Off-Field Data Reference Architecture Guide

Make the case for an off-field data reference architecture.

Table of Contents

Off-Field Data Reference Architecture Guide

Make the case for an off-field data reference architecture.

EXECUTIVE BRIEF

Analyst Perspective

Centralize your fan data with the right off-field data architecture.

Sports entertainment organizations are struggling to simplify their siloed data to create the 360-degree view of the fan and effectively use it to improve their business. Thirty percent of sports organizations report that only one person has the appropriate knowledge of data and 25% say that no one has any expertise in the area (Fan Engagement Consultancy, 2021).

Sports entertainment organizations are new to collecting fan data to meet business goals, where 61% of all sports entertainment organizations do not use data for their overall strategy. Additionally, only 51% of teams collect data in a centralized place, meaning that many teams still work with separate data sources, which limits their marketing abilities to understand fans (Fan Engagement Consultancy, 2021).

Through the right off-field data, architecture teams can enable their business strategies, where they can discover data-driven digital opportunities and relieve the pains of monetizing their fan data while maximizing revenues, sponsorships, enhancing fan engagement, and guiding fan behaviors.

Elizabeth Silva Research Specialist, Sports Entertainment Industry Info-Tech Research Group

Executive Summary

Info-Tech Overarching Insight

An effective off-field data architecture can create data-driven digital opportunities and new insights. Equipped with the right data strategy, any sports entertainment organization can create a sustainable sports business and improve fan engagement and sponsorship relations, all while achieving business goals.

The meaning of off-field vs. on-field

Off-Field vs. On-Field Analytics

An off-field data architecture and fan-driven data strategy is important

Use fan data to differentiate and remain competitive in today’s digital economy

An off-field data architecture needs strategic drivers

Your fan-driven data strategy needs to align with your organizational strategy, such as a digital business strategy.

Privacy, Risk & Compliance As a sports organization, you are more than likely operating as a privately held organization that is owned by a larger organization/holding company and mandated to meet certain regulatory requirements from the league your team belongs to and the area you are located in. Risk mitigation is also another driver for formalizing or optimizing your current data architecture. Your current practices and environment may be outdated, leading to potential exposure to risk.		Fan Engagement/Service Excellence As a sports organization, your current focus is on improving fan/customer experience, engagement, and striving for service excellence, whether by offering highly tailored products or services, upselling, cross-selling, sending targeted communication, or building fan/customer loyalty. Stakeholders within the sports industry are fans, internal customers, sport spectators, sponsors/partners, media participants, leagues/clubs, host community, and governing bodies.
Operational Excellence As a sports organization, you’re focused on optimizing your operational excellence and efficiency to ensure you are delivering high-quality products or services in the most cost-effective manner. This may mean your focus is on optimizing your ordering, production, and fulfillment processes for the venue. Or you may be working on the efficiency of your operations, making them leaner, reducing waste, and optimizing resource utilization, all of which can contribute to lower costs and higher profit margins.		Product & Service Innovations To maintain or establish your competitive edge, your sports organization is looking to become innovative in the product(s) and service(s) that you offer. As an organization, you’re seeking to differentiate through product or service innovation. You’re inventing and adapting to keep pace and/or get ahead of changing fan and stakeholder preferences by understanding purchasing habits, consumption, behaviors, more varied and larger data sets, IoT, and other disruptive forces.

Many opportunities are revealed for sports entertainment organizations once they start using data

The opportunities data can help your sports entertainment organization leverage:

HIGHER QUALITY SERVICES The strategic use of data can enable sports entertainment organizations to provide higher quality services.	FAN INTELLIGENCE The strategic use of data can provide sports entertainment organizations with a wealth of knowledge on fans and you will be able to not just know the fan behaviors but also guide and predict what they may be to enhance marketing, fan engagement, and revenues.	FAN-DRIVEN DATA DECISIONS The insights that can be found through the strategic use of data can provide intuitive information around fans and sponsorships so fan-driven data decisions can be made.
IMPROVE SPONSORSHIP RELATIONS Make better evidence-informed decisions and improve understanding around the impact of sponsorships and fan engagement, so funds and sponsorship can be directed where they are most likely to deliver the best results.	DATA MONETIZATION Create actionable decisions around your fan data so you will be able to monetize it.	BECOME A PROVEN BUSINESS PARTNER If you have any business strategy, such as a digital business strategy, in place where data and integration is highly important, you will be able to effectively align with the business and be a proven business partner rather than just a business enabler.

Align and enable your organizations goals cascade with an off-field data architecture

An off-field data architecture is what makes an organization’s goals actionable. Ensuring that your off-field data architecture will have the right components to support organizational goals will allow for better buy-in from business executives.

Info-Tech’s methodology for an off-field data architecture

Blueprint Deliverable

Key deliverable:

Off-Field Data Reference Architecture Business Case Presentation Template
Input the activities and outputs of this blueprint into the Presentation Template to easily present your business case to executives.

