Data as a tool for value creation strategies

• The resilience of strategies is often only revealed in crisis situations.
• Data & analytics is the key to both realising quick successes and securing long-term value creation through transformation initiatives.
• Innovative approaches are needed to utilise data efficiently and effectively for value-creating strategies.

Crises and difficult economic situations make one thing clear: companies should not wait until such times to critically review their business models and performance. These should already prove their resilience in economically volatile phases.

However, even in crisis situations, it is not possible to completely dispense with a continuous review of the value chain. This allows optimisation and transformation opportunities to be identified, the consistent implementation of which can enable companies to realise EBITDA improvements in a timely manner.

Whether a company is able to act depends, among other things, on whether it can use the data available in the organisation effectively and profitably. A central component of value creation approaches should therefore be methods for measuring, analysing and quantifying data, with which data, insights and implementation capabilities can be combined. This enables companies to set priorities and create added value quickly and reliably.

In view of the current economic conditions and the associated challenges for companies, a holistic, data-based approach that can be used to analyse and optimise the entire value chain is indispensable. Companies are increasingly in the situation of having to generate financial added value in the short term as well as making effective long-term adjustments to ensure profitable value creation.

The use of proprietary data and the insights gained from it create the prerequisites for identifying and realising the most suitable opportunities to increase EBITDA. To understand the role that data and data & analytics play in this, it is worth taking a closer look at the four phases of data-based value creation strategies.

Data-based approaches to value creation require four phases, which ensure that a customised process is created that is aligned with the individual needs of a company:

1. preparation

In the first phase, market and sector analyses are carried out. Based on this, the precise project objectives can be defined and the relevant data requested.

2. value identification

In the second phase, the requested data is used to evaluate the various areas of the company and identify hidden potential for value enhancement. This allows the potential for operational and/or financial performance improvement to be quantified. Financial and operational analyses as well as benchmarking and comparative studies can be helpful for this.

3. value development

Once the potential has been successfully identified, the optimisation options are prioritised in phase three and customer-specific solutions are developed. It is particularly important here to identify quick wins and carry out strategic planning for the following months.

4. value delivery

Phase four is concerned with ensuring the long-term and targeted implementation of the optimisation plan. The defined goals and initiatives are transferred into an implementation plan, which can be used to continuously monitor the implementation status and success of the project.

This overview makes it clear that data and its analysis provide an important basis for identifying and implementing opportunities for improvement in all areas. Only on the basis of reliable data analyses can the performance of the entire organisation and its value chain be evaluated and value-enhancing measures derived.

These can be measures to improve the company's performance, realise potential savings or develop new skills. All components of the value creation process are considered (see Figure 1).