Why organizations must act like software companies with agile, devops, APIs and analytics capabilities

It is almost seven years to the day from when Mark Andreesen wrote a signature thesis on why software is eating the world. He wrote it nearly a decade after the internet bubble burst and he defended the growing valuations of technology companies based on increases in broadband access, the relatively low investment required to start a software company, and the increasing ability for companies built on software to disrupt legacy value chains.

Then five years ago, Peter Sondergaard declared during his Gartner Symposium keynote that, “Every company is a technology company” and should take steps to develop capabilities in mobile, cloud, social and information in order to stay competitive.

With many organizations in this midst of digital transformation programs, the question one might ask is how much like a software or technology company should the average enterprise or medium-sized business target? What practices should they adapt, at what level of investment, and targeting what level of maturity?

Technology backed companies dominate their industries

Recent studies and news provide some answers showing that the biggest companies keep getting bigger based on how they spend on technology. The top most productive manufacturing and service firms are at least 25 percent more productive than their peers based on a quoted study. These companies invest significantly in proprietary technologies and have a higher percentage of their workers in IT compared to their peers.

This week, Apple became the world’s first trillion-dollar company with $11.5 billion in profits in its most recent quarter. Apple’s milestone illustrates another key trend in big enterprise profitability. Kathleen M. Kahle, a University of Arizona finance professor shared research related to the profits from top companies. “In 1975, 109 companies collected half of the profits produced by all publicly traded companies. Today, those winnings are captured by just 30 companies.” This isn’t just a story about the four biggest technology companies, for example, the largest banks and the three largest United States based airlines control an overwhelming majority of their markets. 

But the race to build proprietary technology capabilities or to develop technology businesses has risks and speed bumps. Not everyone will succeed, and some will slow down or pull the plug before their complete vision is realized. Case in point, GE announced this week that it is seeking a buyer for parts of its digital unit. This unit generated over $500 million in revenue last year but required billions in investment.

The key technology investments that propel organizations

Seeing many examples of companies investing in their digital transformation programs here are several patterns worth reflecting on.

The first is that these companies establish flatter organizational structures and leverage agile, collaborative practices to drive experimentation. Agile drives a deeper customer mindset by enabling teams to understand customer needs and values before jumping into implementation. It then enables ongoing prioritization based on customer or end user feedback. Agile stresses ongoing experimentation and delivering capabilities to end users sooner to get quicker customer feedback and capture more usage data. I also argue that top organizations that want to achieve an agile mindset and culture integrate business functions such as marketing and operations into their agile teams. This ensures that the full delivery of the product or service can be achieved by a multidisciplinary group that handles technical and non-technical deliverables.

From a technology perspective, three key practices stand out. While developing applications is the backbone of improving customer experiences, many organizations are adopting API first strategies. Developing APIs not only drives application quality and scale, but it also is a catalyst for developing new data services and businesses. APIs are being developed by banks to increase distribution and compete with fintechs. In healthcare, APIs will be the backbone of improving patient matching and addressing interoperability of electronic health records. APIs can make a dramatic impact in industries where data standards are developed, and an ecosystem of participants create value chains that compete with legacy business models.

Second, technology companies are cloud-native organizations and have adopted devops practices, IT organizational strategies, and a devops culture to drive productivity, quality, and speed to market. According to a recent survey, 39 percent of respondents that adopted devops practices such a continuous integration and delivery pipelines are able to deploy code changes to customers in under twenty-four hours. Devops also allows organizations to be even more nimble by configuring infrastructure as code using tools like Chef, Puppet and Ansible and leveraging a new generation of monitoring solutions backed by AI such as BigPanda.

Lastly, integrating, managing, and analyzing data at scale is a key organizational capability top companies establish, and this is not just the work of data scientists. They invest in data governance to improve data quality, establish usage policies, and maintain data catalogs. They have technical strengths in integrating data and leveraging a hybrid of SQL and NoSQL datastores. They are experimenting with artificial intelligence to do pattern recognition, predictive analytics and personalizing customer experiences.

Finding technology accelerators that enable more with less

Unfortunately, most organizations can’t take on the same maturity of practices and level of investments compared to technology businesses. Enterprises and medium sized business need to identify technology solutions that accelerate their capabilities so that they don’t have to develop proprietary software or leverage their top talent against every business need.

This can be done by selecting appropriate digital platforms such as low code development, self-service data visualization, data prep, mobile development, and testing automation. These platforms help organizations develop technology and data capabilities faster and with less skill if business leaders are willing to make some compromises and leverage more “out of the box” capabilities.

But for most organizations, getting a technical capability released or enhanced faster is worth many compromises.