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

Guided Implementation

A Guided Implementation (GI) is a series of calls with an Info-Tech analyst to help implement our best practices in your organization.

A typical GI is 8 to 12 calls over the course of 4 to 6 months.

What does a typical GI on this topic look like?

Off-Field Data Reference Architecture Guide

Phase 1

Define a Working Group and the Current State

This phase will walk you through the following activities:

• Identify and assemble key stakeholders
• Document your current data management maturity
• Assess how well information supports business capabilities

This phase involves the following participants:

• CIO
• CEO
• CFO
• CMO
• CDO
• Other stakeholders as appropriate

Step 1.1

Build an Accurate Depiction of the Business

Activities

• 1.1.1 Identify and Assemble Key Stakeholders

This step will walk you through the following activities:

• Identify and assemble key stakeholders

This step involves the following participants:

• CIO
• CEO
• CFO
• CMO
• CDO
• Other stakeholders as appropriate

Outcomes of this step

• Establish a working group to provide direction and clarity on creating a business case for an off-field data architecture
• Understand the risks associated with this initiative

Leverage your working group

Info-Tech Insight

Your head of marketing should be a key stakeholder within your working group as the marketing team are those who will execute any of the insights found through data and analytics with their creative marketing abilities.

1.1.1 Identify and assemble key stakeholders

Input: List of potential stakeholders, Level of influence and support the various stakeholders may have on this initiative

Output: Key stakeholders for this initiative

Materials: Whiteboard, Pen and paper, Presentation Template

Participants: CIO, CEO, COO, CFO, CMO, CDO

1. As a group, create a working group of stakeholders that should be involved in creating the business case for an off-field data architecture.
2. Aim to create a working group that can help inform your organization’s decision on whether to pursue this initiative now or wait.
3. Evaluate and discuss each potential stakeholder on the list based on:
   1. Influence: To what degree can this stakeholder impact the progress of this initiative?
   2. Involvement: How involved is the stakeholder in this initiative already?
   3. Support: How supportive is this person of this initiative?
4. Once the group has decided who the working group will be, document the key stakeholders for this initiative in the appendix of the Presentation Template.

Download the Presentation Template

The importance of fan data has shifted upwards

• The COVID-19 pandemic has shifted the sports entertainment industry’s focus to look at damage control and the potential losses that can be faced in another sports shutdown; analyzing fans and other means of engagement is crucial.
• Sports entertainment organizations that have invested in and developed digital platforms have fared much better in keeping close to their fans and riding out the COVID-19 crisis better than average.
• "COVID-19 could lead to a 60% increase in the amount of content fans watch, where we are seeing higher engagement on social media, meaning people need and want to consume more content.” – Ramón Amich, Managing Director Spain & Portugal, Nielsen Sports, via N3xt Sports, 2020.
• Going digital and satisfying fans is only one part of the strategy. Data is another part of the strategy, where without the right data, you will not be able to understand your fans correctly. Having the right data will carry your organization’s decision making through any global crisis that your organization may be affected by, to ensure success and valuable relationships with fans.
• Effective data can be used as the oil to a sports entertainment organization by fueling its innovation, transformation, and strategic opportunities.

Info-Tech Insight

Using data to understand the current market is critical for determining who your at-home and live game watchers are. Marketing correctly to the right market is highly important for success.

Developments in business and technology are changing how sports organizations use and manage data

Consider the various IT risks that may come with an off-field data architecture

Overarching IT Risks Business intelligence is high in importance but low in effectiveness within the sports entertainment sector, showcasing the importance but struggle of success in this business function. Data architecture is low in importance but high in effectiveness within the sports entertainment sector, demonstrating the lack of value the industry sees for this business function.
(Source: Info-Tech’s Management and Governance Benchmarking Report for Sports Entertainment.)

Consider the various IT risks that may come with an off-field data architecture

Overarching IT Risks Continued Data quality is two ranks below average in the sports entertainment industry when benchmarked to all other industries. This indicates that IT stakeholders do not find data quality to be as important. IT stakeholders should be thinking differently about this core service to meet market demand and be competitive, as relying on team performance is not sustainable. The importance of analytical capability and reports is also low, even though analytics is typically the main driver of business growth, actionable insights, and success. IT stakeholders need to be thinking differently about this space.

(Source: Info-Tech’s IT Stakeholder Satisfaction Benchmarking Report for Sports Entertainment.)

