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Build a Reporting and Analytical Insights Strategy

Deliver actionable business insights by creating a business-aligned reporting and analytics strategy.

  • Citizen data science and federated BI/insights teams are commonplace in most organizations.
  • This shift toward federated BI underlines the need to revisit your operating model type, establish roles and responsibilities for the reporting & analytical insights practices, and promote communication and alignment with the business.
  • Data leaders want to understand the broader BI landscape and drive value within the organization.

Our Advice

Critical Insight

Good insights generation should follow human-centered design practices. Understanding the needs and sentiments of all your customers, internal or external, is the key to creating actionable analytics insights. BI teams, whether centralized or federated, must establish and communicate the services they provide, aimed at delivering or supporting outstanding reporting and analytical insights, with their services regularly measured for effectiveness and for driving for continuous improvement.

Impact and Result

  • Drive strategy development by establishing the business context up-front to align the BI team with the most important needs of their business customers and the strategic priorities of the organization.
  • Choose your target operating model style based on your existing BI environment and business requirements.
  • Assess current BI maturity and determine your future-state BI maturity.
  • Revamp or create a BI strategy to update your BI program to make it fit for purpose.

Build a Reporting and Analytical Insights Strategy Research & Tools

1. Build a Reporting and Analytical Insights Strategy Deck – A step-by-step document that walks you through how to properly align with the business and achieve reporting and analytical insights excellence.

This blueprint will help you establish a comprehensive strategy for your BI program by following our four-phase methodology:

  • Understand the existing BI environment and define high-level business requirements.
  • Select your target operating model and its key components.
  • Assess your existing BI practice by determining the BI maturity level and facilitate the planning of your future state BI.
  • Develop essential BI initiatives. Prioritize the initiatives and construct a BI initiative roadmap.
Build a Reporting and Analytical Insights Strategy – Phases 1-3

2. BI User Perception Survey – A structured tool to collect and analyze BI end-user perception and satisfaction.

The BI User Perception Survey tool helps you to collect and analyze BI end-user satisfaction. The feedback from these questions can be used to understand the strengths and weaknesses of the program and identify areas of improvement.

BI User Perception Survey

3. BI Practice Assessment Tool – A structured tool to help you evaluate the gap between your current and target state and build a roadmap to ensure success.

The BI Practice Assessment Tool will help you analyze your organization's BI practice, describe the BI operations and services components, determine the BI maturity level, and systematically develop a plan for your target BI practice.

BI Practice Assessment Tool

4. BI Strategy and Roadmap Presentation Template – A template to help you build a clear and compelling strategy document for stakeholders.

The BI Strategy and Roadmap Presentation Template will document critical strategy results and information.

Present this presentation to business stakeholders and ensure your BI program is endorsed. Business stakeholders can also learn about how the BI strategy empowers them and how they can help in the BI journey.

BI Strategy and Roadmap Presentation Template
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Business Intelligence & Reporting

Put the business back in business intelligence by injecting new BI use cases.

This course makes up part of the Data & BI Certificate.

Academy: Business Intelligence & Reporting | Introduction
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  • Estimated Completion Time: 1.5 hours

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Academy: Business Intelligence & Reporting | Introduction

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Build a Reporting and Analytical Insights Strategy

Deliver actionable business insights by creating a business-aligned reporting and analytics strategy.

Analyst perspective

Deliver actionable business insights by creating a business-aligned reporting and analytics strategy.

Ruyi Sun.

Self-service capabilities are recognized as the one of the top features that contribute to increased usage and adoption of business intelligence (BI) and analytics solutions. Self-service BI tools are becoming prevalent because businesses want more control over their data. This signals a move toward a more federated operating model for the BI team, as well as a focus on customers and service delivery.

As a technology and data leader, your success is contingent on your ability to effectively manage the move toward a federated operating model. To support this change, you need to follow human-centered design practices and deliver the outstanding reporting and analytical insights that your customers demand.

Your reporting and analytical insights strategy must support the organization’s strategy. Your strategy for reporting and analytical insights provides direction and requirements for data accumulation, augmentation, and consumption. This further paves the way for predictive analytics, market/industry intelligence, and social network analytics.

Ruyi Sun
Research Analyst, Data & Analytics
Info-Tech Research Group

Our understanding of the problem

This research is designed for:

  • A CIO or business unit (BU) leader looking to improve reporting and analytical insights, reduce time to information, and embrace fact-based decision-making with analytics, reporting, and BI.
  • Data leaders experiencing poor results from an initial BI tool deployment who are looking to improve the outcome.

