What is involved in Data Monetization
Find out what the related areas are that Data Monetization connects with, associates with, correlates with or affects, and which require thought, deliberation, analysis, review and discussion. This unique checklist stands out in a sense that it is not per-se designed to give answers, but to engage the reader and lay out a Data Monetization thinking-frame.
How far is your company on its Data Monetization journey?
Take this short survey to gauge your organization’s progress toward Data Monetization leadership. Learn your strongest and weakest areas, and what you can do now to create a strategy that delivers results.
To address the criteria in this checklist for your organization, extensive selected resources are provided for sources of further research and information.
Start the Checklist
Below you will find a quick checklist designed to help you think about which Data Monetization related domains to cover and 128 essential critical questions to check off in that domain.
The following domains are covered:
Data Monetization, Business intelligence, Credit card, Crowd sourced, Customer experience, Data as a service, Data capitalism, Data supply chain, European Union, Federated identity, Financial services, General Motors, Gramm–Leach–Bliley Act, Information banking, Internet of things, Location data, Market share, Mobile devices, Patient privacy, Personal cloud, Personal data vaults, Privacy rights, Real time, Retail banks, Reward programs, Risk factors, The Guardian, Trade value, United States Congress, Vendor relationship management, Venture capital:
Data Monetization Critical Criteria:
Design Data Monetization governance and probe the present value of growth of Data Monetization.
– Are there any disadvantages to implementing Data Monetization? There might be some that are less obvious?
– Does Data Monetization appropriately measure and monitor risk?
– What are internal and external Data Monetization relations?
Business intelligence Critical Criteria:
Study Business intelligence failures and gather Business intelligence models .
– Does the software let users work with the existing data infrastructure already in place, freeing your IT team from creating more cubes, universes, and standalone marts?
– Can you easily add users and features to quickly scale and customize to your organizations specific needs?
– What are the main differences between a business intelligence team compared to a team of data scientists?
– How does Tableau stack up against the traditional BI software like Microstrategy or Business Objects?
– What is the biggest value proposition for new BI or analytics functionality at your company?
– Does your BI solution allow analytical insights to happen anywhere and everywhere?
– What are some common criticisms of Sharepoint as a knowledge sharing tool?
– Who prioritizes, conducts and monitors business intelligence projects?
– What is your anticipated learning curve for Technical Administrators?
– What are the pros and cons of outsourcing business intelligence?
– Number of data sources that can be simultaneously accessed?
– What type and complexity of system administration roles?
– What are the most efficient ways to create the models?
– What is the purpose of data warehouses and data marts?
– What are the pillar concepts of business intelligence?
– How can data extraction from dashboards be automated?
– What are typical data-mining applications?
– Does your system provide APIs?
Credit card Critical Criteria:
Canvass Credit card visions and acquire concise Credit card education.
– Think about the kind of project structure that would be appropriate for your Data Monetization project. should it be formal and complex, or can it be less formal and relatively simple?
– What are your most important goals for the strategic Data Monetization objectives?
– If credit card payments are accepted, do we currently have a payment gateway?
– Does the Data Monetization task fit the clients priorities?
– Will mobile payments ever replace credit cards?
Crowd sourced Critical Criteria:
Examine Crowd sourced results and report on setting up Crowd sourced without losing ground.
– Can we do Data Monetization without complex (expensive) analysis?
– Who sets the Data Monetization standards?
Customer experience Critical Criteria:
Own Customer experience goals and oversee Customer experience management by competencies.
– What tools do you use once you have decided on a Data Monetization strategy and more importantly how do you choose?
– Does Data Monetization create potential expectations in other areas that need to be recognized and considered?
– When a person has a bad Customer Service experience how many people do they tell?
– How does mystery shopping help us improve our Customer Service and experience?
– What is the difference between customer experience and user experience?
– How important is real time for providing social media Customer Service?
– what is Different Between B2C B2B Customer Experience Management?
– What are the best community tools for Customer Service?
– So how do we add value to the customer experience?
– How will you measure your Data Monetization effectiveness?
– What is the internal customer experience?
– How can Customer Service be improved?
Data as a service Critical Criteria:
Experiment with Data as a service adoptions and display thorough understanding of the Data as a service process.
– Does Data Monetization include applications and information with regulatory compliance significance (or other contractual conditions that must be formally complied with) in a new or unique manner for which no approved security requirements, templates or design models exist?
