In a recent article, the president of Accelleron’s digital division, Cristian Corotto, asserted that digitalization and data were the fundamental foundations for sustainable business transformation. Digital technologies have allowed modern organizations to gather and measure unprecedented amounts of data, allowing them to gain insights and develop strategies that were previously impossible. In this article, we consider how this happens – the key steps in the journey from data discovery to effective transformation.
1. Identifying Inefficiencies
The first step towards sustainable business transformation is identifying areas of inefficiency within an organization. These take various forms, including wasted resources, loss of time, unproductive processes, missed opportunities, delayed reactions, confused governance mechanisms and poor decision-making. By harnessing the power of data, businesses can pinpoint these inefficiencies and develop policies to directly address them.
An important and practical example is for organizations to identify patterns of waste in energy consumption, water and ground usage, and around their exploitation of raw materials. By analyzing these patterns, organizations can implement changes to minimize this waste, reducing their environmental impact, while simultaneously improving the bottom line.
2. Optimizing Processes
Once any inefficiencies have been identified, the next step is to optimize those processes to enhance company sustainability. Data-driven insights can help businesses streamline their operations, reduce waste, and maximize resource efficiency. Process optimization should also result in increased productivity, enabling organizations to maintain growth without the negative impacts to the planet.
Through analysis of data points along the supply chain, for example, companies can identify bottlenecks and inefficiencies. By addressing these issues, organizations can reduce their environmental impact, improve relationships with suppliers and customers, ensure the ethical sourcing of materials, and help ensure the company is able to respond quickly to unexpected events in either the market or in terms of regulations.
3. Discovering New Opportunities
Bringing together information from data silos that were previously quite separate can foster entirely new ways to add value in consolidated value chains. For example, IOT applications can detect maintenance needs helping organizations to improve safety and security while also reducing downtime and extending the life cycles of products and assets.
Cristian Corotto
4. Understanding the Customer
Ready access to large volumes of high-quality information can improve an organization’s understanding of customer behaviour, increasing customer trust and loyalty towards brands and companies at the same time.
Understanding how customers use a software package, for example, can help developers identify the most frequently-used functions and also understand where they encounter difficulties which may be eliminated. They can continually optimize products around human-generated metrics, as opposed to guesswork or unguided experimentation.
5. Informed LCA Decision-Making
The final aspect of sustainable business transformation is informed life cycle assessment (LCA) decision-making. Data-driven insights can help organizations make smarter decisions, aligning their goals with sustainability objectives. This includes decisions related to product design, manufacturing, logistics, sales and support.
Data analysis can reveal, for example, trends in consumer preferences for sustainable products, allowing businesses to adapt their offerings accordingly. Likewise, data can help organizations identify potential regulatory change risks and market disruptions, enabling them to proactively address these challenges.
Sustainable Data-Driven Culture
To fully harness the power of data for sustainable business model transformation, organizations must foster a data-driven culture. This includes:
- Investing in data infrastructure: a robust data infrastructure is essential for collecting, storing, and analyzing large volumes of data. By investing in the right technology, organizations can ensure they are able to not just collect and store data, but also extract valuable insights.
- Developing data literacy: to make the most of the data at their disposal, businesses must ensure that employees possess the necessary skills for understanding and analyzing data. This includes training in data analytics, visualization, and interpretation, as well as promoting a culture of curiosity and continuous learning across the board.
- Embracing data governance: maintaining data quality and ensuring compliance with relevant regulations requires clear governance. This includes defining data ownership, establishing data access controls, and implementing processes for data validation and cleansing.