How to Choose the Most ROI-Driven Partner for BI Modernization

Modernization of Business Intelligence is not just about a technology refresh anymore. It’s a business decision that needs to create tangible business value. The problem is that all of the BI modernization partners offer almost the same promises: fast dashboards, high-quality data, self-service analytics, and cloud scale. The issue is who will be able to create tangible ROI out of this.

In this guide, you will learn how to evaluate the BI modernization partners, differentiate between specialist analytics vendors and big consulting firms, and understand what creates ROI in BI modernization projects.

Perceptive Analytics’ POV

Here at Perceptive Analytics, we hold the view that BI modernization must be measured in terms of business results and not the technical aspects. The benefits of a good modernization project include reduction in reporting efforts, decision-making speed, consistency of KPIs, and higher user adoption rates. Successful projects are those which lower maintenance costs in order for analysts to focus more on providing insights than on dashboarding, data management, and reporting.

It is always evident from our experiences that the best ROI results in companies whose modernization efforts include governance of self-service analytics, scalability of semantic models, data quality checks, and operational dashboards that provide insight within a few seconds.

1. What ROI-Driven BI Modernization Really Means

Many companies evaluate the effectiveness of their modernization efforts based on technical parameters alone. But it is important to focus on real ROI, which comes from business value created by analytics.

Six Key BI Modernization ROI Metrics to Track

• Time-to-Insight Improvement
  
  • Decrease in report development time.
  • Quick availability of operational KPIs.
• User Adoption Improvement
  
  • Increase in number of dashboard users.
  • Higher self-service adoption rate.
• Infrastructure Optimization
  
  • Lower costs of legacy platforms.
  • Better management of cloud resources.
• License Reduction
  
  • Discontinuation of redundant BI software.
  • Simplification of vendor list.
• Decision Making Influence
  
  • Faster reaction time of operations.
  • Better forecasting accuracy.
• Risk Reduction
  
  • Improved governance.
  • Lower compliance and audit risk.

As per the guidance of Microsoft on power BI governance, successful analytics initiatives are those which achieve the right balance between user empowerment and governance, thus delivering positive results in terms of productivity and compliance. Governance becomes an enabler of business benefits here.

Questions to Ask Your Possible Partner

• How do you assess BI modernization success?
• Which KPIs did improve in your previous projects?
• Could you show us some before/after business metrics?
• How do you measure post-implementation adoption?
• What realistic ROI period could we expect?

2. Evaluating Partner Track Record and Proof of ROI

Sector-specific experience is vital since there is variation in terms of the usage patterns of dashboards, governance considerations, and the structure of KPIs.

Eight Types of Evidence You Can Ask For

• Sector-relevant case studies.
• Before/after comparison of KPIs.
• Adoption measures.
• Enhancements in data quality.
• Executive testimonials.
• POC results.
• ROI calculation.
• Ongoing client relationship.

According to research conducted by McKinsey, firms carrying out focused transformations can achieve tangible benefits within one or two years, with top performers achieving three dollars of value for each dollar spent. The research emphasizes that focused transformation efforts driven by businesses yield better results than technology-driven, broad-scale projects.

Examples of Perceptive Analytics Success Stories

One of such success stories is Perceptive Analytics’ Sales Forecasting Transformation, wherein automation of forecasting and analytics enhanced decision-making speed while minimizing manual effort:

Another success story is related to Perceptive Analytics’ Executive Marketing Dashboard project, through which consolidation of marketing performance metrics in one report facilitated quick executive decisions:

The Transform Decision-Making with a Unified View of the Business project involved standardization of reporting and increased operational transparency for leadership teams:

Such examples prove business value, not just dashboard implementation.

3. Uncovering Hidden Costs and Risks in BI Modernization Partnerships

Most BI projects tend to go over budget due to underestimation of hidden costs.

Six Hidden Costs

• Change management.
• User training.
• Data cleansing.
• Legacy system integration.
• Custom development support.
• Vendor lock-in.

Typical Risks

• Highly customized architecture.
• Inadequate semantic model design.
• Low adoption.
• Consultant churn.
• Governance failures.
• Scope creep.

