- A constant influx of new data solutions combined with closed or siloed source transactional applications create complexity and challenges when trying to integrate it together to create insights you can act on to improve fan experience, engagement, revenue, and sponsorship relations.
- You are struggling to get buy-in from your business executives for investing in off-field data applications.
Our Advice
Critical 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, improve fan engagement and sponsorship relations, and achieve business goals.
Impact and Result
- Establish a working group of key stakeholders from the organization to work on this endeavor together and determine what the risks and considerations may be.
- Determine the state of your current data architecture and what data-driven digital opportunities can arise from Info-Tech's off-field reference architecture.
- Build a business case for why an off-field data architecture is important to get buy-in from your business executives.
- Once buy-in is secured, input this off-field architecture into your next data strategy to achieve your business goals.
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.
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Elizabeth Silva
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Executive Summary
Your Challenge
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Common Obstacles
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Info-Tech’s Approach
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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
Off-Field Analytics
Deals with the business side of sports. Off-field analytics focus on helping a sports organization surface patterns and insight through data that would help increase ticket and merchandise sales, improve the fan experience, increase engagement, and more. Off-field analytics is what creates an off-field data architecture and makes for a fan-driven data strategy. |
On-Field Analytics
Deals with improving the on-field performance of teams and players by collecting player statistics and patterns. On-field analytics is what makes for a player development or team development strategy. |
“Off-field data and analytics is the ability to transform data into capabilities that transform the experience for fans.” (Rajiv Maheswaran, CEO, Second Spectrum) |
An off-field data architecture and fan-driven data strategy is important
An off-field data architecture should be the core of any fan-driven data strategy. This type of strategy should be a vehicle for ensuring data is poised to support your organization’s strategic objectives and opportunities.
“Data-driven organizations are not only 23 times more likely to acquire customers, but they're also 6 times more likely to retain customers and 19 times more likely to be profitable." (McKinsey Global Institute via Tappit, n.d) |
Other benefits that were found from using data are:
“Data itself isn’t valuable, it’s the ability to use data to create content that fans want." (Rajiv Maheswaran, CEO, Second Spectrum) |
Use fan data to differentiate and remain competitive in today’s digital economy
Off-field data in sports can create many benefits for organizations, such as sustainable revenue streams, robust fan intelligence to improve fan experience and engagement, and improved sponsorship relations. Having effective off-field data to understand fans better has so many more benefits than it may seem, as being different and remaining competitive in today's sports market is difficult to do without it.
Revenue Reliant on Team Performance Is Not SustainableData and analytics have been used for improving team performance, although relying on team performance is not a sustainable choice as revenue is linked to performance. If a team is performing well, it generates revenue. If a team performs poorly, sources of revenue such as ticket and merchandise sales will drop. Sports teams must create new revenue streams to be sustainable. By collecting data through multiple different sources, the 360-degree view of the fan will give sports teams a deeper understanding of their fans, to help them generate revenues and sustain relationships beyond team performance. Understanding fans better is good for the long-term health of the business, as it allows for prediction of fan engagement behaviors and actions. (Source: CIO, 2017) |
Fan Intelligence BenefitsUnderstanding fans and their fan engagement behaviors is a key aspect of fan engagement, which every sports organization is looking to achieve. Having the right data allows sports organizations to target and personalize offerings to maximize the potential of monetizing their assets. Fan-driven data decision making is crucial when it comes to understanding your fan base, as understanding the data to further engage fans in order to refine and improve future activations is important. (Source: Sportcal, 2020) |
Sponsorship BenefitsData and measurability can provide wins for sports team, fans, and sponsors. With data and analytics, it’s now possible for sports organizations to measure the impacts of the sponsorship opportunities placed within their venues in aggregated ways. The three wins:
(Source: Sportcal, 2020) |
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. |
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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. |
Consider a comprehensive fan-driven data strategy to unlock value
