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Democratizing Transformation — The case of Novartis and Microsoft
And the results of a 150 organizations survey
Harvard Business Review
by Marco Iansiti and Satya Nadella
From the Magazine (May–June 2022)
Summary (of the full version of the paper)
Many companies struggle to reap the benefits of investments in digital transformation, while others see enormous gains. What do successful firms do differently?
This article describes the five stages of digital transformation, from the traditional stage, where digital and technology are the province of the IT department, through to the platform stage, where a comprehensive software foundation enables the rapid deployment of AI applications.
The ideal is the native stage, whose hallmarks are an operating architecture designed to deploy AI at scale across a huge, distributed spectrum of applications; a core of experts; broadly accessible, easy-to-use tools; and investment in training and capability-building across the enterprise.
The Success Drivers
When we started our research, we wanted to understand why many companies struggle to reap the benefits of investments in digital transformation while others see enormous gains.
What do successful companies do differently?
We looked at 150 companies in manufacturing, health care, consumer products, financial services, aerospace, and pharma/biotech, including a representative sample of the largest firms in each sector.
Some were failing to move the needle, but many had made dramatic progress.
Perhaps surprisingly, we found that outcomes did not depend on the relative size of IT budgets.
Nor were the success stories confined to “born digital” organizations.
Legacy giants such as Unilever, Fidelity, and Starbucks (where one of us, Satya, is on the board)-not to mention Novartis-had managed to create a digital innovation mindset and culture.
.. surprising … outcomes do not necessarily depend on: (1) the relative size of IT budgets, or (2) “born digital” organizations
Our research shows that to enable transformation at scale, companies must create synergy in three areas:
1.Capabilities.
Successful transformation efforts require that companies develop digital and data skills in employees outside traditional technology functions.
These capabilities alone, however, are not sufficient to deliver the full benefits of transformation; organizations must also invest in
- developing process agility and,
- more broadly, a culture that encourages widespread, frequent experimentation.
Successful transformation efforts require that: (1) companies develop digital and data skills in employees outside traditional technology functions, along with (2) developing process agility and, (3) more broadly, a culture that encourages widespread, frequent experimentation.
2.Technology.
Of course, investment in the right technologies is important, especially in the elements of an AI stack:
- data platform technology,
- data engineering,
- machine-learning algorithms, and
- algorithm-deployment technology.
Companies must ensure that the technology deployed is easy to use and accessible to the many nontechnical employees participating in innovation efforts.
Of course, investment in the right technologies is important, especially in the elements of an AI stack … Companies must ensure that the technology deployed is easy to use and accessible to the many nontechnical employees …
3.Architecture.
Investment in organizational and technical architecture is necessary to ensure that human capabilities and technology can work in synergy to drive innovation.
That requires an architecture-for both technology and the organization-that supports the sharing, integration, and normalization of data (for example, making data definitions and characteristics consistent) across traditionally isolated silos.
This is the only real, scalable way to assemble the necessary technological and data assets so that they are available to a distributed workforce.
Investment in organizational and technical architecture is necessary … and requires an architecture-for both technology and the organization-that supports the sharing, integration, and normalization of data … across traditionally isolated silos.
Many large companies are making headway in each of these areas.
But even leading companies tend to underestimate the importance of getting employees to pull transformation into their functions and their work rather than having central technology groups and consultants push the changes out to the business.
… even leading companies tend to underestimate the importance of getting employees to pull transformation into their functions and their work rather than having central technology groups and consultants push the changes out to the business.
As Eric von Hippel of MIT has advocated for many years, frontline users, who are closest to the use cases and best positioned to develop solutions that fit their needs, must take a central role, joining agile teams that dynamically coalesce and dissolve on the basis of business needs.
… frontline users, who are closest to the use cases and best positioned to develop solutions that fit their needs, must take a central role, joining agile teams that dynamically coalesce and dissolve on the basis of business needs.