This research will help you:

  • Align your reporting and analytical insights strategy with the data strategy and the business’ strategic objectives before you rebuild or invest in BI capabilities.
  • Identify reporting and analytical insights objectives to inform the requirements gathering process.
  • Avoid common pitfalls that derail BI and analytics deployments and lower their adoption.
  • Identify BI gaps prior to deployment and incorporate remedies within your plans.

This research will also assist:

  • Project managers and business analysts assigned to a BI project team to collect and analyze requirements.
  • Business units that have their own BI platforms and would like to partner with IT to take their BI to an enterprise level.

This research will help them:

  • Recruit the right resources for the program.
  • Align BI with corporate vision, mission, goals, and strategic direction.
  • Understand the needs of business partners.
  • Assess BI maturity and plan for the target state.
  • Develop a BI strategy and roadmap.
  • Track the success of the BI initiative.

Executive summary

Situation

Complication

Resolution

Citizen data science and federated BI/insights teams are commonplace in most organizations.

This shift toward federated use underlines the need to revisit your operating model type, establish roles and responsibilities for the reporting and analytical insights practices, and promote communication and alignment with the business.

Data leaders want to understand the broader BI landscape and the value it can drive within the organization.

Challenges that lead to inaccurate insights and a lack of trust in data could derail BI initiatives:

  • Lack of understanding of and alignment with business needs and sentiments.
  • Poor data quality and lack of data governance.
  • Inadequate change management and end-user training.
  • Lack of best practices and standards for your BI processes and outputs.

Drive strategy development by establishing the business context up-front to align the BI team with the most important needs of their business customers and the strategic priorities of the organization.

Choose your target operating model style based on your existing BI environment and business requirements.

Assess current BI maturity and determine your future-state BI maturity.

Revamp or create a BI strategy to update your BI program to make it fit for purpose.

Info-Tech Insight

Good insights generation should follow human-centered design practices. Understanding the needs and sentiments of all your customers, internal or external, is the key to creating actionable analytics insights. BI teams, whether centralized or federated, must establish and communicate the services they provide, aimed at delivering or supporting outstanding reporting and analytical insights, with their services regularly measured for effectiveness and for driving for continuous improvement.

Organizations that successfully grow their BI capabilities are reaping the rewards

Evidence is piling up: If planned well, BI contributes to the organization’s bottom line.

The image contains a screenshot of a graph titled Top Benefits After Using BI to Drive Decisions.

Source: Unsupervised, 2022

The global business intelligence market is estimated at US$33.3 billion in 2024, growing at a compound annual growth rate of 13.16% from 2024 to 2029

(Mordor Intelligence, 2024).

#3 priority for best-in-class companies

Best-in-class organizations differentiate themselves by prioritizing self-service analytics & data discovery, which ranks third in importance for best-in-class organizations, sixth overall, and eighth for laggards (BARC, 2023).

Reporting and analytical insights challenges

Data initiative gaps exist in organizations:

Only 32% of data available to enterprises is put to work. The remaining 68% goes unleveraged (Seagate, 2020).

87% of data science projects never make it into production (VentureBeat, 2019).

Despite ongoing interest in the field of reporting and analytical insights, few organizations manage it well:

67% of employees have access to BI tools, but many aren’t data literate enough to use them. Only 21% of employees are confident in their ability to work with data in the most impactful way (Accenture, 2020).

On average, a company uses 3.8 BI solutions. However, managing multiple BI solutions is a challenge, and 15.4% of respondents didn’t know their organization’s BI adoption rate (Wiiisdom, 2020).

The image contains a Thought Model on Build a Reporting & Analytics Insights Strategy.

Measure the value of this blueprint

Track the success factors throughout the project to keep stakeholders informed.

Success Factor

Potential Metrics

Example Target

Deliver expected business outcomes

  • % of BI projects that meet defined objectives
  • # of BI reworks
  • > 80%
  • Reduction of 10% in BI reworks

Improve operational efficiency

  • $ amount saved after implementing reporting and analytical insights strategy
  • Time saved after implementing reporting and analytical insights strategy
  • > $50K saved
  • > 2 months saved

Increase end-user satisfaction

  • % of increased end-user feedback and satisfaction rates
  • > 20% increase

Deliver BI solutions/ services on time

  • % of BI projects delivered on time
  • % reduction in overrun
  • > 80%
  • > Reduction in project implementation overrun by 20%

Analytics maturity progression

From passive observation to action

The image contains a screenshot of the Analytics Maturity Progression diagram.