"Data can be considered to be one of the most valuable commodities in today’s world - more so than gold, oil and bitcoin. It underpins most business and performance operations; and the organizations that are able to maximize its use are the most successful.” (David Ingham, Client Partner of Media, Entertainment & Sport at Cognizant via Techradar, 2021) |
"The awareness, collection and usage of data needs to be seeded and cultivated from the top of the organization as a priority for it to take root within sports entities so they can pave the way for inclusion as a source of insight in decision making that will future-proof the organization's operating model." (Global Sports Innovation Center, Powered by Microsoft, 2020)
In the major leagues, 75-85% of single game buyers don’t come back every single year, where teams need to be investing in effective tools to better understand fans through practical insights. (StellarAlgo, 2021) "After the first lockdown, there was a short pause in CDP-projects within the sports industry. However, the need for a digital transformation became globally evident to most sports organizations, resulting in tremendous growth in CDP-projects. The CDP is finally perceived as a backbone to digital transformation & fan engagement.“ (Peter Kekesi, Data Talks, 2021 interview) |
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 SERVICESThe strategic use of data can enable sports entertainment organizations to provide higher quality services. |
![]() FAN INTELLIGENCEThe 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 DECISIONSThe 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 RELATIONSMake 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 MONETIZATIONCreate actionable decisions around your fan data so you will be able to monetize it. |
![]() BECOME A PROVEN BUSINESS PARTNERIf 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.
Example:
Info-Tech’s methodology for an off-field data architecture
1. Define a Working Group and the Current State | 2. Discover Data-Driven Digital Opportunities | 3. Build Your Case for an Off-Field Data Architecture | |
Phase Steps |
1.1 Build an Accurate Depiction of the Business 1.2 Information Assessment |
2.1 Off-Field Data Reference Architecture |
3.1 Construct the Business Case 3.2 Determine the Business Case Impact to the Organization |
Phase Outcomes | Establish a working group to provide direction and clarity on an off-field data architecture, such as the associated risks with this initiative, and comprehend the current data management maturity. | Understand what an off-field data architecture is and discover what data-driven digital opportunities exist for value creation.
Read through conceptual and logical data model examples for value creation. |
Develop vision and mission statements and guiding principles. Identify business drivers and high-value use cases to then prioritize for making the case to business executives. Determine the impact of this initiative by enhancing the organization’s existing goals cascade/business strategy, calculating metrics, and designing a business case profile. |
Blueprint Deliverable
Each step of this blueprint is accompanied by supporting deliverables to help you accomplish your goals: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
DIY Toolkit |
Guided Implementation |
Workshop |
Consulting |
"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." | "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." | "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." | "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 |
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?
Phase 1 |
Phase 2 |
Phase 3 |
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Call #1: Develop working group; discuss and assess current data maturity. | Call #2: Walk through the off-field data reference architecture, and exemplar data models for value creation. | Call #4: Create vision and mission statements.
Call #5: Determine guiding principles. |
Call #6: Build high-value use cases.
Call #7: Conduct a MoSCoW analysis. |
Call #8: Map the data architecture components to the goals cascade.
Call #9: Determine metrics for measuring success. Call #10: Build business case profile. |
Off-Field Data Reference Architecture Guide
Phase 1
Define a Working Group and the Current State
Phase 1 1.1 Build an Accurate Depiction of the Business 1.2 Document Your Current Data Management Maturity 1.3 Assess How Well Information Supports Business Capabilities | Phase 2 2.1 Off-Field Data Reference Architecture | Phase 3 3.1 Construct the Business Case 3.2 Determine the Business Case Impact to the Organization |
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
Step 1.1 | Step 1.2 |
The challenges associated with fan data
“Big data is exploding. But many companies are still struggling to simplify how to make their data actionable.” (CPA Canada, 2019) |
Signals of Concern37% 32% 10% 29% (Source: Tappit, n.d.) |
Leverage your working group
Your working group should:
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A working group should be comprised of:
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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
1-3 hoursInput: 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
- As a group, create a working group of stakeholders that should be involved in creating the business case for an off-field data architecture.
