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Digital Transformation is not solely a technology process – though the term “Digital” might lead one to believe that is the focus. Digital Transformation (Dx) is achieved when an organization plans and exploits digital technologies, workflow and processes, and its core capabilities and skills with an enterprise culture that evolves and shifts to engender a digital business model that advances business. Any Dx plan must include a review and appropriate modification of businesses’ processes, business models, operations, team collaboration, and customer relationships. 

By definition, Digital Transformation must also enable Data Literacy among its team members. Data Literacy describes the capacity of an organizational team to gather, analyze, and use data in a meaningful way to advance the business and to make decisions. The term ‘literacy’ as applied to reading the written word, implies that one can read the words and interpret them to gain insight into the material and to understand the point the author is making. When the term ‘literacy’ is applied to data, it means the same thing: the reader is able to consume and understand what the data says and can explain those concepts to others, share the information, and accurately interpret the data to make decisions, solve problems and leverage should be able to use data to inform and drive activities and tasks and to gain insight into the big picture so every team member can add value, achieve objectives and optimize performance. 

Since a Data Literacy and Digital Transformation initiative will touch all aspects of the organization, it is critical to bring technology and cultural changes together by identifying those business users that have, by their nature, a respected position within the enterprise, are curious about and use data on a daily basis and are open to change. Transitioning business users of technology into Citizen Data Scientists will help to integrate Data Literacy and Digital Transformation within the teams, departments, and divisions of the business. 

When combined, Digital Transformation and Data Literacy provide a rich and profound value to the organization. A properly structured initiative will prepare the business for an ever-changing market and business environment and make the business and its team members agile, nimble, and capable of responding to change. The initiative, once employed, will provide many benefits to offset the efforts involved in completing the initiative.

The benefits of a Dx and Data Literacy approach are numerous. Here are just a few of them:

  • The business can drive the customer experience and buying behavior with insight into data to anticipate changes, new products, etc.
  • The organization can innovate processes and activities on a tactical, operational, and strategic level to optimize resources and move more quickly in the market.
  • The business can attract and retain team members who embrace and adapt to change, thereby ensuring that the organization will not ‘age out’ of the market with old, tired approaches to business. 
  • The enterprise can build and sustain a nimble infrastructure and IT portfolio and an analytical environment that can be used by every team member. 

As mentioned in the first paragraph of this Introduction, it is important for businesses to realize that a Dx and Data Literacy project is not simply a technology project and, moreover, that this type of project takes planning and will work best with incremental changes and a roll-out and deployment that acknowledges that change takes effort and commitment at every level within the enterprise. When a business decides to adopt a Digital Transformation and Data Literacy initiative, it must begin with a comprehensive review of its tools, processes, culture, technology, and team.

Steps in the Process

As the business begins its review and planning process, it is important to keep the customer at the center of its experience. Every change must support the core business purpose and acknowledge its mission and vision. While data may seem a dry and unengaging way to focus on a customer, it is actually the way that the business will gain a better understanding of its customers. The data is right under the noses of team members but it is either inaccessible or difficult to understand for the average team member. 

With the customer firmly ensconced at the center of the process, the enterprise can then begin its review of the various aspects of the business that will inform, impact, and ensure the success of the Dx and Data Literacy initiative. 


One of the first steps in the Dx and Data Literacy review process is to look at Technology and understand the roadmap and trails a team member must take to find information and to use that information. 

If the team is to become more data literate and the organization is to transform into a data-driven enterprise, it must first make its systems, solutions, and data more accessible and easier to understand. It must ensure performance and scalability for mobile access and create an environment where users want to adopt new tools and techniques to use in everyday tasks. 

If the business wants to encourage digital transformation and data literacy, it must provide its team members with the right tools and it must expand processes and workflow within those systems to streamline access and provide insight to partners, suppliers, and stakeholders. The enterprise must look for ways to break down the walls of data silos and integrate data to make it accessible with appropriate security and reporting for all manner of information sharing and collaboration. 

In looking at the goals for transformation, the organization can focus on small, incremental changes that will support a long-term goal of total transformation and building the flexible technology environment it wants to ensure scalability and agility for the changes to come. 

Short-term projects should focus on function and productivity improvement and on encouraging the continuous change process that will provide team members with the support they need to learn and grow in the new data-driven environment. An organization must transition to a cloud environment in order to avoid rebuilding platforms in the short-term and can thereby make more data available to begin to build access and encourage analytical engagement among all team members. 

For long-term projects, the organization can then look at selecting, designing, and implementing a more flexible, modern environment that will meet its needs in the future and continue to support the digital transformation initiative as it evolves. 