Step 1.2

Information Assessment

Activities

• 1.2.1 Document Your Current Data Management Maturity
• 1.2.2 Assess How Well Information Supports Business Capabilities

This step will walk you through the following activities:

• Assess how well information supports capabilities
• Evaluate accessibility to data for key capabilities
• Determine what areas are not being supported by data
• Document your current data management maturity

This step involves the following participants:

• Stakeholder working group
• Other key business stakeholders as appropriate

Outcomes of this step

• Identification of capability data support
• Comprehend your current data management maturity

Define a Working Group and the Current State

Determine and document the business context for an off-field data architecture

Develop an understanding of the strategic plans, goals, and current state of the business; you may have already completed a goals cascade, business strategy, or data maturity assessment that you can leverage.

If you do not already have supporting documentation, leverage Info-Tech resources to get this done:

The data quality and culture diagnostics help identify information gaps

Assessing how well information supports capabilities is nearly impossible to perform without an honest and thorough understanding of end-user sentiment toward data, reporting, and analytics. Develop data-driven insights to help you decide which business capabilities require new or improved reporting and analytics and find opportunities to improve business processes, and by extension, enable the capabilities of the business. The Data Quality and Culture Diagnostics will help you: Assess data quality and reporting satisfaction at a glance. Evaluate data quality across nine dimensions of quality. Evaluate reporting across ten dimensions of satisfaction. Determine which areas are the most critical. Determine effectiveness of analytics tools. Determine whether the organization perceives data to be an asset.

1.2.1 Document your data business context

1-2 hours

Input: Business context, Data Quality diagnostic, Data Culture diagnostic

Output: The current data management maturity of the organization

Materials: Completed diagnostics, Presentation Template

Participants: Stakeholder working group

1. Gather your working group to discuss the results of the Data Quality and Data Culture diagnostics.
2. Discuss and determine what your current data management maturity is, based off business context and the diagnostics completed.
3. Document the results of the data management maturity in the Presentation Template.

Info-Tech Insight

The path to "one view" of the fan is a systematic journey aligned with the level of data maturity and fluency.

Download the Presentation Template

The sports entertainment business capability map

Business Capability Map Defined…

In business architecture, the primary view of an organization is known as a business capability map.

A business capability defines what a business does to enable value creation, rather than how. Business capabilities:

• Represent stable business functions.
• Are unique and independent of each other.
• Typically will have a defined business outcome.

A business capability map provides details that help the business architecture practitioner direct attention to a specific area of the business for further assessment.

Download the Full Business Capability Map for Sports Entertainment

Information Assessment

Assess the availability and quality of data in providing information as a business asset. Information is central to every sport entertainment organization’s success and ability to realize its goals. Too often organizations experience the following pains: Duplicated or conflicting data residing in disparate databases. Inadequate controls or edits on data. Manual rekeying of data into multiple systems. Inability to provide executives with reliable and easily accessible information for decision making. Inability to provide sponsors with reliable data for transparency and measurability to their sponsorship efforts. Unable to use data to create better market targeting. Inability of business units to assume “ownership” of data. Inability to develop insights through data and analytics to improve fan hyper-personalization, experience, and engagement. These organizations are driven by the desire to effectively manage existing business processes while recognizing the need for a faster ability to share data, information, and insight across multiple systems and business units to support increasing demands for more rapid response. A primary goal of a strategy is to provide a framework that enables information to be viewed as a critical business asset, across organizational boundaries, and accessed as seamlessly as possible. Through effective strategy design, IT can provide integration of data across business units by performing an analysis of how well the organizational capabilities are supported by information. Specifically, IT should analyze and assess data on the basis of quality, integrity, and ownership and on the presence of an effective data governance framework.	Assess how well existing information supports capabilities
		NONE: Data is unavailable, unreliable, duplicated, or not of sufficient detail
		LOW: Data is available but not subject to adequate integrity or quality controls. Data ownership is undefined.
		MEDIUM: LOW + Data is available but not fully automated. Data ownership is mostly defined.
		HIGH: MEDIUM + Data is available, of high quality, fully automated, and has clear ownership. Figure above: Information Assessment Legend

Information support of key capabilities

Note: Illustrative Example. To edit and customize this visual go to the appendix of the Presentation Template.

1.2.2 Assess how well information supports business capabilities

1-2 hours

Input: Business context, Sports entertainment business capability map

Output: Clear understanding on how well the existing information and data supports business capabilities

Materials: Sports entertainment business capability map, Presentation Template

Participants: Stakeholder working group, Other key business stakeholders as appropriate

1. Gather your working group to discuss the availability and quality of current data to provide information as a business asset.
2. Analyze and assess data on the basis of quality, integrity, and ownership and on the presence of an effective data governance framework.
3. Use the following color scheme in assessment of your data:
   • None = Red: Data is unavailable, unreliable, duplicated, or not of sufficient detail.
   • Low = Yellow: Data is available but not subject to adequate integrity or quality controls. Data ownership is undefined.
   • Medium = Light Green: Low + data is available but not fully automated. Data ownership is mostly defined.
   • High = Dark Green: Medium + data is available, of high quality, and fully automated with clear ownership.
     • Use the eyedropper tool for easy completion of this activity.
4. Use the output of this activity to build your case on why you need an off-field data architecture by providing a visual of where data lacks in supporting the business.

