Build a Reporting and Analytics Strategy

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

Terminology

As the reporting and analytics space matured over the last decade, software suppliers used different terminology to differentiate their products from others’. This caused a great deal of confusion within the business communities.

Following are two definitions of the term Business Intelligence:

Business intelligence (BI) leverages software and services to transform data into actionable insights that inform an organization’s strategic and tactical business decisions. BI tools access and analyze data sets and present analytical findings in reports, summaries, dashboards, graphs, charts, and maps to provide users with detailed intelligence about the state of the business.

The term business intelligence often also refers to a range of tools that provide quick, easy-to-digest access to insights about an organization's current state, based on available data.

CIO Magazine

Business intelligence (BI) comprises the strategies and technologies used by enterprises for the data analysis of business information. BI technologies provide historical, current, and predictive views of business operations.

Common functions of business intelligence technologies include reporting, online analytical processing, analytics, data mining, process mining, complex event processing, business performance management, benchmarking, text mining, predictive analytics, and prescriptive analytics.

Wikipedia

This blueprint will use the terms “BI,” “BI and Analytics,” and “Reporting and Analytics” interchangeably in different contexts, but always in compliance to the above definitions.

ANALYST PERSPECTIVE

A fresh analytics & reporting strategy enables new BI opportunities.

We need data to inform the business of past and current performance and to support strategic decisions. But we can also drown in a flood of data. Without a clear strategy for business intelligence, a promising new solution will produce only noise.

BI and Analytics teams must provide the right quantitative and qualitative insights for the business to base their decisions on.

Your Business Intelligence and Analytics strategy must support the organization’s strategy. Your strategy for BI & Analytics provides direction and requirements for data warehousing and data integration, and further paves the way for predictive analytics, big data analytics, market/industry intelligence, and social network analytics.

Dirk Coetsee,

Director, Data and 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 analytics, reduce time to information, and embrace fact-based decision making with analytics, reporting, and business intelligence (BI).
• Application Directors experiencing poor results from an initial BI tool deployment who are looking to improve the outcome.

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 You:

• Align your reporting and analytics strategy with the business’ strategic objectives before you rebuild or buy your Business Intelligence platform.
• Identify reporting and analytics objectives to inform the data warehouse and integration requirements gathering process.
• Avoid common pitfalls that derail BI and analytic deployments and lower their adoption.
• Identify Business Intelligence gaps prior to deployment and incorporate remedies within your plans.

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 target state.
• Develop a BI strategy and roadmap.
• Track the success of the BI initiative.

Executive summary

Situation:

BI drives a new reality. Uber is the world’s largest taxi company and they own no vehicles; Alibaba is the world’s most valuable retailer and they have no inventory; Airbnb is the world’s largest accommodation provider and they own no real estate. How did they disrupt their markets and get past business entry barriers? A deep understanding of their market through impeccable business intelligence!

Complication:

• In respect to BI matureness, you can’t expect the whole organization to be at the same place at the same time. Your BI strategy needs to recognize this and should strive to align rather than dictate.
• Technology is just one aspect of your BI and Analytics strategy and is not a quick solution or a guarantee for long term success.

Resolution:

• Drive strategy development by establishing the business context upfront in order to align business intelligence providers with the most important needs of their BI consumers and the strategic priorities of the organization.
• Revamp or create a BI strategy to update your BI program to make it fit for purpose.
• Understand your existing BI baggage – e.g. your existing BI program, the artifacts generated from the program, and the users it supports. Those will inform the creation of the strategy and roadmap.
• Assess current BI maturity and determine your future state BI maturity.
• BI needs governance to ensure consistent planning, communication, and execution of the BI strategy.
• Create a network of BI ambassadors across the organization to promote BI.
• Plan for the future to ensure that required data will be available when the organization needs it.