- Aim to create a working group that can help inform your organization’s decision on whether to pursue this initiative now or wait.
- Evaluate and discuss each potential stakeholder on the list based on:
- Influence: To what degree can this stakeholder impact the progress of this initiative?
- Involvement: How involved is the stakeholder in this initiative already?
- Support: How supportive is this person of this initiative?
- 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.
Case StudyCanada West TV and Canada West Universities Athletic Association’s Sporting Events Data Strategy |
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INDUSTRY
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SOURCE
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ChallengeCanada West TV is a video streaming platform service launched on YAREtv to showcase Canada West Universities Athletic Association’s sporting events. An affiliate of U Sports, Canada West consists of 17 universities across Alberta, Manitoba, British Columbia, and Saskatchewan. Over the last three seasons (2016-2017 to 2019-2020), the platform was struggling to achieve higher YOY growth rates and they were looking to increase those numbers by understanding their fans better through data. |
SolutionOn assuming charge from the incumbent in 2017, a three-pronged strategy was adopted: Reach, Engage, and Monetize. Using data as its guiding light enabled Canada West TV to identify users in the target segment, convert them into subscriptions, retain them as registered users in the off-season, and steadily acquire a critical mass for what was a fledgling service three years ago. |
ResultsThe service performed extremely well, gaining 12,000+ registered users and selling 15,000+ passes from a universe of 150,000, giving them a 10% conversion rate, which is extremely high relative to comparable organizations. The successful identification of fan segments and creation of a registered data base within the YAREtv platform were crucial factors in securing a title sponsor for the property who was able to accurately calculate the ROI for the brand association with Canada West TV.
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Developments in business and technology are changing how sports organizations use and manage data
The main objective of BI and advanced analytics is for the organization’s decision makers to have improved value to cost and identify new business opportunities from data-driven decision making.
Operate in Real TimeBusinesses of today operate in real time; to maintain a competitive edge, businesses must identify and respond quickly to opportunities and events. To effectively do this the business must have accurate and up-to-date data at their fingertips. |
Business Intelligence and AnalyticsBusiness intelligence: analytical capabilities centered around metrics and measures that gauge past performance and guide business planning.
Advanced analytics: uses sophisticated techniques to predict events, uncover trends and patterns, and garner additional insights from data that could not be uncovered from traditional BI practices.
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Consider the various IT risks that may come with an off-field data architecture
Overarching IT Risks
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(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
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(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
Step 1.1 | Step 1.2 |
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:
Discover Business Goals & Capabilities
The business goals and capabilities blueprint helps you uncover what IT knows and needs to know about the business context. This is a necessary first step to begin each of Info-Tech’s strategic IT initiatives and to uncover business context gaps. |
Data Quality Diagnostic
The data quality diagnostic assesses what the data quality satisfaction is within your organization, compared to satisfaction across different departments, and helps you understand data issues at an individual respondent level. Additionally, you can uncover which data is most important and more error-prone. |
Data Culture Diagnostic
The data culture diagnostic is used to understand how your organization scores across ten different areas relating to data culture to determine whether the organization perceives data to be an asset or not. Contact your rep for this diagnostic. |
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:
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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
- Gather your working group to discuss the results of the Data Quality and Data Culture diagnostics.
- Discuss and determine what your current data management maturity is, based off business context and the diagnostics completed.
- 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.
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Assess how well existing information supports capabilities | |
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NONE: Data is unavailable, unreliable, duplicated, or not of sufficient detail | |
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LOW: Data is available but not subject to adequate integrity or quality controls. Data ownership is undefined. | |
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MEDIUM: LOW + Data is available but not fully automated. Data ownership is mostly defined. | |
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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
- Gather your working group to discuss the availability and quality of current data to provide information as a business asset.
- Analyze and assess data on the basis of quality, integrity, and ownership and on the presence of an effective data governance framework.