There are three key steps to building reporting and analytical insights

The image contains a screenshot of a diagram demonstrating the three key steps to building reporting and analytical insights.

1.1 Identify major business use cases

1.2 Aggregate requirements to determine

2.1 Accumulate data from data sources

2.2 Build your master data

3.1 Augment and integrate data

3.2 Package for each major use case

What are operational reporting and self-service analytics?

Operational Reporting

Operational reporting is focused on tracking operational key performance indicators (KPIs) and providing visibility into the day-to day operations of a business. These reports are typically created using data from transactional systems such as CRM software. These reports are typically used by managers and front-line staff who need visibility into how their team or department is performing against key metrics.

Self-Service Analytics

Self-service analytics refers to the capability of individuals, typically within an organization, to independently access and derive meaningful information and insights from data without relying heavily on specialized technical assistance. It is a facet of modern BI that lets users visualize, analyze, and make decisions based on business data without relying on analysts or IT.

Info-Tech Insight

Your insights can come from self-service analytics or a central BI team, but it's also crucial to notice insights that come directly from the application landscape. Enterprise applications like Salesforce or SAP are rich sources of existing reports. Don't waste time and resources on developing reporting that already exists.

Why has self-service BI become prevalent?

Improved Productivity: Self-service BI tools improve productivity by providing easy access to data, intuitive interfaces, and quick analysis capabilities. Employees can work faster, make informed decisions based on real-time data, and reduce dependency on IT or data analysts for reports, leading to improved efficiency.

Faster, More Informed Decision-Making: Self-service BI enables faster, more informed decision-making through real-time data access, trend identification, and collaboration, expanding decision-making beyond limited individuals or departments.

Cost Reduction: Self-service BI reduces costs by minimizing the need for specialized IT or data analyst resources, eliminating the expense of hiring additional staff or relying on external contractors for data analysis tasks.

Increased Agility and Flexibility: Self-service BI enhances agility by enabling quick data access and analysis, facilitating faster responses to market changes. Customization options ensure employees have timely access to relevant data, fostering flexibility and competitive advantage.

Your business customers want more control over their data

This impacts how teams work with each other.

Organizations use citizen data science to democratize data, bridge skill gaps, speed up decisions, cut costs, and foster innovation. Empowering all employees to be data-savvy unlocks data’s full potential for a competitive edge.

Traditionally, data tasks required skilled experts – data scientists, analysts, and statisticians. They gathered, cleaned, and analyzed data for insights. But this bottlenecked decision-making due to high demand, causing delays and missed chances.

Citizen data science aims to address this limitation by enabling a broader range of individuals, including subject matter experts, business analysts, and other nontechnical professionals, to actively participate in the data analysis process. By providing accessible tools, user-friendly interfaces, and training, organizations can empower employees at all levels to work with data and extract insights relevant to their areas of expertise.

By empowering employees at all levels to become data literate and proficient in data analysis, organizations can unlock the full potential of their data and gain a competitive edge in the market.

The image contains a screenshot of logos that demonstrate software made available for business customers to have control over their data.

When BI and self-service analytics initiatives are poorly executed, they can negatively impact organizations

Potential business impacts when BI and self-service are done badly:

  1. Inaccurate and unreliable insights: If data quality is compromised or data governance processes are not in place, BI and self-service analytics can result in inaccurate or unreliable insights. Decision-makers may base their actions on flawed information, leading to poor strategic decisions, operational inefficiencies, or misguided resource allocation.
  2. Misinterpretation of data: Without proper training or understanding of data analysis techniques, users may misinterpret the data they are working with. This can lead to incorrect conclusions, flawed correlations, or misleading visualizations.
  3. Data silos and fragmentation: BI and self-service analytics initiatives may lead to the creation of data silos and fragmented analysis. Different teams or individuals may use different tools, data sets, or methodologies, resulting in inconsistent and disconnected analysis across the organization.
  4. Overwhelming complexity: BI tools often provide users with a wide range of capabilities and functionalities. Without proper guidance or training, users may feel overwhelmed by the complexity of the tools or struggle to navigate the vast amount of data available.

To mitigate these potential negative impacts, organizations should invest in proper data governance, establish clear guidelines and training programs for users, ensure data quality and security measures are in place, and promote collaboration and standardization in self-service analytics initiatives. Effective communication, support, and monitoring are key to ensuring that BI and self-service analytics initiatives deliver accurate, reliable, and actionable insights for the organization.