Info-Tech Insight

1. Put the “B” back in BI. Don’t have IT doing BI for IT’s sake; ensure the voice and needs of the business are the primary drivers of your strategy.
2. The BI strategy drives data warehouse and integration strategies and the data needs to support business decisions.
3. Go beyond the platform. The solution to better BI often lies in improving the BI practice, not acquiring the latest and greatest tool.

Metrics to track BI & Analytical program progress

Goals for BI:

• Understand business context and needs. Identify business processes that can leverage BI.
• Define the Reporting & Analytics Roadmap. Develop data initiatives, and create a strategy and roadmap for Business Intelligence.
• Continuous improvements. Your BI program is evolving and improving over time. The program should allow you to have faster, better, and more comprehensive information.

Info-Tech’s Suggested Metrics for Tracking the BI Program

Intangible Metrics:

Tap into the results of Info-Tech’s CIO Business Vision diagnostic to monitor the changes in business-user satisfaction as you implement the initiatives in your BI improvement roadmap.

Your Enterprise BI and Analytics Strategy is driven by your organization’s Vision and Corporate Strategy

Formulating an Enterprise Reporting and Analytics Strategy requires the business vision and strategies to first be substantiated. Any optimization to the Data Warehouse, Integration and Source layer is in turn driven by the Enterprise Reporting and Analytics Strategy

The current state of your Integration and Warehouse platforms determine what data can be utilized for BI and Analytics

Where we are, and how we got here

How we got here

• In the beginning was BI 1.0. Business intelligence began as an IT-driven centralized solution that was highly governed. Business users were typically the consumers of reports and dashboards created by IT, an analytics-trained minority, upon request.
• In the last five to ten years, we have seen a fundamental shift in the business intelligence and analytics market, moving away from such large-scale, centralized IT-driven solutions focused on basic reporting and administration, towards more advanced user-friendly data discovery and visualization platforms. This has come to be known as BI 2.0.
• Many incumbent market leaders were disrupted by the demand for more user-friendly business intelligence solutions, allowing “pure-play” BI software vendors to carve out a niche and rapidly expand into more enterprise environments.
• BI-on-the-cloud has established itself as a solid alternative to in-house implementation and operation.

Where we are now

• BI 3.0 has arrived. This involves the democratization of data and analytics and a predominantly app-centric approach to BI, identifiable by an anywhere, anytime, and device-or-platform-independent collaborative methodology. Social workgroups and self-guided content creation, delivery, analysis, and management is prominent.
• Where the need for reporting and dashboards remains, we’re seeing data discovery platforms fulfilling the needs of non-technical business users by providing easy-to-use interactive solutions to increase adoption across enterprises.
• With more end users demanding access to data and the tools to extract business insights, IT is looking to meet these needs while continuing to maintain governance and administration over a much larger base of users. The race for governed data discovery is heated and will be a market differentiator.
• The next kid on the block is Artificial Intelligence that put further demands on data quality and availability.

RICOH Canada used this methodology to develop their BI strategy in consultation with their business stakeholders

CASE STUDY

Industry: Manufacturing and Retail

Source: RICOH

Ricoh Canada transforms the way people work with breakthrough technologies that help businesses innovate and grow. Its focus has always been to envision what the future will look like so that it can help its customers prepare for success. Ricoh empowers digital workplaces with a broad portfolio of services, solutions, and technologies – helping customers remove obstacles to sustained growth by optimizing the flow of information and automating antiquated processes to increase workplace productivity. In their commitment towards a customer-centric approach, Ricoh Canada recognized that BI and analytics can be used to inform business leaders in making strategic decisions.

Enterprise BI and analytics Initiative

Ricoh Canada enrolled in the ITRG Reporting & Analytics strategy workshop with the aim to create a BI strategy that will allow the business to harvest it strengths and build for the future. The workshop acted as a forum for the different business units to communicate, share ideas, and hear from each other what their pains are and what should be done to provide a full customer 360 view.

