Learn how design thinking, robotic process automation and artificial intelligence are defining the new wave of digital business transformation.
Almost two decades have passed since organizations began introducing digital technologies into their operational model. Yet, even today, there is little consensus on what the term ‘digital business transformation’ means.
Digital business transformation: an evolving term
The term ‘digital transformation’ has come to be used broadly to encompass both the implementation or use of technology within an organization, but also the adoption of a shakily defined culture of innovation. Companies that have engaged in a digital transformation strategy have seen a wide variety of results.
A study from MIT’s Sloan School of Business posits that if technologies have been introduced into organizations without a clear objective, they often remain unused by employees and simply do not deliver an impact on productivity.
In softer experiments including ones that promote a culture of innovation through structural change or innovation departments, large teams and multi-level hierarchies are broken down into smaller teams and a flatter organizational structure.
Although these initiatives are intended to make companies more agile and responsive in a quickly evolving market, they may or may not take the form of a technology.
Digital technologies certainly do make up a significant portion of the tools deployed in structural evolution. However, they do not provide assurance for real organizational transformation and innovation as measured through gains in productivity or increases in top-line revenue.
The difficulties in approaching digital transformation for well-established organizations result from two principal historic trends.
The first is the evolution of the IT department. IT departments were mandated with the creation, and later, adoption of new technologies in order to support the organization. As these structures evolved from building in-house solutions to outsourcing core activities to third-parties, they lost their culture of innovation.
The second trend is the rise of digital transformation itself. It is no understatement to suggest that most large organizations were laggards in the last technology boom. As significant as the technological shifts of the past decade, were the approaches to the business processes that were ingrained in the culture that accompanied them.
In response to this rapid evolution of the business environment, innovation teams were assembled for a variety of reasons. Some companies perceived threats from new market entrants and sought out to defend themselves. Others invested heavily in new products and lines of business in search of fresh revenue streams.
These teams began by looking outward, seeking to keep up with or prevent small, innovative actors of encroaching on their markets. The most intelligent organizations that weren’t able to beat their new competitors began acquiring them, amassing products and talent. Often these acquisitions resulted in the failure of the acquired products and the departure of the talent altogether.
Only in the past few years, have organizations begun to look inwards at the optimization of their processes and organizational structure. They are currently in the throws of understanding that the mechanisms that brought about technological disruption were in fact a culture of agility, a design thinking approach and a strong focus on talent and process.
As the age of data begins to dawn on large organizations, and as startups hark upon path of the productization of AI and machine learning, the question begs to be asked — how can digital transformation departments, innovation teams and IT be the winners in this upcoming wave of intelligent technology?
A modern understanding of digital business transformation
Boston College professor Gerald C. Kan, describes digital business transformation as “adopting business processes and practices to help the organization compete effectively in an increasingly digital world.”
Kan continues “much of the need for digital transformation is outside managers’ control and it involves adapting to how your customers, partners, employees, and competitors use digital technologies to change how they act and what they expect. Whether and how your company responds to those digital trends is the key question facing managers.”
In many respects, digital transformation can be viewed as an organization’s efforts to keep up. Many businesses have been bogged down by legacy systems or have lost the flexibility and culture to adapt to these challenges internally.
Kan views how an organization implements technology as “a small part of digital transformation. In cases where digital transformation does involve implementing new technologies, the technology is only part of the story. Other issues, such as strategy, talent management, organizational structure, and leadership, are just as important, if not more important, than technology for digital transformation.”
The professor’s insistence on the structural and environmental factors that influence digital strategies surpass organizational culture, but do not exclude it. More than technology, companies that will weather the upcoming wave of data-centric technology will need to fundamentally rethink their operational models. Investment, resources and patience must be allocated inwards, on the processes and people that contribute to the longevity of the organization.
How metriq sees digital transformation
Organizations are constructs – the result of individuals’ collaboration. For digital transformation strategies to be successful, they must be driven by human needs.
Both customers and employees can express these needs. The response can thus take the form of an outward or an inward approach.
Because responses are need-based, user experience design methodologies should be applied to understanding how a company’s customers or employees interact with an organization’s processes and products.
There are likely myriad needs inside and outside your organization. Investing in culture and talent to create or discover value is essential to long-term success. The difficult lies in determining the appropriate level of investment and the extent to which digital technology can have an impact.
Defining impact and subsequently selecting the most impactful project is a task in and of itself — one with which most organizations, even the most innovative, struggle.
In some cases, changing the way employees work can have enormous effects on internal productivity as well as top-line revenue. When these investments are made in technology in support of employees and collaborators, their impact on ROI can be amplified.
The emerging field of inward facing technology-based digital business transformation is driven by design thinking, but is expressed through robotic process automation.
Robotic process automation (RPA) is at the heart of automation. It is a means of automating the flow data to facilitate or remove interactions with a process. RPA encompasses an organization’s efforts to transform its operational model through the orchestration of data in service of humans.
The value of a simple RPA or “micro-automation” transforms an interaction or set of interactions in a process into an invisible passing of data from one medium or tool to another.
Take for example, the onboarding process for new employees. An HR representative must prepare a contract for a new recruit. He currently sends an email to the new employee with a text he drafts each time, asking for the same information. The employee replies to the email with text containing the answers to the HR representatives questions. The HR representative must read the email and prepare the contract manually, entering the values provided in plain text by the new recruit. He must then sign, save, attach and send the contract to the new employee.
Such a process accounts for total active time (for the HR representative and the employee) totaling 30 minutes.
An RPA would automate sending an email from the HR representative using a few variants of a standardized email and include a link to a form. The form would include all of the normal fields the HR representative would ask for. When the employee fills the form, the data is returned to HR and a contract is automatically generated and emailed to the HR representative for review. Upon signing the new contract via electronic signature, it is automatically attached to an email and sent to the recruit for signature.
The HR representative gains a total of 22 minutes, while the new recruit gains 6 minutes, a savings of 28 minutes, or an efficiency gain of 93% in time in addition to the monetary value of the HR representative’s time. The result is thus that an employee, liberated from his manual task, obtains a marginal gain in productivity and can allocate the saved time to more creative work.
More advanced versions of RPA leverage technologies like machine learning and are referred to as intelligent process automation (IPA). While IPA is not required in the vast majority of digital projects, it has the highest potential contribution to long-term efficiency gains.
In the next articles will explore more deeply the concepts of RPA and IPA and their role in shaping the organization of the future.
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