Digital business strategy for climate action
« Without a great strategy, hard work becomes a nightmare. »

Quoting James Clear, you will find in the link a whitepaper on Digital Microeconomics and Business Strategy. Learn about product market fit, unit economics of software, network effects, sustaining value creation in time, data-driven culture, and much more.

https://medium.com/@solaire-georges/whitepaper-digital-business-strategy-c074e132d0b2

Digital microeconomics has changed the supply curve, creating a fundamentally different landscape from traditional industrial microeconomic theory. With digital products offering near-zero marginal costs, perfect replication, and instant distribution, digital platforms leverage these properties to maximize consumer surplus and harness network effects. Profit is now driven by quantity rather than high prices, making user base growth the top priority. By calibrating pricing towards benefiting the demand-side buyers and ensuring a freely functioning pricing mechanism, digital platforms can achieve higher growth, attract supply-side suppliers, and optimize revenues. Transparency, trust, and ongoing testing of pricing are crucial for success in dynamic digital markets.

Business strategy is contingent upon a rationalized vision that guides start-up experimentation, with subsequent hypotheses being empirically tested. The iterative process, inspired by scientific methods, involves the continuous refinement of theories based on feedback between theory and practice. Hypotheses are set based on validating or invalidating the Null Hypothesis, but also surprising findings and emotional responses.

Translating scientific insights into practice requires a data-driven decision-making culture where ideas are evaluated based on scientific merit. Understanding data through customer problems and maintaining high data quality are crucial. The role of the data scientist is essential in ensuring statistically sound and operationally relevant learnings. Balancing theory and practice, entrepreneurs must apply scientific methods to learn from customers and test growth opportunities.

Data analysis plays a crucial role in investigating and refining the models, with the scientist acting both as a sponsor and a critic of the model. Flexibility and the ability to recognize and exploit errors in judgment are essential qualities for a scientist. Statistical rigor becomes important after achieving Product-Market Fit, but the focus should be on practical and optimal understanding rather than excessive elaboration. Sufficient sample sizes and relevant user data are necessary for accurate analysis. Ultimately, sales revenue serves as the quantitative benchmark for achieving Product-Market Fit.

The energy industry is facing significant challenges due to the loss of control in value creation. Regulatory liberalization, technological advancements, and standardization of modular processes have disrupted the industry and created a vast choice space for buyers. For example, photovoltaic solar panels are a commodity. The concept of value has shifted away from being tied to specific goods or services. Buyers now determine value, which is thus relative and constantly shifting.

To succeed in this dynamic landscape, digital business strategy focuses on expanding the choice space for buyers, offering new dimensions of value, and adapting to buyer needs. Yesterday’s value engine may fail today. Business models alone are insufficient, and there is a need for sustained value creation through innovation and investment in new opportunity platforms. These enable the development of future value engines and provide spaces for flexible entry into new value-creating markets. The value architecture, which explains how value creation is sustained over time, remains constant while strategies evolve based on buyer value. Ultimately, the goal is to earn customer lifetime loyalty through wise digital strategy and consistent design within a single branded experience.