Reporting and analytical insights do not operate in isolation

Challenges exist outside your program. Be aware of their impact and interdependency.

Lack of governance

Poor data quality

Data privacy and security risks

Inadequate training

Insufficient policies and procedures for data management, including data quality and metadata management, can lead to data inconsistencies and erode trust in decision-making. Enhance trust and consistency in self-service BI through governance. Clear ownership of data by individuals or departments ensures accountability and consistency, while organization-wide data governance policies drive improved data accuracy, consistency, and security.

Poor data quality in BI can lead to inaccurate insights, wasted resources, lack of trust, inefficient processes, compliance risks, missed opportunities, and poor customer experience. Mitigating these problems requires prioritizing data quality management through data governance, quality controls, validation, and cleansing processes.

Self-service BI tools can increase the risk of data breaches if they are not properly secured. Organizations must apply appropriate safeguards and controls to protect data and ensure compliance with data privacy regulations.

Even though self-service BI provides ease of use, don’t overlook training. Inadequate user training can result in low adoption rates, inaccurate insights and analysis, increased IT workload, and privacy and security problems.

The benefits of your initiatives are not just about technology

Informed Decision-Making

Well-executed BI and self-service analytics empower decision-makers with accurate, timely, and relevant insights. By providing access to real-time data and intuitive analytics tools, organizations can make informed decisions based on data-driven insights. This leads to improved strategic planning, better resource allocation, and increased operational efficiency.

Agility and Responsiveness

BI and self-service analytics enable organizations to quickly respond to changing market conditions and emerging opportunities. With self-service capabilities, business users can independently explore and analyze data, reducing dependency on IT or data teams. This agility allows organizations to adapt their strategies and operations in a timely manner, gaining a competitive edge.

Enhanced Productivity and Efficiency

Self-service analytics empowers business users to access and analyze data without relying on technical experts. This reduces the burden on IT or data teams, freeing up their time for more strategic initiatives. Self-service analytics tools also streamline workflows, automate repetitive tasks, and provide intuitive interfaces, resulting in improved productivity and efficiency across the organization.

Data Democratization and Collaboration

Well-executed BI and self-service analytics initiatives promote data democratization by making data accessible to a broader range of users. This fosters a collaborative environment where individuals from different departments can explore and share insights, leading to cross-functional collaboration, innovation, and a more holistic understanding of the business.

Improved Operational Performance

By leveraging BI and self-service analytics, organizations can identify operational inefficiencies, bottlenecks, and areas for improvement. Data-driven insights enable process optimization, resource allocation refinement, and better operational decision-making. This leads to streamlined operations, reduced costs, and enhanced overall performance.

Insight summary

Overarching insight

Good insights generation should follow human-centered design practices. Understanding the needs and sentiments of all your customers, internal or external, is the key to creating actionable analytics insights. BI teams, whether centralized or federated, must establish and communicate the services they provide, aimed at delivering or supporting outstanding reporting and analytical insights, with their services regularly measured for effectiveness and for driving for continuous improvement.

Insight 1

A business analyst or business intelligence analyst is typically one of the first hires and the most outward-facing member of the team, acting as a bridge between the BI team and other business stakeholders. A successful BI team necessitates investment in business analysis skills.

Insight 2

The BI operations and services components enable programmatic development of outstanding reporting and analytical insights. These components guide organizations’ plan for success. Without proper setup for stakeholder engagement, performance measurement, etc., the BI program is likely to fail.

Insight 3

Assessing current and target states is only the beginning. The real value comes from the interpretation and analysis of the results. Use visualizations of multiple viewpoints and discuss the results in groups to come up with the most effective ideas for your strategy and roadmap.

Tactical insight

Your insights can come from self-service analytics or a central BI team, but it's also crucial to notice insights that come directly from the application landscape. Enterprise applications like Salesforce or SAP are rich sources of existing reports. Don't waste time and resources on developing reporting that already exists.

Tactical insight

The BI team does not typically own the responsibility for solving problems in data management disciplines, but it's important to understand their interdependence and impact on the BI program. For example, if your data is of poor quality, the reports will not offer valuable insights even if they are well constructed.

Blueprint deliverables

Each step of this blueprint is accompanied by supporting deliverables to help you accomplish your goals:

The image contains a screenshot of the BI User Perception Survey. The image contains a screenshot of the BI Practice Assessment Tool.

BI User Perception Survey

Collect and analyze BI end-user perception and satisfaction.