Download the Presentation Template

Off-Field Data Reference Architecture Guide

Phase 2

Discover Data-Driven Digital Opportunities

This phase will walk you through the following activities:

• Understand what an off-field data architecture is.
• Discover what data-driven digital opportunities exist for value creation.
• Read through conceptual and logical data model examples for value creation.

This phase involves the following participants:

• CIO
• CEO
• CFO
• CMO
• CDO
• Other stakeholders as appropriate

Step 2.1

Off-Field Data Reference Architecture

This step involves the following participants:

• CIO
• CEO
• CFO
• CMO
• CDO
• Other stakeholders as appropriate

Outcomes of this step

• Understand what an off-field data architecture is.
• Discover what data-driven digital opportunities exist for value creation.
• Read through conceptual and logical data model examples for value creation.

Discover Data-Driven Digital Opportunities

Together, data architecture and data modeling fill in the gaps between business goals and technology

Data Architecture Data architecture is the set of rules, policies, standards, and models that govern and define the type of data collected and how it is used, stored, managed, and integrated within the organization and its database systems. In general, the primary objective of data architecture is the standardization of data for the benefit of the organization.	Data Modeling Data modeling is a fast-paced activity responsible for the logical and physical data models as part of sprints. Conceptual data models are high-level models that present abstract business concepts in an easy, consumable way that tells the story of the organization. Logical data models are models that describe the data with as much detail as possible. (Source: Pediaa, 2019)
Info-Tech’s Traditional Data Architecture Framework Visit the Big Data Architecture and Implementation Plan blueprint to learn more	Info-Tech’s Data Modeling Framework Visit the Create and Manage Enterprise Data Models blueprint to learn more

Use transactional & analytics data to support the business

Data Architecture Supports applications that drive the ongoing operations of an organization. Activities could include sales, billing, reservations, venue management, and administration. Transactional databases are typically designed for high responsiveness and integrity under all operational conditions.

Architecture

Analytics Data Is accumulated from transactional data sources to provide business intelligence and decision support capabilities. Analytical data repositories can take the form of a data warehouse, data lakes, data marts, and other specialized forms, optimized for efficiency across massive volumes of accumulated data.

“To maximize insights, key stakeholders must better understand who their fans are with a 360-degree view to their demographics, the brands they like, the products they buy, and the media they consume.

When developing strategies for sponsorship, advertising, amenities, event format, venue design, or loyalty programs, results can be strengthened by considering your target audience and what’s most important to them.

Through industry-leading products such as the PRIZM segmentation and MobileScapes, Environics Analytics is uniquely positioned to take fan data further, leading to an enhanced and positive fan experience.” (Environics Analytics, 2022 interview)

Unification of data from multiple disparate sources yields powerful and potentially unexpected insights

Creating “one view” of the fan for enhanced insights requires expanded data and integration capabilities.

Data sources are vastly larger today. Sources include traditional & cloud repositories, IOT sensors including cameras, etc.		High bandwidth pictures, videos, AR, VR, and MR technologies are now mainstream within a digital-first world, especially in the sports entertainment industry.
"Headless" application architectures with efficient integration capabilities allow true best-of-breed solutions to be deployed and replaced as necessary or as new technology becomes available.		Connectivity and 360-degree data access is necessary for many digital use cases. (Source: Forbes, 2019)

“The use of analytics in the sports entertainment industry will only increase as the deluge of data increases. For example, teams can now optimize sponsorship negotiations and save millions through data analytics.”

“The market for sports analytics is expected to reach almost $4 billion by 2022, as it helps a variety of sports organizations in a range of areas.”

“Data from customer engagement within the stadium can be captured through electronic tickets - and even fingerprint or retinal scans - to understand fan movements.”

“Sports entertainment organizations can mine sentiment from social media streams to understand what fans are thinking and can use analytics to engage those fans via social channels.”

Info-Tech Insight

Traditional architecture typically features monolithic data repositories and data pre-integrated by ETL or other means. Whereas evolved digital-capable architectures support multiple real-time federated data sources and flexible real-time integration.

Leverage industry roundtables and trend reports to understand what’s possible

Refer to the organization’s business goals and initiatives and the Fan Experience Strategic Foresight Trend Report to identify data-driven digital opportunities.

Uncover important business goals, initiatives, and industry trends that can inform technology innovation and create data-driven digital opportunities. Through the Fan Experience Strategic Foresight Trends Report you will understand what drives these trends to be weak, medium, strong, or superior within the sports entertainment industry and how data plays a part in enabling them. Explore trends in areas such as: Advanced wireless Digital ecosystem Digital sustainability Vision recognition Immersive and gamified sports While you ensure that your organization’s business goals and initiatives are being evaluated for data-driven digital opportunities, it is also critical to do your market research. Identifying factors external to your organization and identifying technology innovation that will provide a competitive edge is crucial to competing in a data-driven and digital-first world.