- 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.
- 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
Phase 1 1.1 Build an Accurate Depiction of the Business 1.2 Document Your Current Data Management Maturity 1.3 Assess How Well Information Supports Business Capabilities | Phase 2 2.1 Off-Field Data Reference Architecture | Phase 3 3.1 Construct the Business Case 3.2 Determine the Business Case Impact to the Organization |
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
Step 2.1 |
Together, data architecture and data modeling fill in the gaps between business goals and technology
Data Architecture vs. Data Modeling
Data Architecture
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Data Modeling
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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
The data reference architecture must support both forms, based on the profile of users and applications.
Data ArchitectureSupports 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 DataIs 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.
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“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.
New data sources and demands for real-time information, require expanded integration capabilities for both transactional and analytical applications
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Off-Field Data Reference Architecture for the Sports Entertainment IndustryExamples of external data points that may be required from the organization to generate new and intuitive insights through the data architecture.![]() Examples of applications and channels that an organization may want to integrate to gather information to reach fans. |
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:
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![]() ![]() Visit the Fan Experience Strategic Foresight Trends Report Visit Info-Tech’s Trends & Priorities Research Center |
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Trends powered by the right data architecture will create data-driven digital opportunities
1. TRENDS
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2. FUNNELED THROUGH AN OFF-FIELD DATA ARCHITECTURE![]() |
3. ENABLE NEW DATA-DRIVEN DIGITAL OPPORTUNITIES
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Download Build a Data Integration Strategy
Digital opportunities for value creation
Its important to understand how the data-enabled digital opportunities will impact your organization.
Example:
Data-Enabled Digital Opportunities |
New Customer |
New Market |
New Business Model |
New Product or Service |
Incremental Value |
What opportunities can have a high or immediate impact on the organization? | Target new customer segments for existing products or services | Enter or create new markets by applying existing products or services to different problems | Adjust the business model to capture a change in how the organization delivers value | Introduce new products or services to the existing market | What value is the organization receiving from this opportunity? |
A. Food & Beverage Pre-Ordering |
— | — | Online mobile app for F&B pre-ordering + concession order handling | New/enhanced mobile app with hyper-personalization | Improved service delivery |
B. Premium Fast Pass Ticketing |
New entitlement to premium ticket holders | — | New premium ticket for faster access to venue | New ticket option available through mobile app, (potentially exclusively via mobile app) | Increased revenue |
C. Fitbit Challenge |
— | Corporate partnership with Fitbit | Use externally streamed data from corporate partner to drive fan engagement | New/enhanced mobile app and aggregation data service | Strategic alliances |
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
Greatest Risks
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Complexity
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Key Benefits
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Dependencies
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Financial Revenue Impact
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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
Greatest Risks
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Complexity
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Key Benefits
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Dependencies
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Financial Revenue Impact
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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
Greatest Risks
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Complexity
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Key Benefits
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Dependencies
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Financial Revenue Impact
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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
Phase 1 1.1 Build an Accurate Depiction of the Business 1.2 Document Your Current Data Management Maturity 1.3 Assess How Well Information Supports Business Capabilities | Phase 2 2.1 Off-Field Data Reference Architecture | Phase 3 3.1 Construct the Business Case 3.2 Determine the Business Case Impact to the Organization |
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.
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Vision & Mission Statement
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Guiding Principles
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High-Value Use Cases
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Prioritization of Use Cases
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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
Step 3.1 | Step 3.2 |
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.
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VisionExample: 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) |
MissionExample: 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.
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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
- Gather your working group to create vision and mission statements for an off-field data architecture, to get buy-in from business executives.
- 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?
- Vision:
- 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.
- 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
Define the underlying general rules and guidelines (across the data architecture environment) that the organization will apply to use and deploy all business and IT resources and assets. Principles are intended to: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 |
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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
- 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.
- 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…
- 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?
- 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.
