Far too often I see organizations who try to push their analytical tools to the limit beyond what they were intended to do. Sure, they have many features including report
development, calculations, visualization, data modeling and even some light data
transformations. However, there is much more in building a robust business intelligence
(BI) environment than just having your reporting tool do it all and it starts with first
developing a BI Strategy.
At its core, a well-structured BI strategy should provide a clear roadmap for leveraging
data as a strategic asset. It sets the direction for the organization's data-related
activities, outlining key objectives, and aligns data these initiatives with the broader
business mission.
What is Business Intelligence
Let us start with a basic definition of what is Business Intelligence. BI includes far more
than a mere reporting tool that generates reports and dashboards. It is a comprehensive approach to data management and analysis that empowers organizations to extract valuable insights from their data for informed decision-making. While reporting serves as a fundamental component of BI, the true essence of BI extends beyond just reports. It encompasses data integration, data quality, data analysis, visualization, governance as well as the alignment with organizational goals, collaboration, and a commitment to ongoing improvement, making it an essential strategic asset for organizations.
The BI Challenge
However, organizations often face challenges in deriving value from Business
Intelligence due to a variety of factors. A few common reasons include dealing with a
lot of data silos, a lack of focus on data governance, poor data quality, and employee’s
resistance to change have all hindered adoption and effective use.
For some organizations, there also seems to be too much focus on the technology
which is driven by IT rather than addressing the broader strategy and culture necessary
for BI to succeed. Without strong executive support and sponsorship, BI initiatives may
lack the necessary leadership commitment.
To overcome these challenges, organizations must develop a broader plan and hence,
here is where an effective BI Strategy can help.
BI Strategy
As mentioned earlier, BI strategy is a structured plan that outlines how an organization
intends to collect, analyze, and utilize data to drive informed decision-making. Below are
the key sections that you should include in your BI Strategy.
1. Goals and Vision
Start with the end in mind: Strategic leaders start by defining the desired outcomes
they want to achieve with their BI strategy and define how data will be used to
support those goals. This will require participation and buy-in from multiple
stakeholders across the organization, including business leaders, IT professionals,
and data scientists, to understand their needs and expectations and to gain support
for their data vision.
Examples may include goals for revenue growth, cost reduction, risk mitigation or
improving operational efficiencies. Try to get as detailed and specific as possible and
include a few use cases.
2. Current State Assessment
Performing a current state assessment is a crucial part of your BI strategy as it
provides a clear snapshot of your organization's existing BI infrastructure,
processes, and capabilities. Understanding the current BI landscape helps
identify strengths, weaknesses, and areas in need of enhancement, ensuring that
future BI initiatives align with organizational goals and effectively address any
existing challenges.
Identify gaps and opportunities. Based on the assessment, clearly identify and document the key gaps and opportunities for improvement. This includes identifying areas where the organization needs to invest in modern technologies, processes, or skills to improve data quality, accessibility, governance, and security.
3. Define Future-State BI Architecture
Based on your current BI environment and gap analysis, your organization may
need to invest in some newer technologies and training to support the goals and
future-state vison. The BI strategy should define a high-level, modern BI
architecture that comprises several key components essential for efficient data
processing and reporting. It typically includes:
Data sources, where raw data is collected (applications, databases, files, etc.)
Extract, Transform, Load (ETL) processes that capture, cleans, and prepares the data for analysis
Data warehouse or data lake for storage and data modeling for structuring data
BI semantic layer for creating data models, reports, and dashboards
End-user BI tools such as Power BI or Tableau, to allow stakeholders to access and interact with data and dashboards. In addition, robust security measures, data governance, and metadata management are integral parts of this architecture, ensuring data quality, integrity, and compliance
4. Roadmap
Finally, your BI strategy will include a multi-phase detailed strategic roadmap that will
guide your organization's BI evolution and incorporate previously identified future-
state analytical capabilities and architecture. It will define the sequence and timeline
of projects to support incremental release of business value and “connect the dots”
from current to future state. The roadmap should also include estimates to provide a
clear understanding of the effort, resources, and dependencies to implement the
data strategy.
In summary, organizations that are serious about leveraging their data assets take
the time and make the investment to create a BI strategy which aligns with its business goals. They continuously monitor progress, adapt to changing circumstances, and communicate vision to key stakeholders to foster a data-driven environment.