Visit the Fan Experience Strategic Foresight Trends Report Visit Info-Tech’s Trends & Priorities Research Center

Trends powered by the right data architecture will create data-driven digital opportunities

1. TRENDS Digital Ecosystem Mobile integration & automation platforms Stadium/team apps Mobile ticket platforms Public engagement through digital and social media Contactless POS systems Digital signage, IPTV Vision Recognition Smart access control systems Real-time crowd intelligence Touchless access using facial recognition Facial recognition for COVID-19 screening Palm reading for payments & access control Biometric security

2. FUNNELED THROUGH AN OFF-FIELD DATA ARCHITECTURE

3. ENABLE NEW DATA-DRIVEN DIGITAL OPPORTUNITIES Food & Beverage Pre-Ordering by Mobile App Fitbit Challenge Fast Pass Premium Ticketing

Download Build a Data Integration Strategy

Download Build an Application Integration Strategy

Digital opportunities for value creation

Its important to understand how the data-enabled digital opportunities will impact your organization.

Example:

Info-Tech Insight

Incremental value that an organization can receive from different data-enabled digital opportunities can vary. Some others to consider are cost savings and improved risk management.

Digital opportunity value chain analysis

A. Food & Beverage Pre-Ordering Scenario

Exemplar conceptual data model

A. Food & Beverage Pre-Ordering Scenario

A high-level model that presents abstract business concepts in an easy, consumable way that tells a story.

Survey data shows a desire among fans to pre-order food and drinks before a game or other events.

• 50% of respondents indicated they were excited about the possibility to pre-order food and drink.
• 67% said they would buy more if they could pre-order and avoid the line.
(Source: Oracle, 2021)

Metrics:

• % mobile app fans engaged by offer
• $ spend, increase, and impact on loyalty
• % of fans who pick deliver to seat vs. over counter
• Time to order
• # of retained season ticket holders

Exemplar logical data model

A. Food & Beverage Pre-Ordering Scenario

A model that describes the data with as much detail as possible.

Digital opportunity value chain analysis

B. Fast Pass Premium Ticketing

Exemplar conceptual data model

B. Fast Pass Premium Ticketing

A high-level model that presents abstract business concepts in an easy, consumable way that tells a story.

Survey data from Oracle determines that 57% of people would love a fast pass system to gain priority access to food and shops.

This was mostly popular with families as 62% highly rated the option. (Source: Oracle, 2021)

• % of fans opting for fast pass
• Incremental revenue
• Time to process fast pass
• # of retained season ticket holders

Exemplar logical data model

B. Fast Pass Premium Ticketing

A model that describes the data with as much detail as possible.

Digital opportunity value chain analysis

C. Fitbit Challenge

Exemplar conceptual data model

C. “Fitbit” Challenge

The Minnesota Timberwolves have partnered with Fitbit to develop programs that engage players and fans, on and off the court.

The partnership facilitates many targeted opportunities, including challenges that reward participants with discounted tickets if they can keep up with their favorite player's daily workouts or the team's average weekly steps! (Source: NBA, 2017)

Metrics:

• % fans participating in challenge
• Average activity for fans
• Average activity for players
• # of long-term engaged fans in challenge
• # of retained season ticket holders

Exemplar logical data model

C. “Fitbit” Challenge

A model that describes the data with as much detail as possible.

Off-Field Data Reference Architecture Guide

Phase 3

Build Your Case for an Off-Field Data Architecture

This phase will walk you through the following activities:

• Create vision and mission statements
• Determine guiding principles
• Build high-value use cases
• Conduct a MoSCoW analysis
• Map off-field data architecture components to the goals cascade
• Measure your organization with metrics
• Build your business case profile

This phase involves the following participants:

• CIO
• CEO
• CFO
• CMO
• CDO
• Other stakeholders as appropriate

Ensure you bring a compelling case to the table to receive buy-in from the rest of the organization

The activities within this phase should create a compelling business case to get buy-in from your business executives.
Use our Off-Field Data Reference Architecture Business Case Presentation Template to present to your business executives.

