that use advanced analytics and predictive and prescriptive capabilities, but whose primary job function is outside the field of statistics and analytics.4
Citizen data scientists tell stories about a company based on company data by translating this data into a language that everyone can understand. Most of all, citizen data scientists need to be curious. They have to be able to recognize potentially useful information in a large amount of data and to highlight and translate key findings for other employees and departments.
The culture of citizen data science is based on the strategic topics of big data processing and cloud computing and artificial intelligence, and supports data-driven decision-making and the maker culture.
Maker Culture
The maker culture encourages employees to think about what kind of apps, processes, or algorithms they could build for their organization. While it once required software development skills, building apps today can be done within minutes and without writing a single line of code. This creativity is not limited to apps; it also includes process automation and algorithms that can be easily reused in the entire organization.
The maker culture is based on the strategic topics of artificial intelligence, process automation, blockchain, and Internet of Things (IoT), and it supports citizen data science.
Impact
Every organization has a set of core competencies and unique assets. The digital strategy needs to identify specific differentiators that can unlock impact beyond the original core competencies and leverage the unique assets.
Core competencies can manifest in different ways depending on the industry. Unique assets might be physical assets like retail stores, proximity to customers, or intellectual property. While some of these impacts are specific to core competencies and unique assets, some impacts are more generic and can be triggered by fostering a certain culture. Here are some examples:
Attracting new employees, enabled by the collaborative culture
Knowledge generation and exchange, enabled by the collaborative culture and the culture of data-driven decision-making
Understanding customer behavior, enabled by the culture of data-driven decision-making and the culture of citizen data science
Improving products and customer service, enabled by the culture of citizen data science and the maker culture
Reducing time to market, enabled by the maker culture
There are, of course, also certain impacts that cannot directly map to the culture but are conditioned by a strategic topic directly. Here are some noteworthy examples:
Reducing total cost of ownership (TCO), enabled by big data processing and cloud computing
Scalability, enabled by big data processing and cloud computing
Agility, enabled by process automation, blockchain, and IoT
Furthermore, it is possible that impact initiated by a certain culture helps to improve another culture within the organization, for example, by using the insights from remote work data to understand the way the team works (data-driven decision-making) and to modify future tasks and processes for better collaboration (collaborative culture).
Digital Capabilities
Enabling impacts requires continually developing a wide range of digital capabilities. Let's stick with the previously mentioned examples and take a look at which digital capabilities would be required to pursue them.
Attracting New Employees
Unified communications: Using chat and video call beside traditional channels, such as email and phone
Collaboration tools: Working together on notes, documents, spreadsheets, and so on
Remote work: Working from everywhere with secure access to all company resources
Knowledge Generation and Exchange
Self-service business intelligence: Asking your own questions without tying up your traditional business intelligence (BI) team
Visual analytics: Seeing and understanding patterns with interactive visual interfaces5
Data literacy: Communicating insights for a human-information discourse
Understanding Customer Behavior
Stream processing: Streaming customer feedback and needs in real time
Governed data discovery/mining: Acquiring new or enriching existing data sources that the organization can rely on
Social media ingestion: Improving customer retention by leveraging social media data
Improving Products and Customer Service
Machine learning: Providing the ability to automatically learn and improve from experience without being explicitly programmed
Chat bots and recommender systems: Providing information to users according to their preferences via a chat interface
Human-in-the-loop: Leveraging the power of human intelligence to improve machine learning–based models
Reducing Time to Market
Low-code/no-code: Allowing citizen developers to drag and drop application components, connect them, and create platform-agnostic apps
Application design (UI/UX): Creating products that provide a meaningful user interface (UI) and a relevant user experience (UX)
Cybersecurity: Protecting computer systems from the damage or theft of data, as well as from service disruption
Reducing Total Cost of Ownership (TCO)
Serverless architecture: Eliminating the need for server software and hardware management
Data center transformation: Migrating the on-premise IT infrastructure to a cloud hyper-scale environment
DevOps: Shortening the development life cycle and providing continuous feature delivery
Completing Your Digital Strategy Big Picture
Once you’ve identified the impacts that you want to generate and the corresponding digital capabilities, it is time to complete your digital strategy big picture, as shown in Figure