– Do you monitor the effectiveness of your Data Monetization activities?
– What business benefits will Data Monetization goals deliver if achieved?
Data capitalism Critical Criteria:
Own Data capitalism quality and visualize why should people listen to you regarding Data capitalism.
– What are our best practices for minimizing Data Monetization project risk, while demonstrating incremental value and quick wins throughout the Data Monetization project lifecycle?
– In a project to restructure Data Monetization outcomes, which stakeholders would you involve?
– How does the organization define, manage, and improve its Data Monetization processes?
Data supply chain Critical Criteria:
Participate in Data supply chain risks and slay a dragon.
– For your Data Monetization project, identify and describe the business environment. is there more than one layer to the business environment?
– What are our Data Monetization Processes?
European Union Critical Criteria:
Infer European Union results and visualize why should people listen to you regarding European Union.
– A compounding model resolution with available relevant data can often provide insight towards a solution methodology; which Data Monetization models, tools and techniques are necessary?
– Does Data Monetization systematically track and analyze outcomes for accountability and quality improvement?
– Which Data Monetization goals are the most important?
Federated identity Critical Criteria:
Examine Federated identity governance and gather practices for scaling Federated identity.
– Who is the main stakeholder, with ultimate responsibility for driving Data Monetization forward?
– Have you identified your Data Monetization key performance indicators?
– Why should we adopt a Data Monetization framework?
Financial services Critical Criteria:
Look at Financial services management and gather Financial services models .
– What are your results for key measures or indicators of the accomplishment of your Data Monetization strategy and action plans, including building and strengthening core competencies?
– How likely is the current Data Monetization plan to come in on schedule or on budget?
General Motors Critical Criteria:
Face General Motors risks and finalize the present value of growth of General Motors.
– Do we monitor the Data Monetization decisions made and fine tune them as they evolve?
Gramm–Leach–Bliley Act Critical Criteria:
Depict Gramm–Leach–Bliley Act governance and report on the economics of relationships managing Gramm–Leach–Bliley Act and constraints.
– What is the source of the strategies for Data Monetization strengthening and reform?
– What are the long-term Data Monetization goals?
Information banking Critical Criteria:
Bootstrap Information banking planning and maintain Information banking for success.
– What are your key performance measures or indicators and in-process measures for the control and improvement of your Data Monetization processes?
– Where do ideas that reach policy makers and planners as proposals for Data Monetization strengthening and reform actually originate?
– What are the disruptive Data Monetization technologies that enable our organization to radically change our business processes?
Internet of things Critical Criteria:
Debate over Internet of things engagements and get answers.
– The pharmaceutical industry is also taking advantage of digital progress. It is using IoT for supply chain security in packaging and tracking of drugs. There are new companies using computer chips in pills for tracking adherence to drug regimens and associated biometrics. Using this as an example, how will we use and protect this sensitive data?
– Sensors and the IoT add to the growing amount of monitoring data that is available to a wide range of users. How do we effectively analyze all of this data and ensure that meaningful and relevant data and decisions are made?
– How will the service discovery platforms that will be needed to deploy sensor networks impact the overall governance of the iot?
– What are the critical success factors which will support the expansion and wide adoption of IoT applications?
– How will IoT applications affect users control over their own privacy and how will they react?
– Do you believe that additional principles and requirements are necessary for iot applications?
– How to re-issue the secrete key to the device again in case of key leakage to third party?
– Is any form of notice provided to the individual prior to collection of information?
– What are the organizations that are using the Internet of Things using it for?
– What impacts on users, clients and the business must be planned for?
– What are some good open source projects for the internet of things?
– Has your organization established leadership for its IoT efforts?
– How much are companies liable vs. the consumers themselves?
– What safeguard measures are in place to ensure security?
– How do we ensure that memory bandwidth is keeping up?
– Does our wireless sensor network scale?
– Can we remove maintenance?
– Is the IoT a reality?
Location data Critical Criteria:
Deliberate over Location data results and get out your magnifying glass.
– Among the Data Monetization product and service cost to be estimated, which is considered hardest to estimate?
– Is Data Monetization Realistic, or are you setting yourself up for failure?
Market share Critical Criteria:
Consult on Market share leadership and adopt an insight outlook.
– Are the calculated sales volumes realistic, taking into account the competitive position, realistic market share, importance of customer problem/pain and stage/maturity of customer needs?
