Why digitalization and software are essential to the value chain

This article is brought to you thanks to the collaboration of The European Sting with the World Economic Forum.

Author: Noel Nevshehir, Director, International Business Services and Global Strategic Partnerships, Automation Alley

• Digitalization has transformed business models, veering them away from traditional brick-and-mortar businesses and physical assets and toward leaner ways of working.
• A further shift in software-driven production has allowed more space for innovation.
• Further progress will be seen via the adoption of artificial intelligence and machine learning to intelligently decipher continuous product and service improvements.

More than 10 years ago, Netscape’s co-founder Marc Andreessen wrote what turned out to be a pivotal commentary in the Wall Street Journal entitled, “Why Software is Eating the World” and, for that matter, its value chain, too. Today, software is disrupting and transforming the value chain—or a product’s lifecycle from cradle to grave—and the idea of traditional industries, such as brick-and-mortar retail stores and manufacturing.

There are legendary examples in the retail sector: Borders and Blockbuster being summarily displaced by Amazon and Netflix, respectively. In the automotive industry, Tesla’s market capitalization has risen to $941 billion today, exceeding the value of the next nine largest non-electric car manufacturers in the world, even though Elon Musk’s company’s physical assets and labour represent a mere fraction of its total capital investments. Software-driven business models have delivered efficiency and productivity while allowing firms to rapidly evolve and seize new market opportunities, meet changing consumer demands, and innovate at an accelerated pace.

So, how did this all happen? And if the software-driven approach is all that it claims to be, why aren’t more business and industry leaders fully integrating it into their enterprises?

Pre-requisites for digitalization

Digital transformation requires human transformation and a cultural mindset that champions continuous learning and experimentation. Musk was one of a few to recognize the importance of software in the value chain of industries based on hardware. However, the technological sophistication involved in designing electric vehicles, exponential rise in computational power over the last decade or less and overall complexity of vehicles with 100 million lines of computer code were somehow overlooked by established players.

Electric vehicles, which are literally, computers on wheels, possess a complex tech stack of integrated code that power the vehicle’s touchscreens, navigation software, safety sensors, plugged-in smart devices and cloud-based updates.

So, as the boundaries of hardware and software have become blurred and even indistinguishable, mechanical engineers have taken a back seat to software engineers.

Tesla’s success is also down to their online sales strategy, which has relieved them of dealership and sales staff costs. In addition, the company’s organizational structure leans toward one-tier teams without hierarchal bloat, making the company as a whole more agile and responsive to changes in market demand and consumer needs.

But traditional manufacturers are often reluctant to break away from their legacy systems and abandon a strategy or course of action because they have invested heavily in it, even when it is clear that doing so would be more beneficial.

Thinking fresh

Software and the speed of technological change, coupled with changing customer demands has enabled new businesses to emerge and being to overtake established players that relied on traditional business models without taking stock of the new realities causing them to lag behind on new technology.

But historically, human ingenuity has banked on putting aside what we already know: the use of empirical evidence for problem solving and instead, continually adapting for the contemporary world.

The breakneck growth in innovative technologies like machine learning (enabled by big data, artificial intelligence and algorithms) could continue providing solutions to future challenges. Software making software, despite its Orwellian connotation and with attention to debiasing, is the key to wealth creation and vastly improved global living standards.

In a 2019 Forbes article, Peter Bender-Samuel observed that software may have been eating the world but services today are now consuming software like prey.

Many manufacturers used to working with the physical may not be set up to operate in a world of services defined by the digital. But while the offerings of services are intangible, they are creating tangible results. Yet this is the lifeblood of digitalization as companies substitute labour, physical assets and legacy IT systems for capital spending on software.

What’s more, companies are opting to use their vendors’ software delivered by the cloud rather than pummel money into software data centres. This as-a-service paradigm shift has been shown to be more efficient and productive than owning the software, parsing code and managing the complexity of enterprise integration. It also avoids distracting designers and engineers away from improving quality and creating value.

This value is created by using algorithms and artificial intelligence to analyze sounder data and telemetry captured by the network to make better decisions to boost network performance.

Discover

How is the World Economic Forum ensuring the ethical development of artificial intelligence?

The World Economic Forum’s Platform for Shaping the Future of Artificial Intelligence and Machine Learning brings together global stakeholders to accelerate the adoption of transparent and inclusive AI, so the technology can be deployed in a safe, ethical and responsible way.

• The Forum created a toolkit for human resources to promote positive and ethical human-centred use of AI for organizations, workers and society.
• From robotic toys and social media to the classroom and home, AI is part of life. By developing AI standards for children, the Forum is creating actionable guidelines to educate, empower and protect children and youth.
• The Forum is bringing together over 100 companies, governments, civil society organizations and academic institutions in the Global AI Action Alliance to accelerate the adoption of responsible AI in the global public interest.
• The Forum’s Empowering AI Leadership: AI C-Suite Toolkit provides practical tools to help companies better understand the ethical and business impact of their AI investment. The Model AI Governance Framework features responsible practices of leading companies from different sectors that organizations can adopt in a similar manner.
• In partnership with the UK government, the Forum created a set of procurement recommendations designed to unlock public-sector adoption of responsible AI.
• The Centre for the Fourth Industrial Revolution Rwanda is promoting the adoption of new technologies in the country, driving innovation on data policy and AI – particularly in healthcare.

Contact us for more information on how to get involved.

Pivoting business models

Counterintuitively, the fact that services are eating software is actually accelerating the adoption of software because of the transition from a “license sale” to an “instant access rental” business model, the latter having substantially less friction and a much more seamless customer experience.

Software-as-a-service has resulted in software creeping into all areas of a company’s operations. Companies now must ramp-up internal software talent and technological savviness to align tools with long-term strategy and vision.

The software-first approach can be seen beyond manufacturing. In agriculture, for example, Deere & Company, which has dominated the market for farm machinery hardware used to plant seeds, fertilize fields and harvest crops, recently developed software to make its agricultural machinery more productive and efficient.

The Internet of Things has helped the almost 200-year-old company to develop self-driving tractors that can plow the fields on their own while deploying smart herbicide sprayers (with 120-foot booms aided by computer vision) that differentiate between weeds and crops. Imagine a high-speed planter deftly dropping seeds in precise numbers per-acre of farmland at exact soil depth to optimize crop yields.

Doing more with less mutually benefits farmers, consumers and the global environment. It also helps Deere generate more revenue by capturing previously hidden data that farmers can now access for a fee.

If software-as-a-service and a cloud-based approach to data management sounds familiar, pioneering companies that overlay a digital mindset on the physical world have paved the way for this shift in philosophy that is critical to navigating future supply chain disruptions.

If software eats the world and services are accelerating software distribution, imagine what is next for the Fourth Industrial Revolution.