Breakout session #1
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Breakout session #2
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Breakout session #3
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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
- 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.
- 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
- Have the stakeholders move through each breakout session, using flip charts to brainstorm and to document thoughts.
- 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. |
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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
- 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)?
- If the use case is poorly supported by people, process, or technology it should be considered high effort, or difficulty, to address.
- 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.
- 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.
- 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
Step 3.1 | Step 3.2 |
An off-field data architecture should align with your goals cascade
The identified digital opportunities that are supported through off-field data architecture and modeling align with the following IT goals, which in the end are achieved through the various initiatives, improve the data architecture and other IT capabilities, and support the various organizational goals, initiatives, and capabilities.
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
- 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.
- 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.
Download the Presentation Template
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
Outcomes | Metrics | Impacts | Measures |
Fan engagement |
Fan engagement rate | Increase fan engagement within a year |
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Improved back-end intelligence |
Return on investment (ROI) | Improve data intelligence and efficiencies within a year |
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Personalization |
Conversion rate, click through rate | Through data and analytics, personalization can be improved where conversion rates and click through rates will increase, resulting in actionable results |
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Actionable analytics |
Return on engagement, monthly recurring revenue | With the improved service of data reports, sports entertainment organizations can create actionable and valuable decisions to satisfy fans and improve engagement |
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Superior fan relationship |
Fan lifetime value, churn rate | By understanding fans better with improve data intelligence, organization can create superior relationships with fans, resulting in high lifetime value and lower churn rate |
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Efficient venue management |
Employee satisfaction, operating cash flow, operating profit margin | Better data intelligence allows for improving operations efficiencies, making tasks easier for employees and more efficient |
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Effective fan service |
Net promoter score | With improved venue management, effective fan service should follow, improving the quality of the experience where net promoter scores are expected to increase |
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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
- 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.
- Document the outcome, metric, impact, and measure of the metrics your organization wants to use within the Presentation Template.
- Calculate any of the metrics that you can do.
- 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.
- 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:
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Project Timeline:
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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:
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Other Expected Business Benefits:
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Project Team:
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Risks:
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Dependencies:
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(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
- Gather your working group, and discuss the different components needed to fill in the business case profile.
- 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
Get buy-in from business executives.- 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.
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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
The Off-Field Data Architecture Guide can assist with the following blueprints:
1 |
Data Strategy
Sports entertainment organizations are evolving and becoming more and more data centric, with maturing expectations and demands. A strategy needs to be in place for an off-field data architecture to work. |
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2 |
Data Management
As organizations increase their need for data to become more strategic, and with a growing demand for data to better support business processes and inform decision making, it is important for data to be accessible and trustworthy. |
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3 |
Big Data Architecture
An increasing number of businesses, especially within sports entertainment, are starting to use data to make decisions. If a data architecture has not already been built, chances are one will be needed soon. |
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4 |
Data Model
Data models tell the story of the organization and its data in pictures to be used by a business as a tool to evolve the business capabilities and processes. |
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5 |
Master Data Management
IT and business leaders are recognizing the need to implement master data management (MDM) processes and technology to better manage enterprise master data. |
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6 |
Data Integration
Any time an organization changes applications or the database ecosystem it requires the organization to solve a data integration problem. Poor integration holds back critical functions. |
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7 |
Data Quality Diagnostic
Get a report showing the business’ evaluation of data quality so you can focus your improvement efforts to meet their needs. |
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8 |
Analytics, BI & Reporting
In respect to business intelligence (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. |
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9 |
Privacy, Risk, and Compliance
Depending on the geographical area of your organization you may have regulations that you need to follow and be aware of to stay in compliance when it comes to fetching data. |
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10 |
Infrastructure
Infrastructure is left in a reactive mode, overwhelmed with work, while the business fumes at the delay. Follow the roadmap process to better interface with the business, becoming true strategic partners. |
Research Contributors and Experts
Ian Greenwood
Dan Axman
Adam Bernatt
Tania O’Brien
Jordan Rutner
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Peter Kekesi
Igor Ikonnikov
Sharon Foltz
Andy Neill
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Bibliography
Andrus, Aden. “What is Conversion Rate? How to Calculate and Improve Your Conversion Rate.” Disruptive Advertising, 15 April 2020. Accessed 9 Feb 2022.