– Are there recognized Data Monetization problems?
– Are there Data Monetization problems defined?
– What drives market share?
Mobile devices Critical Criteria:
Graph Mobile devices results and shift your focus.
– Imagine you work in the Human Resources department of a company considering a policy to protect its data on employees mobile devices. in advising on this policy, what rights should be considered?
– If mobile technologies are supported, how is the software optimized for use on smartphone, tables, and other mobile devices?
– Does the tool we use provide the ability for mobile devices to access critical portions of the management interface?
Patient privacy Critical Criteria:
Shape Patient privacy quality and drive action.
– Do several people in different organizational units assist with the Data Monetization process?
– What are the record-keeping requirements of Data Monetization activities?
Personal cloud Critical Criteria:
Refer to Personal cloud leadership and attract Personal cloud skills.
– Is there any open source personal cloud software which provides privacy and ease of use 1 click app installs cross platform html5?
– Does Data Monetization analysis show the relationships among important Data Monetization factors?
– Does Data Monetization analysis isolate the fundamental causes of problems?
– What about Data Monetization Analysis of results?
Personal data vaults Critical Criteria:
Categorize Personal data vaults goals and arbitrate Personal data vaults techniques that enhance teamwork and productivity.
– What are your current levels and trends in key measures or indicators of Data Monetization product and process performance that are important to and directly serve your customers? how do these results compare with the performance of your competitors and other organizations with similar offerings?
– How do we Improve Data Monetization service perception, and satisfaction?
Privacy rights Critical Criteria:
Consult on Privacy rights outcomes and tour deciding if Privacy rights progress is made.
– Will Data Monetization have an impact on current business continuity, disaster recovery processes and/or infrastructure?
– Who is responsible for ensuring appropriate resources (time, people and money) are allocated to Data Monetization?
– What are the usability implications of Data Monetization actions?
Real time Critical Criteria:
Collaborate on Real time planning and budget for Real time challenges.
– Think about the people you identified for your Data Monetization project and the project responsibilities you would assign to them. what kind of training do you think they would need to perform these responsibilities effectively?
– Do you monitor your network in real time to detect possible intrusions or abnormalities in the performance of your system?
– How is it possible to deliver real time self service BI with a legacy RDBMS source?
– Is it important to have access to information in real time?
– What are some real time data analysis frameworks?
Retail banks Critical Criteria:
Guard Retail banks engagements and report on setting up Retail banks without losing ground.
– Can we add value to the current Data Monetization decision-making process (largely qualitative) by incorporating uncertainty modeling (more quantitative)?
– Are we Assessing Data Monetization and Risk?
Reward programs Critical Criteria:
Reorganize Reward programs leadership and define what do we need to start doing with Reward programs.
– What may be the consequences for the performance of an organization if all stakeholders are not consulted regarding Data Monetization?
– What prevents me from making the changes I know will make me a more effective Data Monetization leader?
– How to Secure Data Monetization?
Risk factors Critical Criteria:
Map Risk factors planning and probe the present value of growth of Risk factors.
– Which customers cant participate in our Data Monetization domain because they lack skills, wealth, or convenient access to existing solutions?
– Risk factors: what are the characteristics of Data Monetization that make it risky?
– How can you mitigate the risk factors?
– How much does Data Monetization help?
The Guardian Critical Criteria:
Value The Guardian management and catalog The Guardian activities.
– Consider your own Data Monetization project. what types of organizational problems do you think might be causing or affecting your problem, based on the work done so far?
– What new services of functionality will be implemented next with Data Monetization ?
Trade value Critical Criteria:
Brainstorm over Trade value outcomes and spearhead techniques for implementing Trade value.
– How do you incorporate cycle time, productivity, cost control, and other efficiency and effectiveness factors into these Data Monetization processes?
– How can you measure Data Monetization in a systematic way?
United States Congress Critical Criteria:
Conceptualize United States Congress adoptions and look in other fields.
– What will drive Data Monetization change?
Vendor relationship management Critical Criteria:
Frame Vendor relationship management projects and intervene in Vendor relationship management processes and leadership.
– Marketing budgets are tighter, consumers are more skeptical, and social media has changed forever the way we talk about Data Monetization. How do we gain traction?
Venture capital Critical Criteria:
X-ray Venture capital goals and be persistent.
– How do mission and objectives affect the Data Monetization processes of our organization?
