OPEX & business transformation hinge on data analytics

Operational excellence (OPEX) and business transformation success hinges on data analytics and business intelligence. That’s a key finding from the PEX Report 2024/25, which assesses the results of a recent survey of almost 200 professionals.

Data analytics empowers businesses with predictive, prescriptive and real-time insights that optimize operations, enhance efficiency and sustain competitive advantage. Almost two-thirds (64 percent) of surveyed organizations are using business intelligence dashboards to support OPEX and transformation, followed by data visualization (42 percent) and process intelligence (27 percent).

Power of data analytics and business intelligence

Businesses are also using customer analytics (26 percent), sales and marketing analytics (26 percent) and employee experience and people analytics (25 percent) to support OPEX and transformation. What’s more, almost a third of businesses (31 percent) are planning to invest in business intelligence and data analytics over the next 12 months.

A robust framework of data analytics and business intelligence empowers companies to achieve a strategic advantage by continuously refining and adapting processes, eliminating waste and inefficiencies, says industry analyst Madhu Kittur.

Central to this is predictive analytics, which uses machine learning algorithms to project potential operational disruptions. By analyzing historical datasets, companies can predict maintenance needs, streamline supply chain operations and minimize downtime.

The integration of real-time data across various systems further supports OPEX and business transformation initiatives, enabling technologies like robotic process automation (RPA) to take over repetitive tasks. This minimizes human error and accelerates process execution.

Advanced models can synthesize data from internet of things (IoT) sensors and other sources to optimize logistics and inventory management, while analyzing market trends through business intelligence enables organizations to stay ahead of emerging opportunities and threats.

Ishneet Kaur, National Grid, reflects on what it means to innovate

5 steps to data analytics and business intelligence

While the potential benefits of data analytics and business intelligence are significant, a disciplined, modern yet practical approach is essential for business process improvement and business transformation overall, says Teresa Fortescue, chief marketing officer (CMO) at ProcessMaker.

She outlines five key steps to practical data analytics and business intelligence.

1. Collect, cleanse and integrate your data, determining all relevant internal and external data sources to create a unified view.
2. Select a tool that is easy yet comprehensive, deeply reviewing the user interface and workflows with respect to analytics capabilities and the ability to deep-drill on specific data parameters.
3. Create predictive models that are AI-based, establishing the specific objectives and key results (OKRs) and key performance indicators (KPIs) your models need to optimize.
4. Design responsive dashboards and reports to ensure they support your unique requirements.
5. Continuously monitor, plan and adapt to change, updating and improving data analytics models based on internal feedback and external data.

READ MORE HIGHLIGHTS FROM THE PEX REPORT 2024/25

• Half of businesses deploy enterprise-wide OPEX & transformation
• Cost, budget limits biggest challenges of OPEX & business transformation
• Change management integral to OPEX & business transformation