Results

“This workshop allowed us to collectively identify the various stakeholders and their unique requirements. This is a key factor in the development of an effective BI Analytics tool.” David Farrar

The Customer 360 Initiative included the following components

Improve BI Adoption Rates

Sisense

Reasons for low BI adoption

• Employees that never used BI tools are slow to adopt new technology.
• Lack of trust in data leads to lack of trust in the insights.
• Complex data structures deter usage due to long learning curves and contained nuances.
• Difficult to translate business requirements into tool linguistics due to lack of training or technical ineptness.
• Business has not taken ownership of data, which affects access to data.

How to foster BI adoption

• Senior management proclaim data as a strategic asset and involved in the promotion of BI
• Role Requirement that any business decision should be backed up by analytics
• Communication of internal BI use case studies and successes
• Exceptional data lineage to act as proof for the numbers
• A Business Data glossary with clearly defined business terms. Use the Business Data Glossary in conjunction with data lineage and semantic layers to ensure that businesses are clearly defined and traced to sources.
• Training in business to take ownership of data from inception to analytics.

Why bother with analytics?

In today’s ever-changing and global environment, organizations of every size need to effectively leverage their data assets to facilitate three key business drivers: customer intimacy, product/service innovation, and operational excellence. Plus, they need to manage their operational risk efficiently.

Investing in a comprehensive business intelligence strategy allows for a multidimensional view of your organization’s data assets that can be operationalized to create a competitive edge:

Historical Data

Without a BI strategy, creating meaningful reports for business users that highlight trends in past performance and draw relationships between different data sources becomes a more complex task. Also, the ever growing need to identify and assess risks in new ways is driving many companies to BI.

Data Democracy

The core purpose of BI is to provide the right data, to the right users, at the right time, and in a format that is easily consumable and actionable. In developing a BI strategy, remember the driver for managed cross-functional access to data assets and features such as interactive dashboards, mobile BI, and self-service BI.

Predictive and Big Data Analytics

As the volume, variety, and velocity of data increases rapidly, businesses will need a strategy to outline how they plan to consume the new data in a manner that does not overwhelm their current capabilities and aligns with their desired future state. This same strategy further provides a foundation upon which organizations can transition from ad hoc reporting to using data assets in a codified BI platform for decision support.

Business intelligence serves as the layer that translates data, information, and organizational knowledge into insights

As executive decision making shifts to more fact-based, data-driven thinking, there is an urgent need for data assets to be organized and presented in a manner that enables immediate action.

Typically, business decisions are based on a mix of intuition, opinion, emotion, organizational culture, and data. Though business users may be aware of its potential value in driving operational change, data is often viewed as inaccessible.

Business intelligence bridges the gap between an organization’s data assets and consumable information that facilitates insight generation and informed decision making.

Most organizations realize that they need a BI strategy; it’s no longer a nice-to-have, it’s a must-have.

– Albert Hui, Principal, Data Economist

Business intelligence and business analytics: what is the difference and should you care

Ask 100 people and you will get 100 answers. We like the prevailing view that BI looks at today and backward for improving who we are, while BA is forward-looking to support change decisions.

• Business intelligence is concerned with looking at present and historical data.
• Use this data to create reports/dashboards to inform a wide variety of information consumers of the past and current state of affairs.
• Almost all organizations, regardless of size and maturity, use some level of BI even if it’s just very basic reporting.
• Business analytics, on the other hand, is a forward-facing use of data, concerned with the present to the future.
• Analytics uses data to both describe the present, and more importantly, predict the future, enabling strategic business decisions.
• Although adoption is rapidly increasing, many organizations still do not utilize any advanced analytics in their environment.

However, establishing a strong business intelligence program is a necessary precursor to an organization’s development of its business analytics capabilities.

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.

It’s expected that there will be nearly 45 billion connected devices and a 42% increase in data volume each year posing a high business opportunity for the BI market (BERoE, 2020).

The global business intelligence market size to grow from US$23.1 billion in 2020 to US$33.3 billion by 2025, at a compound annual growth rate (CAGR) of 7.6% (Global News Wire, 2020)

In the coming years, 69% of companies plan on increasing their cloud business intelligence usage (BARC Research and Eckerson Group Study, 2017).