BI Practice Assessment Tool

Evaluate the current and target performance levels for your organization’s BI practice. Populate your Gantt chart to visually represent your key initiative plan.

Key deliverable:

BI Strategy and Roadmap Presentation Template

Present this presentation to ensure the business is aligned with the formulated strategy and roadmap and to generate interest in your BI program.

The image contains three screenshots of the BI Strategy and Roadmap Presentation Template.

Info-Tech’s methodology for building a reporting and analytical insights strategy

1. Align Organizational Strategy With Reporting & Analytical Insights Strategy

2. Choose Your Operating Model Style

3. Evaluate BI Practice Maturity

4. Create a BI Strategy and Roadmap

Phase Steps

  1. Establish the business context
  2. Assess the existing BI environment
  3. Undergo high-level BI services requirements gathering
  1. Select your BI operating model
  2. Define BI operations and services key components
  3. Understand the other associated data disciplines
  1. Assess your current BI maturity
  2. Envision the BI future state
  1. Construct a BI initiative roadmap
  2. Create a continuous improvement plan for BI

Phase Outcomes

  • Clearly articulated high-level mission, vision, and key drivers from the business, as well as objectives related to BI
  • Documentation regarding your organization’s BI usage, user perception, and outputs
  • Consolidated list of high-level business requirements, existing and desired
  • Selection of target operating model type
  • Aligned BI operations and services key components description
  • A current-state assessment highlighting alignment and discrepancies
  • A defined future state to provide a benchmark for your BI program
  • Identified gaps between the future and current states and recommendations to close gaps
  • Consolidated BI improvement initiatives
  • BI initiative roadmap
  • Identified supplementary program that will facilitate the smooth execution of roadmapped initiatives

Info-Tech offers various levels of support to best suit your needs

DIY Toolkit

Our team has already made this critical project a priority, and we have the time and capability, but some guidance along the way would be helpful.

Guided Implementation

Our team knows that we need to fix a process, but we need assistance to determine where to focus. Some check-ins along the way would help keep us on track.

Workshop

We need to hit the ground running and get this project kicked off immediately. Our team has the ability to take this over once we get a framework and strategy in place.

Consulting

Our team does not have the time or the knowledge to take this project on. We need assistance through the entirety of this project.”

Diagnostics and consistent frameworks used throughout all four options

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Deliver actionable business insights by creating a business-aligned reporting and analytics strategy.

About Info-Tech

Info-Tech Research Group is the world’s fastest-growing information technology research and advisory company, proudly serving over 30,000 IT professionals.

We produce unbiased and highly relevant research to help CIOs and IT leaders make strategic, timely, and well-informed decisions. We partner closely with IT teams to provide everything they need, from actionable tools to analyst guidance, ensuring they deliver measurable results for their organizations.

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Average Days Saved

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What Is a Blueprint?

A blueprint is designed to be a roadmap, containing a methodology and the tools and templates you need to solve your IT problems.

Each blueprint can be accompanied by a Guided Implementation that provides you access to our world-class analysts to help you get through the project.

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Guided Implementation 1: Align organizational strategy with reporting & analytical insights strategy
  • Call 1: Review business context, identifying organizational drivers, challenges, pain points, enablers, and inhibitors.
  • Call 2: Analyze user sentiment feedback.
  • Call 3: Review critical BI artifacts and understand the usage of your existing BI.
  • Call 4: Discuss high-level business requirements gathering.

Guided Implementation 2: Choose your operating model style
  • Call 1: Review different operating model types and select target operating model type.
  • Call 2: Discuss BI operations and services key components.

Guided Implementation 3: Evaluate BI practice maturity
  • Call 1: Measure the BI current-state maturity.
  • Call 2: Determine the BI target-state maturity and perform a gap analysis.

Guided Implementation 4: Create a BI strategy and roadmap
  • Call 1: Discuss initiative building.
  • Call 2: Review completed roadmap and next steps.

Author

Ruyi Sun

Contributors

  • Albert Hui, Principal, DataEconomist
  • Cameran Hetrick, Senior Director of Data Science & Analytics, thredUP
  • David Farrar, Director – Marketing Planning & Operations, Ricoh Canada Inc.
  • Emilie Harrington, Manager of Analytics Operations Development, Lowe’s
  • Sharon Blanton, VP and CIO, The College of New Jersey
  • Raul Vomisescu, Independent Consultant

Related Content: Business Intelligence Strategy

Search Code: 79665
Last Revised: May 28, 2024

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