A decade ago, as much as 73% of enterprise data was classified as “dark data” by Forrester – stored but unused. CFOs understand that this dark data exacts a cost. The financial cost of storage. The environmental cost: dark data is estimatedto generate over 5.8 million tons of CO₂ annually. And the opportunity cost of lost potential.
Today’s advances in AI-powered analytics are helping industry to transform this untapped – and expensive – resource from cost center to value creator. As they seek to realize data potential, industrial companies are investing in advanced technologies and digital platforms across global manufacturing sectors at a rapid pace. The global manufacturing analytics market is projected to grow from $19 billion this year to over $60 billion by 2032.
McKinsey reports that when “implemented successfully, these solutions deliver irresistible returns.” Observable results include 30 – 50% reductions in machine downtime; 10 – 30% increases in throughput; 15 – 30% increases in productivity; and 85% more accurate forecasting.
Industrial CFOs have an important role to play in releasing this potential value from the massive, underutilized asset base of industrial data.
The best data-centric industrial and manufacturing companies are already leveraging their industrial data using manufacturing analytics tools to answer a wider variety of industrial challenges: asset optimization, process optimization, predictive and preventative maintenance, downtime reduction, failure avoidance, and increased overall efficiency.
The accelerating trend toward IT/OT integration creates new opportunities. It exposes traditionally siloed manufacturing and operational datasets to new tools, datasets and people. Industrial CFOs have access to process data in a way they never had before. Now, the power of operational intelligence extends far beyond the shopfloor, traditional process optimization or Overall Equipment Effectiveness (OEE).
By integrating industrial, operational and process data with financial data, industrial CFOs can engage with industrial data in new ways, enhancing strategic decision making and driving value throughout their organizations.
In fact, industrial data is becoming one of the most powerful financial value drivers as IT/OT integration opens up industrial data to a new and broader set of use cases, led by forward-thinking industrial CFOs.
CFOs arethe gatekeepers of the strategic planning process and financial disciplines. This combination puts industrial CFOs in the ideal position to drive thedigital and analytics transformation that will release the value of theorganization’s industrial data.
Theindustrial CFO plays a central role in:
So wheredoes this add value for industrial companies?
Industrial CFOs can seize the opportunity to utilize industrial data to optimize entire production networks – employing advanced modelling that can span every step from purchasing to production to sales. By bringing together a full range of disparate datasets, such models can help manufacturers decide what to buy, what to make and how they should make it in order to maximize profit.
One European manufacturer used a mixed-integer model to optimize its production network and supply chain. The model encompassed more than 500 variables to explore non-linear cost curves, more than 3,000 constraints related to production capacities, transportation and contracts, and hundreds of production steps. This effort, accounted McKinsey, unlocked millions of euros in annual savings.
CFOs can support industrial leaders to prioritize investment and resources by linking industrial metrics with financial data and modelling to understand both the risk and impact of production changes.
As well as directing funds and resources where they will have most impact, by understanding the value potential of previously “dark” data, CFOs can improve the way data is reflected as an asset within the organization share price – creating a virtuous circle of data asset realization.
Organizations that treat data as an asset and invest in data monetization are more likely to outperform peers and achieve two to three times the return on investment on key metrics, according to Deloitte.
Real-time transparent industrial data empowers CFOs to strengthen compliance, resilience and risk mitigation activities, as well as public reporting on these matters. In particular, by integrating industrial datasets with environmental, social and governance (ESG) initiatives, CFOs can strengthen the measuring, reporting and risk modelling of organizational sustainability.
The modern industrial CFO is already defining and tracking KPIs that go beyond financial metrics. These KPIs encompass operational, market and, increasingly, ESG and sustainability indicators.
The extra transparency in sustainability reporting delivered by industrial data is crucial to meet rising expectations of investors, customers and supply chain partners as well as strengthening the business’ reputation and long-term value.
While the best performers are already driving value, many industrial and manufacturing businesses still struggle to make use of the mountain of potential intelligence. According to McKinsey, “many organizations are two to three years behind on their analytics journey than they are in their digital journey.”
Companies need industrial data platforms that not only capture, collate and consolidate operational data but that can integrate easily with higher-level and IT systems and advanced analytics tools to open up these new data possibilities.
COPA-DATA’s zenon software platform is the ideal backbone for industrial organizations. Using zenon, organizations can connect OT data, IT systems, and business software to break down data silos and create a unified data backbone that serves as a foundation for cashflow analysis, ROI models, investment planning, risk and sustainability reporting, and cost optimization.
Armed with zenon, industrial CFOs who are fluent in technology will be better equipped to guide strategic investments and articulate digital, data, and analytics priorities. But this type of organizational advanced analytics transformation must be a team effort – from CFOs and top leadership through managers and process engineers, maintenance and shopfloor operators – with a mindset of continuous innovation and improvement. CFOs and companies that take this organizational-wide approach will maximize the value they release from their industrial data.