Critical to the new technology strategy is the selection and implementation of an augmented analytics solution that will remove the handcuffs on team members and allow them to find and use data and become comfortable with that data. Data flow and data sharing are inherent in this strategy as well and, as business users become Citizen Data Scientists and embrace the use of data to make decisions and find solutions, the business analyst and Data Scientist team will be free to work on more strategic issues. Data Literacy and Digital Transformation cannot take root and grow if team members are not comfortable with data. Augmented Analytics allows team members to leverage easy-to-use tools that will build their confidence and understanding and act as training mechanisms to help them integrate data and data sharing into the daily culture. 

It is imperative that a Dx project include the assessment and investment in tools to support team members in embracing a data-driven, fact-based process that leverages data and data literacy at every level of the organization. Restrictive technology tools or tools that are only designed for IT or data scientists will not advance the initiative. s

The Data Literacy and Digital Transformation initiative should include a focus on transitioning business users within the enterprise to create Citizen Data Scientists. The renowned international technology research firm, Gartner, defines a Citizen Data Scientist as, ‘A person who creates or generates models that use advanced diagnostic analytics or predictive and prescriptive capabilities, but whose primary job function is outside the field of statistics and analytics.’ In order to successfully execute a digital transformation strategy, a business must provide easy-to-use, intuitive tools that will enable business users and create Citizen Data Scientists to improve data literacy and increase the use of data throughout the enterprise.


When planning for Dx and data literacy, the enterprise must also acknowledge that culture will play a primary role in making changes. The ‘way things are done’ is always an obstacle to new ideas and concepts and it will be important to address the existing culture with an eye toward workflow, processes, and collaboration. 

Team members must understand that the organization has made a commitment and that commitment must be clear in all forms of team evaluations and interactions. The enterprise should engage team members in the process and ask for creative, out-of-the-box suggestions on how to streamline processes, automate approval loops, and optimize time and resources. The organization must encourage the use of data in decisions and presentations rather than accepting the old processes and workflows as adequate. 

Dx strategies cannot focus solely on what happens online. There are a lot of activities and tasks that are completed with human interaction, staff meetings, phone calls, and other methods and means. The organization must acknowledge all the steps in the process and bridge the gap between the online and offline worlds. This strategy should apply to how the business is used to interacting with customers as well. What processes are used to engage a customer or client or to communicate with a supplier or a stakeholder or partner? 

As the enterprise pursues data literacy and digital transformation, there should also be a cultural transition to take business users of technology toward a Citizen Data Scientist role. That shift in role will allow team members to access and leverage data and augmented analytical tools to increase their knowledge and confidence in the use of data for daily decisions and to encourage data sharing and collaboration. 

Team members and customers are human beings, first and foremost, and they are used to doing things a certain way. The enterprise must first understand the culture it has created and supported, if it is to change that culture. 

For example, a regional theater company has a set of processes it uses to communicate with its team, move information for ticket purchases, plan events, work with suppliers, schedule ushers, and seat customers. If the business wishes to digitally transform these processes, it must understand the flow from the perspective of a customer, a team member, and a supplier to ensure that its changes are:

  • truly changes that will digitally transform instead of just changing a step from email to text, for example
  • supported and encouraged by all members of the management team with plenty of training and access until the team understands the new process, 
  • receptive to ideas from team members, customers, etc.
  • implemented with time for transition without creating chaos

A successful shift in culture requires new skills, a team that is hired or re-trained to accept and embrace the concept of constant change, and to see data as a critical tool for building strong customer interaction and team collaboration. Dx requires that team members help to train one another, share ideas, and engage in an environment that is more open to risk and creativity. 


The concept of Champions might be incorporated into the Culture change discussion above, but it is important enough to warrant its own heading. Changes in culture cannot take place without champions at every level.

Managers, Senior Executives – First and foremost, the management team must be committed to Dx and data literacy and it must invest more than just financial support. When managers receive reports or presentations, when managers deliver team evaluations, and when managers interact with customers, partners, and suppliers, every manager must show support for these initiatives in what they say and what they do. They must make decisions based on data, encourage training and support for team members allow for risk and creativity in the environment, and enable change by using data literacy and digital transformation initiatives as examples of role model behavior and by embracing these new ideas in their own processes and behavior.


IT and Data Scientists – Culture shifts within the enterprise will require that IT support and embrace new short-term and long-term initiatives and communicate with management to be sure that funding and timetables are established to ensure success across the enterprise. The business will look to IT professionals for guidance and IT must be honest about its assessment of its own skills and whether it requires support from outside the enterprise to get the job done. For example, an IT team may need support in implementing and rolling out an Augmented Analytics solution and in providing training to business users to ensure that they adopt these solutions. Data Scientists will be challenged to review their own processes and the sole domain of data that has been theirs for some time. These professional analysts will be asked to transition to change their own processes and culture so they can collaborate with business users to encourage the use of data and models and to act as the next stop on data analytics for projects that may require more strategic focus. Data Scientists will be asked to champion these initiatives and to support the concept of data literacy outside the walls of their own departments.


