Digital disruption is changing how organizations create value and deliver goods and services. Digital disruption is transforming industries. The disruption manifests itself in new digital tools, digital services, and expanded data capture and analysis. Digital transformation initiatives by managers in one firm in an industry promote more rapid and ongoing innovation in that industry and in others. Successful adoption of new approaches using digital tools and data leads to more change and more disruption. We have a digital device society, with smart phones and IoT common place. Digital disruption is not an “if it happens,” but rather a “when it happens” phenomenon. Digital disruption is the change that occurs when new digital technologies and business models affect the value proposition of existing goods and services. Understanding and acting appropriately when digital disruptions occur is necessary. Managers should embrace change and build upon innovation.
Analyzing data are now a core decision support task for many organizations. Managers must try to derive greater value from multiple, diverse data sources using analytical tools and decision support applications. Digitalization of activities and processes has led to an explosive growth in data. Big Data has hence increased the need for analytics. This major change has increased the need for managers to understand the possibilities of these technologies and their application in a variety of areas including financial services, manufacturing, retail, pharmaceuticals, health care, and government. As managers across these sectors formulate IS/IT strategies and make investments, it is essential for them to consider how data-based decision making and analytics can contribute to improved decision making, improved information and knowledge management, and ultimately to greater organizational success.
Most decisions are what Jeff Bezos labeled as Type 2 decisions that can be reversed, altered, and changed. The cost of remedying a suboptimal Type 2 decision varies, but use the data you have, analyze it, develop a data story, share the story and get feedback, then go for it. Commit and implement. Many of these operational and tactical decisions should be a priority for implementing advanced analytics and algorithms. we need to find ways to make the decision better and faster.
Strategic, Type 1 decisions deserve and require more thoughtful data-based and data-informed decision making. New data may need to be collected and analyzed. Implementation and commitment may need to be made in stages. Knowing that a decision once made and implemented cannot be reversed is a daunting thought. There is no going back. The decision to digitally transform an organization is a Type 1 decision. Craft a vision for digital transformation and analyze it carefully, then senior managers must decide and make a commitment to the vision. Middle-level managers will and should be responsible for the related Type 1 and Type 2 decisions that must be made to realize the digital vision in that specific organization. Developing a clearly stated vision statement and writing a scenario describing the transformed organization will help guide subsequent data-based decision making.
Many busy managers want to grasp the basics of analytics, data-based decision making, and digital transformation. That quest has begun. Prior chapters discussed decision making and digital transformation, data-based decision making, analytics and high-velocity decision making, and finally implementing digital transformation. The overall goal for prior chapters has been to help managers become more knowledgeable about the what, how, and why of data-based decision making. One hopes greater awareness of the importance of data-based decision making will help managers better assess, choose, and successfully implement digital transformation competitive opportunities.
Figure 6.1 depicts the factors that are determining the winners and losers in the race to implement digital transformation visions and strategies. The basic relationships in the model identify data-based decision making as the key independent factor that can alter outcomes and results in organizations including successful implementation of a digital transformation vision. The relationship is moderated primarily by alignment of organizational elements, adequate and appropriate resources, a skilled team, and the digital transformation vision itself. Characteristics of individual decision makers and organizational factors are especially important to success.
Figure 6.1 Factors that influence organization outcomes
Digital transformation involves making decisions about technology trade-offs and ideally choices are data-informed and fact-based. Data-based decision making is both a process and a culture. Some managers and organizations already value using data and facts to make decisions. Part of digital transformation is to make systematic use of data in decision making. Decision making using data and facts is both a precursor to digital transformation and the reinforcement of a data culture and improved data-based decision making is and should be a necessary consequence of digital transformation.
Global business activity is accelerating and decision-making activities and processes must be responsive to changing business needs and a high-velocity decision environment. Understanding what is occurring can increase the adaptive response of managers.
Finally, understanding the need for new technology supported processes, better use of data in decision making, and possibilities for revised and innovative business models is not sufficient. Managers must understand how to successfully implement digital transformation competitive opportunities. A strategy without an implementation plan and action taking is wishful thinking.
Society is in the midst of profound and irreversible change. Data are everywhere and data provide the opportunity for new business models, increased efficiencies, and greater effectiveness in meeting customer needs. The digital world is volatile, uncertain, complex, and ambiguous. We cope with digital disruption by developing a vision, understanding technology opportunities, simplifying our processes, and using data, and by clarifying our intent and purpose.1
What can we conclude about the broad questions we identified in the introduction? First, we asked how can managers become data-based decision makers? Second, we asked how can digital transformation become part of an organizational strategy? Third, we sought to identify the new skills managers must develop to implement digital transformation? Finally, we asked how will we know an organization has been successfully transformed? So what have we concluded?
First, managers can become data-based decision makers by accepting and understanding that many, if not most, decisions should be based on and informed by data. Asking the “right” questions and getting factual answers is the starting point to becoming a more systematic decision maker who uses relevant data sources and prepares appropriate analyses. Analyses don’t need to be complex, rather tools like data visualization can help identify meaningful relationships for follow-up analysis.
Second, digital transformation can become part of an organizational strategy when managers at all levels learn about leading technologies edge and explore opportunities. It is important to pilot process improvement projects make analytics and decision support to customer facing staff and encourage risk taking and innovation. Managers need to take measured risks. Successful change needs to be rewarded quickly and showcased. Failed innovation must be ended quickly, but those involved must be encouraged to try again. Opportunistic decision making based on data must be encouraged as part of the digital transformation journey. The path to digital maturity is neither short nor easy, the path often involves a steep learning curve, some waste, and false starts. Embarking on a digital transformation journey must start with experimentation and innovation. Data must be captured and analyzed to determine what worked and what aspects of the change need revision or even elimination. A digital transformation vision and strategy should have broad scope and ambitious objectives. Digitally immature organizations need to have decision makers who focus broadly on technology and have strategies that are not only operational in focus.
Third, the new skills managers must develop include analyzing data, visualizing data and data storytelling. Every manager does not need to be a data scientist, rather every manager should strive to be an intelligent consumer of the new skills managers must develop include analyzing data, visualizing data and data storytelling.
Finally, we will know an organization has been successfully transformed when a data-centric culture is entrenched, when data-based decision making is rewarded, when the organization is reporting strong performance and results over a few years, and when performance exceeds that of organizations serving the same or similar needs. We want to create a self-reinforcing cycle of ongoing digital transformation where successful change leads to further success.
Agility is the way forward to find a successful digital transformation. Following a plan for digital transformation is important, but adapting the plan quickly to changing requirements and needs is more important.2 Enjoy the digital journey!
1 Bob Johansen http://iftf.org/bobjohansen