unplanned outages, and extend asset life.
Selecting a Data Platform for Growth
This framework demonstrates how data analytics can help asset-intensive organisations use their data wisely in a rapidly changing market. Choosing the right data analytics platform is crucial, and while off-the-shelf tools may work for some small businesses, larger organisations and enterprise businesses with complex data demand bespoke solutions.
That’s why we created our COSOL EAM Intelligence and Enterprise Intelligence suites. Offering scalability, seamless integration with existing systems, and user-friendly dashboards, our software helps mining, transport, energy, water, and other asset-centric organisations to make faster, holistic, and data-driven decisions.
About Adam Sharp
Service Delivery Director, Toustone | A COSOL Company
Adam Sharp has spearheaded the delivery of Decision Intelligence solutions across the Asia Pacific for decades. Adam has an extensive background in using data to optimise operations in asset-intensive verticals, like transportation, natural resources and logistics.
As an avid cyclist, Adam understands the nature of endurance and perseverance. This is not only reflected in his personal life but also in his approach to applying statistical and data analysis techniques in practical business scenarios to enhance decision-making.
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