An increasing number of organizations are making data and analytics an integral part of their business operations. In Thomas Davenport and Jeanne Harris’ book Competing on Analytics: The New Science of Winning, they define the most analytically advanced businesses as “Analytical Competitors”. These organizations embed data and analytics into their operations and are a fundamental aspect of their business model. Data and analytics, then, is not promoted as a technology initiative but rather as a business initiative. This is a bit of a paradigm shift for most organizations with a less advanced analytic capability. However, data and analytics projects must focus on the business first to be implemented and adopted successfully.
What Happens if Data and Analytics Projects Focus on Technology First?
A common mistake for organizations just starting to build out a data and analytics program is to focus on the technology first. These organizations tend to first ask questions like:
- What data do we have available in our database?
- What data visualization tool should we buy?
- How can we get as much data as possible into our data warehouse/repository?
Each question lacks any insight into how business users will leverage data and analytics.
Focusing on what data is available currently potentially ignores a wealth of information not currently available to your business. External data, like US Census Data or social media information, is already ignored with this mindset. Especially in community banks and credit unions, their tends to be a large number of third-party applications. A majority of these applications may not be hosted on-site and, therefore, access to data stored in these systems could be currently limited. By focusing only on what data is currently accessible, potentially valuable data could be ignored.
Focusing on data visualization tools or data warehouse products should not be one of the first questions asked by your data and analytics project team. Last year, we posted an article titled “Having Business Intelligence Software is Not Equal to Having Business Intelligence”. In this article, we discussed why the tools alone are not enough. A business intelligence strategy needs to address how those tools will be leveraged. Training and development, cultural changes, and proper analysis of the business processes and needs are required for any actionable insights to be gained.
A data warehouse, which, for this post, we assume will be the foundation of your data and analytics program, is not meant to be a repository of ALL data. It is designed to to integrate data from various applications for the purposes of reporting and analysis. Simply copying operational databases with all available data doesn’t create a simpler, analysis-driven design. Organizations that don’t take an iterative approach to building their data warehouse often find themselves buried in an overly-complex project six months down the road.
So, Why Focus on the Business First?
Focusing on the business first creates some significant advantages:
- You understand the data needs of business users
- Better understanding of the processes that drive the business
- Complete picture of the application environment with data integration priorities applied to each source
Since data and analytics projects are designed to provide data driven insights for the business, focusing on the business needs of the business is the best starting point for these projects. With a better understanding of what your business needs, a technological solution can be developed. Without a clear picture of the data needs and goals of the business, there is no guarantee that the needs of the business will be met by the solution. Understanding the business and, specifically, their KPI and metric requirements should be a foundational part of the data and analytics project. Especially with project teams that are mainly supported and staffed by IT, these teams lack the organizational clarity and understanding needed to define high-quality requirements for the data and analytics project.
An understanding of critical business processes is essential to successful data and analytics projects. Processes drive how customers interact with the business and how staff interact with the applications. Each process creates data and each data point gives us a potential opportunity to create insights into operations. By understanding these processes, “quick wins” can often be uncovered to simplify processes or to reduce the amount of manual effort and time involved with them. These quick wins help justify a BI investment and improve the data and analytics project’s ROI.
If you focus on the business first, you will understand what applications are used throughout the organization. We find that our bank and credit union clients typically have well over 30, 40, and even 50 applications. Each application has a purpose; figuring out where that application fits into the data and analytics project is critically important to your strategic roadmap. With an understanding of all applications used in the organization, you will be able to accurately prioritize which applications should be integrated into your data and analytics platform and in what order. Coupling this with the understanding of key business processes, the data and analytics project team will have a great amount of business knowledge with which to design and support the initiative.
The summarization of this post is simple: focus on identifying the business needs for data and analytics FIRST. Only after addressing those needs should the data and analytics project team start to explore which technologies to employ and how best to design the solution. Data and analytics projects that focus too heavily on the technology inevitably fall short of their long term goals.