Cookies help us display personalized product recommendations and ensure you have great shopping experience.

By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    big data analytics in transporation
    Turning Data Into Decisions: How Analytics Improves Transportation Strategy
    3 Min Read
    sales and data analytics
    How Data Analytics Improves Lead Management and Sales Results
    9 Min Read
    data analytics and truck accident claims
    How Data Analytics Reduces Truck Accidents and Speeds Up Claims
    7 Min Read
    predictive analytics for interior designers
    Interior Designers Boost Profits with Predictive Analytics
    8 Min Read
    image fx (67)
    Improving LinkedIn Ad Strategies with Data Analytics
    9 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Why BI-COE: Struggling to justify ROI?
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Data Management > Best Practices > Why BI-COE: Struggling to justify ROI?
Best PracticesBusiness Intelligence

Why BI-COE: Struggling to justify ROI?

SmartAnalytics
SmartAnalytics
5 Min Read
SHARE

Current BI landscape is cluttered with too many tools and technologies. The plain vanilla BI deployments rarely produce desired results. This leaves IT teams to a mere data steward role rather being a potential business partner. Primary inhibiting factors are: exponential data growth, lack of best practices and leveraging prior experience.

Contents
  • What is BI-COE – the Solution:
  • BI-COE Strategy:
  • Deriving ROI for COE: ***IMP***

Current BI landscape is cluttered with too many tools and technologies. The plain vanilla BI deployments rarely produce desired results. This leaves IT teams to a mere data steward role rather being a potential business partner. Primary inhibiting factors are: exponential data growth, lack of best practices and leveraging prior experience.

Organizations today need to focus on Business that derives deep insight into its products, services, customers, and geography and market initiatives. Thus to gain maximum business benefits, there is a need to leverage an effective BI Center of Excellence (BI COE) strategy that can meet the business intelligence requirements with an optimum ROI.

More Read

Can Business Analytics Outperform Humans at Multitasking?
AI is Changing the Landscape of Lead Generation
Long-Range Planning Does Not Work in Isolation
Benefits of Having AI-Powered Software Solutions for Expense Management
Sandy Kemsley gives us a glimpse of what happened to Fuego

What is BI-COE – the Solution:

A CoE integrates the skills, resources and experience of both Business and IT to achieve the common goal of the enterprise: i.e. to achieve fast and accurate BI solutions for senior management to make a right decision at right time.

BI CoE is pooled expertise that supports the efficient implementation, enhancement and maintenance of common business processes and best practices built around the BI tools.

It is a cross-functional team with specific tasks, roles, responsibilities and processes for supporting and promoting the effective use of Business Intelligence across the organization. The functioning of this end-to-end BI implementation would include data integration, data quality, data management, reporting, KPIs, workflow and data visualization.

The following fig. depicts a typical BI COE concept that results in enabling organizations to establish a sustainable and successful BI-COE?
BICOE Conceptual View

Figure 1: A Typical BI COE Conceptual View

BI-COE Strategy:

Where do we start? Before we begin, it is essential to have a good grasp of the business domain to derive a clear set of requirements that define the business need. Elaborating on the same lines, following scoping aspects must be identified:

Scoping Aspects resized 600

Figure 2: BI COE – Scoping Aspects

Irrespective of a certain BI COE scenario, the requirements can be classified either as RFEs, Issues/Service Requests and Production Support activities. This is further illustrated in the following visual:

Next essential step in the process is deriving effort estimates for each kind of activity. Leveraging vast experience in delivering diverse BI/DW solutions, one can quantitatively evaluate the resources required to deploy the COE sustenance activity.

Parameters for sustenance activity resized 600

Figure 3: Parameters for sustenance activity

Deriving ROI for COE: ***IMP***

It is very important for organizations to compare and realize the difference between BI as Tool implementation and COE as Solution implementation.

For instance, consider an organization that wants to understand how users react to a new BI deployment project. In addition to analyzing current data, the BI CoE could provide comparisons with past BI deployment wherein conditions were different, as well as map user requirements appropriately and accurately in that context.

For an end to end BI deployment, it would have the following key parameters.

RFE, Issues Resolutions, Maintenance, Support, Service Level Agreement (SLAs), Time by Support. Defining every parameter will provide the scalability in implementing BI COE. A perfectly leveraged project has seen more than 40% Gross Margin Improvement through Service Products, which is to say the least remarkable.

The amount of data is enormous, and the BI CoE helps to chart an action course. Given an idea of the necessary parameters i.e. RFEs, Issues, Maintenance and Production support activities then the BI COE SMEs can quickly (<24 hours) analyze customer organizations’ requirements and come-up with the proposed BI COE solution with the ‘Gross margin’ , ‘Net Cost Savings’ and benefits.

After deriving the efforts and quantitatively evaluating the above initiatives, organizations clearly realize the difference between BI as tool implementation and COE as a solution to get the highest productivity, cost savings and best decision. 

Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

AI role in medical industry
The Role Of AI In Transforming Medical Manufacturing
Artificial Intelligence Exclusive
b2b sales
Unseen Barriers: Identifying Bottlenecks In B2B Sales
Business Rules Exclusive Infographic
data intelligence in healthcare
How Data Is Powering Real-Time Intelligence in Health Systems
Big Data Exclusive
intersection of data
The Intersection of Data and Empathy in Modern Support Careers
Big Data Exclusive

Stay Connected

1.2kFollowersLike
33.7kFollowersFollow
222FollowersPin

You Might also Like

big data and SMEs
Big DataBusiness IntelligenceExclusiveKnowledge Management

Big Data and the SME: Prepare to Succeed

5 Min Read

The “Four Layer” Model Applied to Unstructured Content

4 Min Read

5 Ways Predictive Analytics Cuts Enterprise Risk

5 Min Read

Retail Data Monetization: Are you sitting on top of a retail goldmine?

6 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

AI and chatbots
Chatbots and SEO: How Can Chatbots Improve Your SEO Ranking?
Artificial Intelligence Chatbots Exclusive
ai in ecommerce
Artificial Intelligence for eCommerce: A Closer Look
Artificial Intelligence

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-25 SmartData Collective. All Rights Reserved.
Go to mobile version
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?