Digital transformation strategies for competitive advantage in 2025
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In 2025, adapting, refining and pivoting strategies will not be a matter of choice, but rather a necessity for survival and expansion for companies. Spending on technologies that support digital transformation is expected to reach 3.9 trillion dollars by 2027.
The figure shows the continued increasing effort by companies in this field. The road ahead is not simple, however, studies indicate that almost 70% of digital transformation endeavors fail due to mismanagement, unsupporting corporate culture, and vague goals.
Take the example of General Electric (GE). Once regarded as an industrial innovations leader, GE pursued a strategy of investing heavily into a digital unit with the hopes of transforming its operations and products. The project turned out to be underwhelming as a result of overly optimistic demand forecasts and internal pushback, and serves as a story of what not to do for other businesses with similar objectives.
Getting your digital transformation strategy right can lead businesses towards endless possibilities and provide a competitive advantage. Adopting a digital transformation strategy is not the challenge, rather mastering it is.
Formulating digital transformation framework to achieve competitive advantage
In simple terms, digital transformation can be described as the integration of digital technologies in every aspect of a business.
This includes the modification of business processes and the manner in which value is provided to clients. Does this enhance competitive advantage? When done effectively, it enables companies to gain the following benefits:?
For organisations to digitally transform efficiently, they can leverage pre-existing models, such as the McKinsey 7S Model. This model?focuses?on seven interrelated elements:?Strategy, Structure, Systems, Shared Values, Skills, Style, and Staff,?which help ensure alignment in the processes of transformation.
With the assessment and realignment of these components, businesses can develop an infrastructure that facilitates digital embedding.?
Furthermore, the MIT Sloan Digital Business Model framework offers important analyses by investigating the rebalancing of important relationships: Minds and Machines, Products and Platforms, and the Core and the Crowd. This strategy helps the reconfiguration of a company’s primary strategies to make the most out of the digital economy.?
As the digital world advances, no industry leader will dispute that for one to be competitive, the core of business strategy has to be based on digital transformation. Essentially, as McKinsey & Company noted, to succeed in digital transformation one has to make trade off decisions that will aid in the reinvention of the business.?
Alleviating the complexity of digital transformation is possible when these frameworks and insights are adhered to, in turn facilitating the fostering of sustainable competitive advantage alongside the growing digital landscape.
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Top trends with strategic cases and metrics
Integrating AI and machine learning
Strategy case
Many businesses now utilize AI for productivity growth. For example, AI is applied in writing codes, composing content, and even doing workflow management, which tremendously increases efficiency.
Companies that have AI integrated into their systems report a ROI that is almost 2 times higher than those who apply AI platforms for specific tasks and functions only. Moreover, 92% of large companies report achieving returns on their deep learning and AI investments.
Real life example
The emergence of DeepSeek, a Chinese AI startup, marked a major turn in the AI scene with its advanced open-source AI model called R1. This model competes with the best in reasoning from OpenAI and Google but at a much lower cost.
DeepSeek trained their R1 for under $6 million, using 2,000 less powerful chips instead of the tens of thousands of specialised chips that would cost around $100 million. The launch of DeepSeek's R1 has caused established AI companies in Silicon Valley to revise their plans since it indicates a movement from a focus on raw power to one of reasoning and optimization.
In addition, the fact that the model is open source means that any researcher in the world can examine its architecture and build on it, making a more collaborative approach to AI.
Challenges faced
Most companies find it challenging to determine the ROI on AI spending with only 31% of leaders expecting to be able to measure ROI in 6 months.
Emerging patterns
The increased affordability of AI is shifting investments from hardware to software, which is positive for companies such as Salesforce and Microsoft.
Expansion of cloud services
Strategy case
Companies are developing their capabilities in cloud services to enhance their flexibility and scalability. Around 45% of companies are upgrading their cloud infrastructure to facilitate the transformation process.
Metrics
Europe’s largest software company, SAP expects its cloud revenues to be between 21.6 bln euros and 21.9 bln euros in 2025, which will increase further due to the growth of cloud computing.
Real-life example
Airbnb uses cloud services to manage peak demand during holiday seasons by enabling “on-the-fly” scaling of infrastructure for high resource-consuming events like Black Friday.?
Challenges faced
Cloud cost management is a pain point for 82% of cloud decision makers.?
Emerging patterns
People want more sustainable features in cloud services, which are often overlooked.
Application of Internet of Things (IoT)
Strategy case
According to IoT Analytics’ 418-page IoT Use Case Adoption Report 2024, IoT initiatives appear more successful than ever, as 92% of enterprises report positive ROI from IoT use case implementations.?
Metrics
Various studies predict significant growth in IoT, particularly in industries where IoT can help save operational costs by more than 10-20%.
Real-world example
IoT has been used in environmental conservation through advanced sensing methods that promote monitoring and the protection of forest ecosystems. Advanced sensing technologies allow for a notable real-world application of IoT.
Devices have gotten smaller and smarter, becoming much more interconnected in the process, transforming data collection to even the most harsh of conditions. Innovations such as Dryad Networks’ wildfire sensors that detect preemptive signs of a fire, Treevia’s digitized dendrometers for tree growth monitoring, and Rainforest Connection’s illegal activity and wildlife monitoring smartphone powered devices are great examples.
Such technologies as Switzerland’s?eDNA-collecting drones, Freiburg University’s leaves sensors, Plant-e’s bacteria-powered sensors, and seed-dropping drones revolutionize forest conservation efforts by providing critical insight and reforestation.?
Challenges faced
Protecting the data and the underlying integration issues remain challenges for IoT implementation.
Emerging patterns
In 2023, the IoT integration market was predicted to be worth USD 3.83 bln, with an anticipated CAGR growth rate of 28.3% between 2024 and 2030.
This growth can be attributed to the rising number of connected devices, smart cities, advancements in AI and ML, a greater emphasis on cybersecurity, and the growing popularity and capabilities of edge computing.
Furthermore, the stronger focus on data-based decision-making is driving investment expansion, which is further aiding the growth of value from IoT platforms. These platforms enable businesses to collect data and provide analysis and visualization tools, permitting real-time decision-making.
The coming years are expected to provide further tailwinds to growth, enabling IoT’s full potential.
Want to read more? Maimoon's article was published in full at the AI Accelerator Institute here.
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3 天前Smart take, thanks for the share AI Accelerator Institute