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Data Democratization: Think of It as Home Renovation

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Read more about author Kartik Patel.

The focus of this article is on data democratization within the business enterprise, but the concepts and approaches involved in implementing this type of initiative are worth considering for any kind of major change within an organization. 

When thinking about business environments – how they are established and how they evolve – it is often helpful to use an analogy to which everyone can relate. In this case, we are changing the business environment to establish a more democratized approach to data and we might think of the existing business environment as the four walls of a house. 

Whether you built your home (or business) yourself, or you are living in that house and dealing with the structural decisions made by others, you have established a way of working and living that incorporates the strengths and the shortcomings of the structure. If you don’t have enough closet space, perhaps you purchase a wardrobe to accommodate your clothing. If you don’t have a large space in which to entertain, you may have your parties in the backyard or even rent a space to get together with family and friends. If you have a lot of stairs in your home, the chances are good that you gather your laundry into a basket over a period of days before you take it down to the laundry room – just to save yourself some steps. Over time, the flow of your life and the processes you use to accomplish tasks will morph to accommodate the reality of the house structure. 

And, so it is with workflow and business processes. Over time, a business establishes teams, processes, and workflow to accomplish tasks, and the people within each department and division further alter these workflows and processes to create shortcuts or to get the work done in a way that makes more sense to them. 

When an enterprise-wide change is contemplated, the business must acknowledge the very real existence of a culture within the organization and it must address that culture and understand how it works. That is the only way this type of enterprise-wide change will succeed. You wouldn’t begin a house renovation without drawing up plans, would you? Of course not. Consider the evolution of structural design over the past few decades. Today, architects and designers consider function (how the space will be used) and then design the form or structure, and decide how the space will flow and where closets, cabinets, stairwells, and other features will be placed to make the structure as effective as possible. 

Think of your business environment in the same way and remember that whatever new process or workflow you put in place will be altered by team members if it doesn’t work for them. So, include those team members in the planning phase. 

The following factors should be included in your data democratization initiative. Integrating these issues and roles into the planning process will ensure that you can build an organization that will improve Data Literacy across the enterprise and support the transformation of business users into citizen data scientists – team members who are comfortable using data to make decisions, present findings, and make recommendations and share and collaborate using data. 

Build a Comprehensive Set of Requirements

Think of this as sitting down with the family to discuss what changes should be made to your existing home or to make a list of those things you want so you can search for a new home. What is working? What is not working? Without a comprehensive understanding of how and when you currently use data and where there are gaps or restrictions that prevent business users from accessing and analyzing data, you are unlikely to accomplish your goals for data democratization. To democratize data within the enterprise, one needs access, easy-to-use tools, and a basic understanding of how and when data should and will be used to make decisions, as well as where and when it must be shared across roles and departments.

What are your business metrics? Do these need to change?  Are you measuring the right things? If you provide access to analytical tools for business users, what metrics will they use to know if they are meeting their goals and achieving the business vision? 

Ask how broad access to data can improve business results. How can it make your team more productive?

Your requirements must, by the very nature of the project, include a review of your data systems and repositories. To integrate data and make it easily accessible, you will need to build a strategy with your IT team, data scientists or analysts, and/or a consultant. But, you will also need to understand what type of training or access your individual team members and teams will need, and at what level the access should be provided so that you can design appropriate security and Data Governance policies. 

Build a Data Access and Collaborative Strategy

Once you have that list of features and functional concerns from your “family,” you can begin to design the home renovation or, in this case, the data democratization plan. 

Your project team should engage business users, present the data democratization rationale, and work with the team members to examine existing workflows and gaps. Be honest about what is working and what is not working. This is no time for your team members to hold back. What kinds of issues do they struggle to solve? Where are they missing data that would help them make better decisions? What technical or analytical skills do they have and what do they need to be confident in their use of new tools or processes?

Build business use cases that will help you sketch out the actual flow and outcomes to achieve your goals and reveal where there may be gaps or roadblocks. 

Your plan must also include ongoing reviews and continuous improvement so that when the initiative is rolled out, you have a way of measuring, monitoring, and adapting to ensure that these changes take hold within the enterprise and that every manager, team member, IT professional, and analyst understands their role, collaborates, and uses data to make decisions. 

Use the detailed requirements, use cases, and business process and workflow assessments to begin a search for your “architect” or technical consultant. You will be looking for services and tools that will fit your requirements and training and assistance to get you to your goals. 

Implement and Monitor

As with any change, the change must be embraced at every level or it will not work. Once the data democratization initiative is in place, the management team must support the use of these new tools and business processes and encourage their use by adapting team evaluations, creating expectations of data use in staff meetings, and reporting and asking thoughtful questions during interaction to ensure that team members are bringing in others and collaborating appropriately to get the right outcomes. If the team does not believe you are invested in the changes, they will not adopt new tools or they will find workarounds that more closely align with what is familiar to them. 

Find and leverage champions within each business unit and department. These people can become mentors to those who may be less comfortable with technology or with the new analytics tools and techniques. Create systems of reward and compensation, and change job descriptions and written goals and objectives to ensure that all systems support the new initiative. 

Schedule periodic meetings to discuss what is working and where there may be a need for changes. During these sessions, you may also wish to solicit creative ideas for how to continue the evolution. As team members get comfortable with the tools, the techniques, and the changes, they will often come up with great ideas to continue the growth of the concept within the enterprise. 

Establish and Maintain a Data-Driven Culture

Change is hard and it must be monitored and supported at every step if it is to succeed. Habits are hard to break and people sometimes feel threatened if they perceive that their role might be in jeopardy. Establish a culture that clearly states and supports the idea of data-driven decisions, reporting, collaboration, sharing, and team results and metrics. When you receive a report, ask questions about the data and where it originated, how it was gathered, etc. 

Ask what techniques were used. The first time you ask, you may get a blank stare but the second time you ask, the team member will know what is expected and will have done their homework. Use team meetings and presentations to provide your own metrics and analytics on things so you can role model these changes and tell your team members that if they need help preparing a report or analyzing an issue, there are resources that are ready to help. Depending on the size of the team and the resource demands, analysts, data scientists, and IT may be assigned these mentoring tasks, or you may use champions and power users within each department. The latter is the preferred method, as these people are typically more familiar to the team and it is likely they will feel more comfortable seeking them out and will take the time to talk to them because they know them well. 

A simpler way to think about creating this data-driven approach and implementing it on a daily basis is to think of your products and services as being composed of materials, pieces, steps in a process, and data. Every product or service should be built on the foundation of data – research about changing customer needs and buying behaviors, analysis of risk, mitigation of downtime, resource requirements, investment needs, etc. 

Much has been written about the benefits and future of data democratization in business but, to get there, an enterprise must understand its need for data, who is and will be using that data, how teams work today and how they will work in the future, and how to change the culture and sustain the use of these tools and this philosophy within the enterprise. If a business does not do the hard work of preparing for and planning its strategy for this change, it is not likely to succeed. 

Like a home renovation, data democratization does not miraculously happen on its own, simply because someone decides it is a good idea. There is a lot of demolition, hammering, and hard work. But, when the dust settles, you’ll be glad you put in the effort!

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