An interesting phenomenon has occurred during the past few years: IT professionals have become business-savvy, and business pros have become more tech-savvy. This relationship has evolved to the point where almost everyone has become a developer.
The increasingly pervasive role of citizen developers was discussed in detail recently by Tom Davenport and Ian Barkin in an MIT Sloan Management Review webcast. They also delved into the topic in a related MIT SMR article. The advantage of citizen developers is they offer an “understanding of both sides of the equation,” says Davenport, professor at Babson College and co-author of ‘All-in on AI: How Smart Companies Win Big With Artificial Intelligence‘: “They know what the problems are in the supply chain and they know something about how technology can help to make them better.”
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Davenport predicts hybrid professionals will increasingly deliver and maintain IT functions: “IT and businesspeople are both converging toward the middle.”
With the rise of citizen developers, “there’s almost 100% overlap in that Venn diagram,” agrees Barkin, an entrepreneur, educator, and co-author of ‘Intelligent Automation: Welcome to the World of Hyperautomation‘: “Ultimately, this is going to mean higher success rates for technology initiatives. Traditionally IT projects have a very high failure rate. It’s because there is a lack of overlap between domain expertise and knowing what it is that you’re trying to actually solve. And understanding the tools you’re trying to solve it with.”
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This overlap is happening “because humans are becoming more technical — more and more people are familiar with information technology, and we all pretty much use it every day in the context of our mobile phones, and our laptops and so on,” says Davenport. “At the same time, there’s this long-term trend that technology is becoming more human-oriented — it’s becoming easier to use, it’s a point-and-click thing, it’s a natural language thing, it’s better than having to understand complex programming languages.”
However, citizen developers are not ready to partake in designing enterprise architecture or planning and maintaining infrastructure requirements. These tasks will remain in the domain of software professionals, who provide guidance, plan strategically, and prove the viability of business technology.
“Guardrails are typically built into systems that provide standards, security protocols, and scorecards — basically making it easy to do the right thing,” says Davenport. “Some companies have created zone-based standards, where green applications are those that you can do whatever you want, yellow needs some supervision and risk management, and red, forget about it, IT has to do that,” says Davenport. “There needs to be ownership and handoff rules before people leave organizations and leave their departments are left holding the bag with no documentation.”
Barkin says all workers or professionals will need a basic understanding of technology and tools. “Do the people in business, the non-IT, the citizens, have the skills necessary to be those citizen developers and data scientists? There is research to suggest ‘no’. We have a skill gap as well.” He says research suggests 60% of enterprises have a massive gap, given the pace of technological change.
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The rise of citizen-developed, or perhaps self-serviced, applications is fortunate for another urgent reason: there aren’t enough people to design, build, and maintain the sophisticated systems that run today’s organizations and services.
People use the buzzphrase that “software is eating the world, and every business is now a software business.” Barkin points out: “It begs the question: Where are we getting all the software people if those realities are true?”
Part of the solution may be artificial intelligence (AI), he continues. citing Jensen Huang, CEO of Nvidia, who recently stated that “everybody in the world is now a programmer”. His point, says Barkin, “was that his industry needs to create computing technology such that nobody has to program. Nobody has to know Python or C++ anymore. Instead, they can program with a language that is human.”
That transformation means domain specialists — such as financial or manufacturing managers — can quickly and easily create or assemble the technology they need when required. “They can tap into their domain expertise to solve domain problems,” says Barkin. “Ultimately, the people who understand the domain, who understand the problem, now will have the expertise to utilize the technology that’s readily available to them because programming languages are becoming more human.”
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This shift in understanding is urgent, with an impending shortage of 160 million tech workers “that just aren’t in the market,” Barkin adds. “They just don’t exist. While the need is there because digital transformation is imperative, because every company is a software company.”
Much of this development work can be offloaded to citizen developers, who by an estimate from analyst Gartner, actually “outnumber professional software developers by a factor of four to one,” Barkin says. This split is likely widening, “as a result of things like generative AI coming out and making it just that much easier to use this technology.”
Davenport and Barkin also suggest using technologies, such as robotic process automation (RPA) and intelligent automation (IA), might be the best path for citizen developers to build and deploy applications tailored to their business requirements. Adopting this emerging technology alleviates the need to involve IT employees, who may not be fully familiar with the business pain points.
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“Compared with other forms of artificial intelligence, RPA and IA tend to be easier to implement and less expensive,” the authors suggest in their MIT SMR article. “RPA is being widely adopted to access data from multiple systems and to automate structured, information-intensive tasks, such as routing incoming customer emails or updating order status in a transaction system. When combined with IA tools, such as machine learning and character recognition, they can also make data-driven decisions and extract important information from documents, such as handwritten customer forms or key provisions in a contract.”
The authors also suggest that generative AI adds a whole new dimension. They suggest the technology helps make, “RPA design and implementation easier. Since OpenAI’s ChatGPT was announced, for example, several RPA vendors have announced interfaces between their RPA systems and the language capabilities ChatGPT offers. Before long, it should be very easy for a user to specify the desired attributes of the automation system in virtually any natural language and have a working prototype of the system automatically produced. The generative AI system should also be able to automatically create an easily understood description of the workflow and decision rules, if prompted to do so.”
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