• Vision & Mission Statement

• Guiding Principles

• High-Value Use Cases

• Prioritization of Use Cases

• Metrics

Step 3.1

Off-Field Data Reference Architecture

Activities

• 3.1.1 Create Vision and Mission Statements
• 3.1.2 Determine Guiding Principles
• 3.1.3 Build High-Value Use Cases
• 3.1.4 Conduct a MoSCoW Analysis

This step will walk you through the following activities:

• Create vision and mission statements
• Determine guiding principles
• Build high-value use cases
• Conduct a MoSCoW analysis

This step involves the following participants:

• Stakeholder working group
• Other key business stakeholders as appropriate

Outcomes of this step

• The vision and mission statement for an off-field data architecture
• The guiding principles for an off-field data architecture
• Identified business drivers that apply to the organization
• High-value use cases
• Prioritized use cases for making the case to business executives

Build Your Case for an Off-Field Data Architecture

Construct compelling vision and mission statements for your organizations off-field data architecture

A vision represents the way your organization intends to be in the future. A clear vision statement helps align the entire organization to the same end goal. Your vision should be brief, concise, and inspirational. Consider your IT department’s strengths, the customers of your IT services, and your current/future commitments to service quality. Remember that a vision statement is internally facing for other members of your company throughout the process.	Vision Example: Unify our data to become the world's best fan-centric football club, where fans can have the utmost personalized experience, whether they are at home or in the venue. (Source: Heller Search, 2020)	Mission Example: We strive to offer all our fans a personalized experienced, whether they are at home or in the venue, through trusted data that is integrated across all products, services, and platforms. (Source: Heller Search, 2020)	A mission expresses why the off-field data architecture exists. While your vision is a declaration of where your organization aspires to be in the future, your mission statement should communicate the fundamental purpose of the data management practice. It identifies the function of IT, what it produces, and its high-level goals that are linked to delivering timely, high-quality, relevant, and valuable data to business processes and end users. Consider if the practice is responsible for providing data for analytical and/or operational use cases. A mission statement should be concise and provide a clear statement of purpose for both internal and external stakeholders.

3.1.1 Create vision and mission statements

1-2 hours

Input: Business context

Output: The vision and mission statement for an off-field data architecture

Materials: Whiteboard or paper and pen, Presentation Template

Participants: Stakeholder working group

1. Gather your working group to create vision and mission statements for an off-field data architecture, to get buy-in from business executives.
2. Each participant should create a statement of purpose (1-5 lines) describing the future of an off-field data architecture. Have them consider the following:
   • Vision:
     • What does an organization with an effective off-field data architecture look like?
     • How will our organization benefit and grow from an improved off-field data architecture?
     • What are our fans saying, feeling, and doing? Reflect on current-state data collection.
   • Mission:
     • Why does this off-field data architecture exist?
     • What problems are we trying to solve?
     • Who will benefit from this off-field data architecture?
     • How will we reach our target?
3. Each participant should present their vision and mission. Discuss the common themes and then develop a concise vision and mission statement that incorporates the group’s ideas.
4. Consolidate the findings and document the results in the appendix of the Presentation Template.

Download the Presentation Template

Design guiding principles for your organization’s off-field data architecture

Provide an effective framework that will help the business make decisions about how it uses or implements data architecture technology.		Provide a guide to establish evaluation criteria and influence the selection of suppliers, business partners, components, and products or product architectures used for data.
Drive the functional requirements of a data solution’s architecture.		Assist in the assessment of the existing data architecture environment to provide insights into the transition activities needed to strategically implement the principles in support of the business goals and priorities.
Use the Big Data Architecture Principles & Guidelines Template for examples and to start developing your guiding principles. Download the Big Data Architecture Principles & Guidelines Template		To be effective, all principles, policies, and guidelines should be defined and agreed upon by both business and IT executives. Once they have been agreed to and published, the principles and policies provide a framework that can be used to explain and justify why certain business and IT decisions are being made or need to be made.

3.1.2 Determine guiding principles

1-2 hours

Input: Business context

Output: The guiding principles for an off-field data architecture

Materials: Whiteboard or paper and pen, Big Data Architecture Principles & Guidelines Template, Presentation Template

Participants: Stakeholder working group

1. In your working group, brainstorm guiding principles related to key business objectives and goals of data. These will help you develop the practice's ultimate principles. Use the Big Data Architecture Principles and Guidelines Template to assist in this. Try to create five to ten principles.
2. In smaller groups, each group will take one of the values and determine:
   • Off-field data is…
   • The business can…
   • The off-field data architecture…
3. Get back together a group to discuss the principles:
   • How can these principles help guide the practice's planning?
   • How will these principles help to correct and guide fan behavior?
4. Finalize and document the guiding principles in the appendix of the Presentation Template.

Download the Big Data Architecture Principles & Guidelines Template

Download the Presentation Template

Determine high-value use cases for informing the business case

• During business context interviews your organization should've been able to identify the high-priority initiatives and needs for your organization that an off-field data architecture can support.
• Bring data owners, data stewards, business subject matter experts, and their IT partners or data custodians together to discuss and create use cases that represent the top business needs and priorities. If addressed, these will deliver value and support the strategic direction of the organization.
• Include in these conversations current challenges, risks, and opportunities associated with the use of data across lines of business. Also explore which other stakeholder groups or lines of business will be impacted and how you will measure success.