Call to Action

Small organizations of up to 100 employees had the highest rate of business intelligence penetration last year (Forbes, 2018).

Source: IBM Business Value, 2015

For the New England Patriots, establishing a greater level of customer intimacy was driven by a tactical analytics initiative

CASE STUDY

Industry: Professional Sports

Source Target Marketing

Problem

Despite continued success as a franchise with a loyal fan base, the New England Patriots experienced one of their lowest season ticket renewal rates in over a decade for the 2009 season. Given the numerous email addresses that potential and current season-ticket holders used to engage with the organization, it was difficult for Kraft Sports Group to define how to effectively reach customers.

Turning to a Tactical Analytics Approach

Kraft Sports Group turned to the customer data that it had been collecting since 2007 and chose to leverage analytics in order to glean insight into season ticket holder behavior. By monitoring and reporting on customer activity online and in attendance at games, Kraft Sports Group was able to establish that customer engagement improved when communication from the organization was specifically tailored to customer preferences and historical behavior.

Results

By operationalizing their data assets with the help of analytics, the Patriots were able to achieve a record 97% renewal rate for the 2010 season. KSG was able to take their customer engagement to the next level and proactively look for signs of attrition in season-ticket renewals.

We're very analytically focused and I consider us to be the voice of the customer within the organization… Ultimately, we should know when renewal might not happen and be able to market and communicate to change that behavior.

– Jessica Gelman,

VP Customer Marketing and Strategy, Kraft Sports Group

A large percentage of all BI projects fail to meet the organization’s needs; avoid falling victim to common pitfalls

Tool Usage Pitfalls

• Business units are overwhelmed with the amount and type of data presented.
• Poor data quality erodes trust, resulting in a decline in usage.
• Analysis performed for the sake of analysis and doesn’t focus on obtaining relevant business-driven insights.

Selection Pitfalls

• Inadequate requirements gathering.
• No business involvement in the selection process.
• User experience is not considered.
• Focus is on license fees and not total cost.

Implementation Pitfalls

• Absence of upfront planning
• Lack of change management to facilitate adoption of the new platform
• No quick wins that establish the value of the project early on
• Inadequate initial or ongoing training

Strategic Pitfalls

• Poor alignment of BI goals with organization goals
• Absence of CSFs/KPIs that can measure the qualitative and quantitative success of the project
• No executive support during or after the project

BI pitfalls are lurking around every corner, but a comprehensive strategy drafted upfront can help your organization overcome these obstacles. Info-Tech’s approach to BI has involvement from the business units built right into the process from the start and it equips IT to interact with key stakeholders early and often.

Only 62% of Big Data and AI projects in 2019 provided measurable results.

Source: NewVantage Partners LLC

Business and IT have different priorities for a BI tool

Business executives look for:

• Ease of use
• Speed and agility
• Clear and concise information
• Sustainability

IT professionals are concerned about:

• Solid security
• Access controls on data
• Compliance with regulations
• Ease of integration

Info-Tech Insight

Combining these priorities will lead to better tool selection and more synergy.

Elizabeth Mazenko

The top-down BI Opportunity Analysis is a tool for senior executives to discover where Business Intelligence can provide value

Example: Uncover BI opportunities with an opportunity analysis

Williams (2016)

Bridge the gap between business drivers and business intelligence features with a three-tiered framework

Info-Tech’s approach to formulating a fit-for-purpose BI strategy is focused on making the link between factors that are the most important to the business users and the ways that BI providers can enable those consumers.

Drivers to Establish Competitive Advantage

• Operational Excellence
• Client Intimacy
• Innovation

BI and Analytics Spectrum

• Strategic Analytics
• Tactical Analytics
• Operational Analytics

Info-Tech’s BI Patterns

• Delivery
• User Experience
• Deep Analytics
• Supporting