– Is Data Monetization dependent on the successful delivery of a current project?
This quick readiness checklist is a selected resource to help you move forward. Learn more about how to achieve comprehensive insights with the Data Monetization Self Assessment:
Author: Gerard Blokdijk
CEO at The Art of Service | http://theartofservice.com
Gerard is the CEO at The Art of Service. He has been providing information technology insights, talks, tools and products to organizations in a wide range of industries for over 25 years. Gerard is a widely recognized and respected information expert. Gerard founded The Art of Service consulting business in 2000. Gerard has authored numerous published books to date.
To address the criteria in this checklist, these selected resources are provided for sources of further research and information:
Data Monetization External links:
Data Monetization in Insurance Industry | Accenture
Instarea – Big data monetization company
Why is Data Monetization Important? – Acxiom
Business intelligence External links:
CareOregon Business Intelligence
Mortgage Business Intelligence Software :: Motivity Solutions
CWS/CMS > Portal > Business Intelligence Portal
Credit card External links:
Union Plus Credit Card
Stage Credit Card – Manage your account – Home | Comenity
TD Cash Credit Card
Customer experience External links:
Do You Have a Customer Experience Title? | CustomerThink
GameStop Customer Experience Survey
The Truth About Customer Experience
Data as a service External links:
M-DaaS: Master Data as a Service Solution – D&B
Data capitalism External links:
Data capitalism is cashing in on our privacy . . . for now
[PDF]DATA CAPITALISM – Change This
European Union External links:
EUROPA – European Union website, the official EU website
European Union (EU) Export Certificate List
Federated identity External links:
Federated Identity Service | University of Colorado Boulder
UCF Federated Identity
Financial services External links:
Nebraska DHHS: Financial Services
General Motors External links:
Future Vehicles | General Motors
GBodyForum – ’78-’88 General Motors A/G-Body …
General Motors | Official Global Site | GM.com
Information banking External links:
[PDF]Income Information Banking Relationships
Internet of things External links:
Internet of Things – Microsoft Internet of Things Blog
Location data External links:
Home | Zip Code and Location Data Analytics | CDXTech
2017 Marketer’s Guide To Location Data | AdExchanger
Market share External links:
Market Share Reports in Title Insurance – HDEP …
Title Market Share
California Insurance Market Share Reports
http://www.insurance.ca.gov › … › Company and Agent/Broker Information
Mobile devices External links:
Buy LG cell phones, smartphones & mobile devices – AT&T
Business Plans for Mobile Devices – AT&T Premier …
Microsoft Office 365 for Mobile Devices, Tablets, Phones
Patient privacy External links:
Index of Patient Privacy Forms – HIPAA Compliance …
Johns Hopkins Medicine: HIPAA & Patient Privacy
Patient Privacy and HIPAA | Michigan Medicine
http://www.uofmhealth.org/news/patient privacy hipaa
Personal cloud External links:
Personal Cloud Backup Pricing, Plans & Features | Carbonite
Top 6 Personal Cloud Storage Providers – Lifewire
Seagate Personal Cloud User Manual
Privacy rights External links:
Privacy Rights Clearinghouse
Real time External links:
Real Time Quotes – NASDAQ.com
Retail banks External links:
HELP!! Credit unions differ from retail banks because …
Template:Commercial and retail banks in the United …
Reward programs External links:
Debit Card Reward Programs – List of Cards & Tips
Reward Programs – Red Bird Mission
Level 6: Salesperson Incentives and Reward Programs
Risk factors External links:
Sortable Risk Factors and Health Indicators
Shingles – Causes & Risk Factors | Everyday Health
Risk Factors – National Breast Cancer Foundation
The Guardian External links:
The Guardian Careers :: Work for us
The Guardian – Historical Newspapers
Job search | Inspiring careers on the Guardian Jobs site
Trade value External links:
Trade Value Estimate | Lexus Dealership Serving Atlanta
Subaru Trade Value | Guaranteed Trade-In Program
United States Congress External links:
Powers and Duties of the United States Congress – …
Darryl Glenn | United States Congress
[PDF]UNITED STATES CONGRESS TENTATIVE 2017 …
Vendor relationship management External links:
Vendor Relationship Management Contact – Healthfuse
Venture capital External links:
Healthcare Venture Capital | 7wire Ventures
Venture Capitalist – Investopedia