In our previous post, we introduced you to the data and analytics management methodology, “centrally driven, broadly distributed”. Having discussed the reasons why a “centrally driven” approach to data and analytics is optimal, this post will dive into the second half of the quote, “broadly distributed”.
“Broadly Distributed” Analytics Takes Down Silos
In many organizations without a robust data and analytics program, analytics is typically managed within silos as discussed in part 1. The reporting and analysis is then rarely distributed to the rest of the organization. Rather, it is kept “close to the chest” of the department that originated the analysis. This creates a “broadly driven, centrally distributed” approach whereby analytics originates in departmental silos and never leaves those silos.
Organizational transparency is critical to a strong data and analytics program. Marketing can no longer operate in a vacuum without support and communication with IT, Lending or Operations (to name a few in a banking context). These interdepartmental efforts create the need to view reporting and analytics across department reporting lines as well.
A “broadly distributed” approach to data and analytics ensures that data can be consumed by all departments in the organization. Of course, security measures must be ensured for particularly sensitive data, but operationally data transparency is of critical importance. If a new lending promotion is being planned, Lending shouldn’t have to jump through hoops to get Marketing data. Similarly, Marketing shouldn’t have to jump through hoops to get data from the Lending team.
Silos are bad.
From “I” to “We”
In organizations where analytics is not front-of-mind, there lacks an enterprise-wide view of processes, goals and operations. When data and analytics is “broadly distributed”, staff start to see how their department’s efforts contribute to the organization’s strategic goals.
Enterprise wide distribution of reporting and analytics enables inefficient processes to be identified early and reduce their negative impacts. For example, if a new lending product is not interfacing with the core properly, Lending, IT, Marketing, Operations or a staff member of any department could assist in identifying this process flaw.
More often than not, we tend to find that staff are willing and able to adopt an enterprise level view of their efforts. The challenge often lies in giving them the tools and access to fully embrace a view outside of their own department’s efforts.
A “broadly distributed” data and analytics program enables your employees to no longer think only about their department’s operations but about the enterprise’s operations with the big picture in mind.
Accurate Across Reporting Lines
In part 1 of this post, we described a situation where various members of different departments are asked the same business question, “how many members do we have?”. In a “broadly driven” (instead of “centrally driven”) data and analytics model, each staff member would go to their own data sources to retrieve the “correct” answer. Rarely does each staff member produce the same answer.
A “broadly distributed” approach in conjunction with a “centrally driven” model ensures that each employee retrieves data and analytics from the same, single source of truth (add link to data warehouse article). By distributing the “centrally driven” repository of data and analytics throughout the organization, accurate and consistent reporting proliferates throughout the company.
Combined with a “centrally driven” solution, a “broadly distributed” model is unquestionably the optimal approach to data and analytics. Eliminating silos, reducing inconsistencies and inaccuracies and ensuring an organizational mindset are but a few of the positive outcomes of this design. Coupled with the benefits described in our post on a “centrally driven” solution, our hope is that you and your internal team’s see the value in approaching enterprise analytics the proper way.
If your team needs any form of assistance in formulating your data and analytics strategy, give us a call at 860-593-7842 or send an email to email@example.com!
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