Academic literature on enterprise data modernization projects has consistently found that organizational and governance issues tend to pose a higher level of risks than the choice of technologies themselves. The studies of data mesh and enterprise modernization approaches stress the importance of governance frameworks, ownership and sponsorship.

How to Expose Those Risks?

Ask vendors:

• What assumptions do not apply to your offer?
• What activities need client’s resources?
• What do you do about knowledge transfer?
• What will happen after project completion?

4. Perceptive Analytics vs Larger Consulting Firms: Strengths and Weaknesses

A common decision involves choosing between a specialized analytics partner and a large consulting organization.

Six Key Trade-Offs

• Specialists tend to achieve faster analytics results.
• Big companies can offer more transformative capabilities.
• Specialists can be more flexible.
• Big companies can offer bigger delivery teams.
• Specialists are likely to give more personal attention.
• Big companies can be better suited for extremely complicated global programs.

What makes Perceptive Analytics stand out is our dedication to analytics, data engineering, standardization of KPIs, dashboards and automation. We have teams comprised of technologists and domain specialists who know how industries do business.

• Cost, ROI, and Commercial Models: Smaller Specialist vs Large Firm

Cost and ROI Factors

• Length of project.
• Utilization of resources.
• Licensing costs of platform.
• Maintenance cost.
• Staffing requirements internally.
• Future scalability.

Commercial Models

Big Consulting Firms

• Time-and-materials arrangements.
• Transformation projects for several years.
• Governance model large.

Analytics Specialized Firms

• Outcome-based engagement.
• Components of fixed fee.
• Accelerated delivery times.

ROI Assessment Model Over Three Years

Assess:

• Costs for initial implementation.
• Support cost ongoing.
• Increase in productivity.
• Report writing staff savings.
• Improved business performance.

Perceptive Analytics often designs engagements based on outcome, assisting customers to create more compelling business cases for modernization projects.

6. Service Model, Attention, and Project Management Approach

ROI delivery methodology impacts ROI delivery.

Six Comparing Areas

• Access of executives.
• Continuity of team.
• Project governance.
• First-value speed.
• Communication rhythm.
• Rising process.

Microsoft’s guide to BI adoption constantly stresses the importance of governance, enablement, and adoption of users as key factors of success. Companies who strike the balance between governance and user enablement have proven to reach better adoption of analytics. Practical experiences also stress the importance of training and semantic model governance. Adoption issues of enterprise Power BI implementation are usually associated with the ambiguity of definitions, metrics, and lack of user enablement.

Perceptive Analytics pays great attention to adoption, knowledge transfer and building sustainable analytics skills among the client’s employees. Our “analysis in a capsule” approach is aimed at the simplification of decision making through governance of KPIs, automated validation, dashboards and semantic models.

7. Decision Framework: Selecting the Most ROI-Driven BI Modernization Partner

Apply the following 8 steps in assessing BI modernization partners.

• Establish Success Measures

Identify success measures prior to assessing vendors.

• Industry Expertise

Choose those with proven success in your industry.

• Case Studies

Ask for objectives before and after quantitative measures.

• Governance Approach

Evaluate semantic modeling, KPIs standardization, and compliance capability.

• Commercial Models

Consider total value, rather than daily rates.

• Delivery Methodology

Ensure agility and iterative process, with measurable milestones.

• Long-term Service

Consider ownership and support model after implementation.

• Score Partner Suitability

Based on factors such as:

• ROI potential.
• Industry expertise.
• Maturity of governance.
• Methodology for adoption.
• Cost effectiveness.
• Executive involvement.

Conclusion

A BI modernization partner is not always the biggest or cheapest consulting company. This is the one who consistently delivers ROI via quicker insights, better adoption, enhanced governance, and sustainable analytics.

That is precisely what we have done at Perceptive Analytics. Via our dashboard modernization, KPI standardization, data engineering, semantic modeling, and analytics automation services, we enable companies to establish future-proof BI environments that minimize maintenance efforts, enhance decisions, and generate ROI.

For businesses looking for a modernization partner, the next logical step would be an assessment of reporting costs, adoption, governance maturity, and modernization potential.

Next Steps:

• Request a BI Modernization ROI Assessment with Perceptive Analytics
• Download the BI Modernization Partner Evaluation Checklist and compare vendors using the framework outlined above.

Contact Us here