BOX: To enable transformation, companies must create synergy in three key areas: (1) Capabilities; (2) Technology and (3) Architecture
Capabilities
- Organizational culture
- Training and development
- Low-code/no-code tools
- Agile teams
- Organizational architecture
- Citizen developers
- Product management
Technology
- Machine learning
- Deep learning
- DevOps pipelines
- Data encryption
- Real-time analytics
Architecture
- Data platform
- Horizontal integration and normalization
- Data documentation
- API strategy
- Experimentation and risk
- Data governance
Building Tech Intensity
Our research unpacks how capabilities, technology, and architecture work together to build what we call tech intensity.
Derived from the economics concept of intensive margin-how much a resource is utilized or applied-tech intensity refers to the extent to which employees put technology to use to drive digital innovation and achieve business outcomes.
Our research found that companies that made good investments in technology and made tools accessible to a broad community of data- and tech-skilled employees achieved higher tech intensity-and superior performance.
Companies that failed to develop tech- and data-related capabilities in their employees and offered only limited access to technology were left behind.
We ranked the tech intensity of the 150 firms in our study and found that the top quartile of the sample grew their revenues more than twice as fast as the bottom quartile.
(See the exhibit “Digital Transformation Pays Off.” To score your firm’s tech intensity, go to www.keystone.ai/techintensity.)
We also found that technology, capability, and architecture indices correlated with other measures of performance, from productivity and profits to growth in enterprise value.
Using an econometric technique known as instrumental variables, we also found evidence that the relationship between tech intensity and performance was causal: That is, greater intensity (especially investments in technical and organizational architecture) powered higher revenue growth.
The Imperative for Leaders
The mandate for digital transformation creates a leadership imperative:
- Embrace transformation, and work to sustain it.
- Articulate a clear strategy and communicate it relentlessly.
- Establish an organizational architecture to evolve into as you make the myriad daily decisions that define your technology strategy.
- Deploy a real governance process to track the many technology projects underway, and coordinate and integrate them whenever possible.
- Champion agility in all business initiatives you touch and influence. And finally, break free of tradition.
- Train and coach your employees to understand the potential of technology and data, and release the innovators within your workforce.
This mandate extends to technology providers.
Despite much investment, technologies are still too complex and are often too hard to use and deploy. We need tools and technology that make driving transformation intuitive for frontline workers while keeping data secure. Let’s not forget that until recently many of us were relying on specialists in Fortran and Cobol to model business problems and even to perform basic mathematical operations. Spreadsheets brought about a revolution in mathematical modeling; we need technology providers to bring the same revolution to AI and make using a machine-learning application as easy as creating a pivot table.
Momentum is growing. But we must sustain the efforts to ensure that companies of all stripes make it across the digital divide.
A version of this article appeared in the May-June 2022 issue of Harvard Business Review. (full version)
Originally published at https://hbr.org on May 1, 2022.
Idea in Brief
The Problem
Many companies struggle to reap the benefits of investments in digital transformation, while others see enormous gains. What do successful companies do differently?
The Journey
This article describes the five stages of digital transformation, from the traditional stage, where digital and technology are the province of the IT department, through to the platform stage, where a comprehensive software foundation enables the rapid deployment of AI-based applications.
The Ideal
The ideal is the native stage, whose hallmarks are an operating architecture designed to deploy AI at scale across a huge, distributed spectrum of applications; a core of experts; broadly accessible, easy-to-use tools; and investment in training and capability-building among large groups of businesspeople.
About the authors
Marco Iansiti
David Sarnoff Professor of Business Administration,is a codirector of the Laboratory for Information Science at Harvard and of the
Digital Initiative at HBS.
Satya Nadella
Chairman and CEO at Microsoft
Names mentioned
Chief digital officer Bertrand Bodson, Novartis;
Eric von Hippel of MIT;
Victor Bulto, Novartis’s head of U.S. pharmaceuticals;
Lori Beer, JPMorgan Chase’s global CIO,
CEO Kevin Johnson, Starbucks