Team Members and Business Users – When considering this population of employees, the business should look to existing power users and those who are curious and use data today in their day-to-day interactions. Look for a team member with a profile that makes them a respected member of their community, someone who has a firm grasp of current workflow and processes and sees the potential for improvement and streamlining. These champions will be on the ground, day-to-day, supporting, spending a few minutes with another team member to show them how to use a tool and generally being a cheerleader. The enterprise should be certain not to create an adversarial relationship between these champions and the general population of the teams by setting them apart of favoring the or creating unrealistic expectations for the timing and success of these changes. When an organization engages business users in a transition to the Citizen Data Scientist role, it can identify likely candidates for this role and leverage these team members as Champions within the ranks of the teams.


Where to Start

In order to ensure success, an organization will want to start small to get some small wins that will improve the visibility and reputation of the Dx and Data Literacy initiative. As the enterprise conducts its review and planning process, look for small changes that can be made quickly as a way to introduce the idea of data literacy and digital transformation within the enterprise. 

If the business is a larger enterprise with multiple locations, it is unwise to roll out a new, radical, change to all locations at once. The business might choose a likely candidate to make these changes and then monitor and document the results so it can learn from the first roll-out. One example might be to choose and deploy an augmented analytics solution in one location so that sales, marketing, and advertising teams can integrate data and begin to achieve insight and make decisions based on that data with automated alerts and thresholds to alert them to the need to address an issue or to make sure a supplier will deliver on time so that there is no interruption in-store deliveries. To engender and speed the initiative in a select location, it is wise to identify Citizen Data Scientist candidates and provide them with the support, training, and flexibility to use these new tools and to share their experience and support with other users so that the enterprise can begin to build a positive environment in which to make changes across the organization. 

As this data literacy initiative progresses, the enterprise will gain valuable insight into the technology changes, culture and workflow changes, and other factors they will need to address in a larger initiative. Once this ‘test run’ is complete, the participants may become champions for a roll-out in another location by providing tips and support to others as they embrace the changes. 

To begin work on the Digital Transformation and Data Literacy initiative, the enterprise should appoint a team of professionals from various aspects of the organization. Every industry and business function is a bit different so there is no real rule for where to start. 

Here are some examples of initiatives in various industries that might provide some fodder for thinking through a starting point:

  • A utility company that manages water supply decided to automate certain processes and steps in its process to ensure that it could anticipate repairs and provide information to engineers, repair staff, and even customers. It created a technology ‘center’ of information by integrating systems and data to monitor water mains, take readings, and provide real-time information via a smartphone app to engineers and techs in the field and to make it easier to notify customers along a certain line when the water flow would be shut down for repairs. This long-term project required a change in the technology platform and, as that was happening, engineers, techs, and other team members were provided access to existing data and reports so each team member could understand how data could be used and make suggestions on what they might need to make their job easier. 
  • A jewelry supplier engaged in the use of blockchain technology and implemented a smartphone app to allow team members to see custom jewelry pieces as they worked through the design, construction and delivery process and to automatically notify customers to let them know when the jewelry would be delivered to the store and give them the option to pay online and deliver the jewelry to them at their home or other location. The sales staff is alerted to delays in delivery schedules and can work with jewelers or suppliers to understand and resolve issues. 
  • A large automobile manufacturer decided to start small with automation analytics and changes to its back office processes to streamline and optimize workflow and resources related to purchasing, accounting, and HR, with an eye toward long-term management and streamlining of the supply chain, equipment maintenance, staffing, and scheduling, etc.

As the enterprise considers a Digital Transformation and Data Literacy initiative, is important to reinforce the idea that the best approach is to make incremental changes and that, while the business may be anxious to get to the ‘end point’, Dx and data literacy are not achieved by going from Point A to Point B but, rather by establishing the environment that will support and encourage constant change and optimize resources and creativity – all in the service of supporting business goals and objectives. This is not a point-to-point journey but rather one that will, and should, continue for as long as the business is active. So, take the time to plan and execute and do it the right way. 

Remember that any major cultural transition is challenging because it requires that people change attitudes and behaviors and are, perhaps, asked to focus on new rules and guidelines. This will take some time but, the investment will pay off. It is not a sprint, but rather a long-distance run! 

The successful Dx and Data Literacy initiative will encompass a technology review, an assessment and plan for culture change, the identification and leverage of champions to support the initiative, and a patient approach. Look for short-term and long-term changes and focus on the customer! It is imperative that a Dx project include the assessment and investment in tools to support team members in embracing a data-driven, fact-based process that leverages data and data literacy at every level of the organization. Restrictive technology tools or tools that are only designed for IT or data scientists will not advance the initiative. If all team members and roles are to be included in the transition, data literacy and digital transformation must also take business users of technology toward a Citizen Data Scientist role.

A properly structured initiative will prepare the business for an ever-changing market and business environment and make the business and its team members agile, nimble, and capable of responding to change. The initiative, once employed, will provide many benefits to offset the efforts involved in completing the initiative.


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