Gathering and Documenting Business Requirements

Defining the business requirements is to identify a champion, all stakeholders, and SMEs in the organization. Next is to define the strategic goals and tie department activities to business goals.

Through this process, we’ll discover what leaders are trying to measure, what they are trying to improve, questions they want answered, and ultimately, the KPIs to answer those questions.

By starting with gathering and documenting the business requirements, we overcome the first roadblock to many IT or technical projects: knowledge of what the business is trying to accomplish.

Analyzing Data Source and Data Strategy

With a good understanding of what questions the business is asking, we can turn to the next element: analyzing data sources, how that data is gathered, and where the data exists. It’s unlikely that all data will be available within the organization and that it already exists in a place that’s accessible. So, we need to work backward to find the source.

For most of our clients, we built a matrix that mapped each source data to thier respective data category. We identified their business questions, understood the data needed to answer the question, and mapped each to a source system.

Data Architecture and Security

Our first piece of advice is: Don’t get caught up in the hype and latest technologies; focus on the business reasons for your initiatives. Building a flexible and scalable data architecture is a complex for which there are many options and approaches.

A modern data architecture represents all stages of the data lifecycle, from original data source to reporting-all the way through to analytics. An architecture diagram will identify and represent all the source systems, the methods to ingest data and the landing spots for that data (data marts, data lakes, and data warehouses).

Data Visualization, Understand and Interpret

A data strategy should provide recommendations for how to apply analytics to extract business-critical insights, and data visualization is key.  Data visualization tools should make the data look good, but more importantly, make the data easier to understand and interpret. 

Visualizations – Story Telling – Democratization of Data and Data Granularity: Be able to provide right level of detail for the right audience. An analyst may need more detailed information than an executive, and some people may need drill-down capabilities.

Data and Analytics Training

As we’ve stated, becoming data driven requires more than just technology. In this stage we look at the people in the organization and the processes related to creating, sharing, and governing data. A data strategy is likely going to introduce more data and data analysis and maybe new tools.

Based on this, it makes sense to look at the skillsets of the users to understand their strengths and where they’ll need support.

Do they need data and analytics training?

Do you need to hire more people?

Organizational structure should also be assessed—should analysts be aligned to a business unit or to IT?

And how IT will support the business in their analytics needs?

Data Dictionary and Governance

Data governance is what ultimately allows enterprise level sharing of data and analytics practice.

A data governance program will ensure that:

• Calculations used across the enterprise are determined based on input from across the enterprise.
• The right people have access to the right data.
• Data lineage (where did the data originate and how was it transformed since that origination) is defined.

We don’t look to a tool to solve data governance; it’s people work, and it has to happen. Data governance takes leadership and sometimes navigating through difficult conversations.

Data Strategy Roadmap and Recommendation

The data strategy roadmap is the culmination of all the work we’ve done to this point and what makes all our previous work actionable. We’ve identified all that needs to happen to bring you from where you are to where you’d like to go, but before getting started with any design, build, training, or re-engineering of a business process, it’s critical to prioritize the activities.

For each recommendation that will help bridge the gap from current state to the future state, define the feasibility and expected business value it will provide. The plan should prioritize activities that are easiest to implement but also provide quick wins to the business.

Other factors to include in the data strategy roadmap are:

• Staff availability and whether outside help is required.
• A company’s budgeting process, specifically if a capital investment is required.
• Competing projects that might prevent the right resources from participating.

The roadmap should also contain a timeline that allows for celebration of incremental wins that are earned along the way.