Berry, Andy. “How sports clubs can use data to secure their futures.” CIO, 6 Dec. 2017. Accessed 31 Jan. 2022.
CFI Team. “Engagement Rate The level of engagement generated from a created content or a brand campaign” CFI, 8 Nov. 2019. Accessed 9 Feb 2022.
Data and Sports: A Marriage Made in Heaven, and the Cloud. Global Sports Innovation Center Powered by Microsoft, 2020. Accessed 7 Feb. 2022.
“How Data Can Unlock Fan Engagement.” Sportradar, n.d. Accessed 7 Feb. 2022.
“How to Calculate Customer Churn Rate and Revenue Churn Rate.” Salesforce, n.d. Accessed 9 Feb. 2022.
“How to Calculate Recurring Revenue.” Salesforce, n.d. Accessed 9 Feb. 2022.
Ingham, David. “Data in sport: driving fan engagement and elite performance.” Techradar, 13 July 2021. Accessed 2 Feb. 2022.
Lithmee. “What is the Difference Between Conceptual and Logical Data Model.” Pediaa, 15 July 2019. Accessed 28 April 2022.
Maheswaran, Rajiv. “The Next Way of Seeing Sports.” Second Spectrum, n.d. Accessed 17 Jan. 2022.
Manges, Maneesha. “Calculating ROE – Putting a Number Against the Engagement Metric.” Personify, 19 Nov. 2019. Accessed 9 Feb. 2022.
McCullough, Micheal. “How big data is changing sports fandom.” CPA Canada, 31 Oct 2019. Accessed 7 Feb. 2022.
Mintimberwolvespr. “Minnesota Timberwolves and Fitbit Announce Multi-Year Partnership Naming Company ‘Official Wearable,’ ‘Official Sleep Tracker’ and Jersey Patch Sponsor.” NBA, 20 June 2017. Accessed 29 April 2022.
Nevogt, Dave. “How to Measure and Improve Employee Satisfaction [Survey Included].” Hubstaff, 16 Oct. 2020. Accessed 9 Feb 2022.
Olavsrud, Thor. “What is data architecture? A framework for managing data.” CIO, 24 Jan. 2022. Accessed 28 April 2022.
Peters, Rich. “How to Write Your Data Vision and Mission Statements.” Heller Search, 7 Oct. 2020. Accessed 10 Feb. 2022.
Ricky, Abhas. “How Data Analysis In Sports Is Changing The Game.” Forbes, 31 Jan. 2019. Accessed 27 April 2022.
Saleh, Tariq. “Fan engagement: A game beyond the game.” Sportcal, 10 Dec. 2020. Accessed 4 August 2021.
Schnater, Bas. “Data Maturity Model: 61% of all sports organisations do not use data for their overall strategy.” Fan Engagement Customer Experience Marketing, 6 Jan. 2021. Accessed 7 Feb. 2022.
“SPORTS DATA SOLUTIONS Major League.” Stellaralgo, 2021. Accessed 7 Feb. 2022.
“Sports Innovation: The Power of Data.” N3xt Sports, 14 May 2020. Accessed 9 Feb. 2022.
“The power of fan data for sports organisations – how mature is your strategy?” Tappit, n.d. Accessed 9 Feb. 2022.
Trendell, Amber. “New research from Oracle shows US consumers are eager to return to stadiums provided certain changes are implemented.” Oracle, 23 March 2021. Accessed 28 April 2022.
Vanhaesebroeck, Jente. “Learn your customer lifetime value first, if you want to improve loyalty.” StriveCloud, 29 July 2020. Accessed 9 Feb. 2022.