Leverage Info-Tech’s data requirements and mapping methodology for creating use cases

• Objective: Business-needs gathering activity to highlight and create relevant use cases around data-related problems or opportunities that are clear and contained and, if addressed, will deliver value to the organization.

3.1.3 Build high-value use cases

2-4 hours

Input: Business context, Subject area expertise

Output: Identified business drivers that apply to the organization, High-value use cases

Materials: Whiteboard or paper and pen, Data requirements and mapping methodology, Presentation Template

Participants: Key business stakeholders, Stakeholder working group

1. Bring together key business stakeholders (data owner, stewards, SMEs) from a particular line of business as well as the data custodian to build cases for their units. Data-driven digital opportunities were already identified in phase 2; leverage them or create new ones if you would like to.
2. Leverage Info-Tech’s Data Requirements and Mapping Methodology for Creating Use Cases.
   Document the following items:
   • Risks
   • Opportunities
   • Pains
   • Challenges
   • If perfectly solved scenario
   • Impacted/improved capabilities
   • Concerns
   • KPIs
   • Steps in the current process
   • Applications used at each step
   • Data elements involved, created, used or transformed
3. Have the stakeholders move through each breakout session, using flip charts to brainstorm and to document thoughts.
4. Debrief and document results in the appendix of the Presentation Template. Repeat this exercise with as many lines of business as possible.

Download the Presentation Template

Conduct a MoSCoW analysis

Direct strategic IT investments based on the collective output of the use-case assessments. When combined with a solid understanding of business priorities and the vision and mission, a use-case assessment can be the driving force that informs a unified perspective on the sequencing of an organization’s strategic IT initiatives. Assessments based on how well a use case is supported by people (via organizational analysis), process (via process review), and technology (via application, infrastructure, data, and security improvements) will inform the overall health of a use case, or in other words, the size of a gap. This information, when contrasted with the concept of a MoSCoW-based effort to value, forms an enhanced decision-making framework that can be used to determine initiative sequencing on a strategic roadmap. If a use case has a large gap (is poorly supported by people, process, data, or technology), it should be considered as high effort, or difficulty, to address. When the use case is well aligned with business priorities and the vision and mission, the use case gap should be considered as high value, low effort to address. See the figure on the right: IT leaders should focus their efforts on the lower-right quadrant (high value, low effort). In the top-right quadrant (high value, high effort), IT should seek business support to drive the initiative. Use case gaps on the right side of the quadrant overall are good candidates for use case outsourcing.

3.1.4 Conduct a MoSCoW analysis

2-3 hours

Input: Business context, Use cases

Output: Prioritized use cases for making the case to business executives

Materials: Whiteboard or paper and pen, MoSCow analysis chart, Presentation Template

Participants: Stakeholder working group

1. Bring together the working group and discuss the following questions to determine where each use case belongs on the MOSCOW analysis:
   • How well is this use case supported by internal and external customers? People?
   • What would the process for this use case look like? Is it achievable?
   • Do we have the technology to support this use case? If not, what kind of improvements would have to be done? Are they achievable (application, infrastructure, data, security)?
2. If the use case is poorly supported by people, process, or technology it should be considered high effort, or difficulty, to address.
3. If the use case is well aligned with business priorities and the vision and mission, it should be considered high value, low effort to address.
4. Organizations should focus on the high value, low effort use cases, where they will have to seek business support to drive initiatives in the high value, high effort quadrant. Overall, use cases on the right side of the quadrant are good candidates to present to business executives.
5. Document your findings within the appendix of the Presentation Template.

Download the Presentation Template

Step 3.2

Determine the Impact to the Organization

Activities

• 3.2.1 Map Off-Field Data Architecture Components to the Goals Cascade
• 3.2.2 Measure Your Organization With Metrics
• 3.2.3 Build Your Business Case Profile

This step will walk you through the following activities:

• Map off-field data architecture components to the goals cascade
• Measure your organization with metrics
• Build your business case profile

This step involves the following participants:

• Stakeholder working group

Outcomes of this step

• Enhanced goals cascade/business strategy
• Metrics and measures that determine the impact that the off-field data architecture will have on the organization
• Business case profile

Build Your Case for an Off-Field Data Architecture

An off-field data architecture should align with your goals cascade

3.2.1 Map off-field data architecture components to the goals cascade

1-3 hours

Input: Business context, Goals cascade/business strategy, Off-field data architecture

Output: Enhanced goals cascade/business strategy

Materials: Whiteboard or paper and pen, Presentation Template

Participants: Stakeholder working group

1. Gather your working group and start to map out what components of your off-field data architecture enable the IT goals that support the organizational goals to better illustrate the value to business executives.
2. Document your work in the appendix of the Presentation Template.

Info-Tech Insight

Strategic organizational goals rely on data to be achievable. Without data, the goals are simply statements; with data, the statements become a reality.

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Use metrics to measure business success

Consider the following metrics to measure your current state and continue to measure these metrics year by year to see your organizations improvements

3.2.2 Measure your organization with metrics

2-3 hours

Input: Business context, Metrics

Output: Metrics and measures that determine the impact that the off-field data architecture will have on the organization

Materials: Whiteboard or paper and pen, Presentation Template

Participants: Stakeholder working group

1. Gather your working group and consider the given metrics to determine if they are good measures for what your organization is trying to accomplish. If not, brainstorm or research some metrics that you will be able to use to properly measure your organization.
2. Document the outcome, metric, impact, and measure of the metrics your organization wants to use within the Presentation Template.
3. Calculate any of the metrics that you can do.
4. If there are metrics you cannot currently calculate, discuss with the working group when and who will be accountable for doing so. Record this in the Presentation Template.
5. Discuss how frequently your organization will measure these metrics to determine the impact it is having on the organization (yearly, quarterly, etc.) and who will be responsible for what metrics. Record this in the appendix of the Presentation Template.

Download the Presentation Template

Business case profile for your off-field data architecture

Example: Add the initiative name and its value statement. Although it will be difficult to get an accurate estimate for time and dollars required for initiatives while building the strategy, a ballpark within +/- 100% of the actual will help to begin to budget and scope the roadmap.

Brainstorm risks and dependencies for this initiative. These could be external or internal risks, dependencies, or other initiatives or resources.

Outline the benefits achieved by completing this initiative. Think about the specific capabilities or strategic goals they will help support. Brainstorm who would be the main stakeholders involved in the initiative.

Develop and implement an off-field data architecture

Develop and implement an off-field data architecture that unifies fan data through integration across all products, services, and platforms our organization provides, to become fan-centric and provide personalized experiences.

Incremental Cost: $10,000 LABOR $20,000 SYSTEMS $10,000 CONTRACTS $40,000 TOTAL	Initiative Description: An off-field data architecture will support the existing organizational and IT goals that are set out, and it can also activate additional opportunities for fans. Hiring and training staff to maintain and assure data quality while also analyzing data to create insights will be required. The way we create experiences and engage with fans will become more personalized with off-field data, which is a key outcome of the goals cascade for the organization.		Project Timeline:
CIO comments: “An off-field data architecture that allows for better insights on fan data and ease of creating personalized experiences will allow for us to create better relationships and experiences with fans to lead into higher engagement, which aligns with our digital fan engagement strategy.”	Primary Business Benefits: Collect efficient off-field data on fans to develop more personalized experiences	Other Expected Business Benefits: Enhance fan profiles to determine who is who Decrease the room for error on marketing initiatives with data-driven decision making More opportunities are showcased and developed (upselling)	Project Team: Business Sponsor: Daniel IT Sponsor: Jessica PM: Alex
	Risks: Ongoing maintenance and data quality assurance Data maturity and culture of the organization		Dependencies: Development of data architecture The potential software needed to collect data Hiring staff to maintain and analyze the data Training

(Note: This is an example; therefore, the information here is not accurate, and the cost, timeline, etc. do not reflect real life precisely.)

3.2.3 Build your business case profile

1-2 hours

Input: Business context, Previous activities conducted

Output: Business case profile

Materials: Whiteboard or paper and pen, Presentation Template

Participants: Stakeholder working group

1. Gather your working group, and discuss the different components needed to fill in the business case profile.
2. Complete the business case profile within the appendix of the Presentation Template to then present to business executives.

Download the Presentation Template

Summary of accomplishment

• You have now completed the Presentation Template and the various activities it contains to present to your business executives.
• This presentation should be able to tell the story of why an off-field data architecture is crucial for your sports entertainment organization.
• Not only does it drive a sustainable future for your team, but it will also support IT and organizational goals, bringing more than one purpose to this data architecture.
• Once you get buy-in from your business executives, it is important to build a strategy around your data architecture to ensure success.

Additional Support

If you would like additional support, have our analysts guide you through other phases as part of an Info-Tech Workshop.

Contact your account representative for more information. workshops@infotech.com 1-888-670-8889

To accelerate this project even further, engage your IT team in an Info-Tech workshop with an Info-Tech analyst team.

Info-Tech analysts will join you and your team at your location or welcome you to Info-Tech’s historic Toronto office to participate in an innovative onsite workshop.

The following are sample activities that will be conducted by Info-Tech analysts with your team:

MoSCow Analysis Conduct a MoSCow analysis to define which high-value use cases pose the greatest value and lowest effort to determine what use cases should or could be addressed.

Business Case Profile Create a business case profile to present the project on one page. One-page profiles are adequate ways to showcase and explain an initiative from top to bottom.

Off-field data architecture considerations and next steps

Research Contributors and Experts

Bibliography

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