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 137 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:
Dissect Data Monetization management and explore and align the progress in Data Monetization.
– What are the disruptive Data Monetization technologies that enable our organization to radically change our business processes?
– Do those selected for the Data Monetization team have a good general understanding of what Data Monetization is all about?
– Why are Data Monetization skills important?
Business intelligence Critical Criteria:
Nurse Business intelligence leadership and report on developing an effective Business intelligence strategy.
– Does your BI solution honor distinctions with dashboards that automatically authenticate and provide the appropriate level of detail based on a users privileges to the data source?
– Are NoSQL databases used primarily for applications or are they used in Business Intelligence use cases as well?
– Does your bi solution require weeks of training before new users can analyze data and publish dashboards?
– What are some successful business intelligence BI apps that have been built on an existing platform?
– Are business intelligence solutions starting to include social media data and analytics features?
– What is the difference between business intelligence business analytics and data mining?
– What is the difference between Enterprise Information Management and Data Warehousing?
– What is the difference between business intelligence and business analytics?
– What are some common criticisms of Sharepoint as a knowledge sharing tool?
– Does creating or modifying reports or dashboards require a reporting team?
– Who prioritizes, conducts and monitors business intelligence projects?
– Describe the process of data transformation required by your system?
– Is Data Warehouseing necessary for a business intelligence service?
– What are the pillar concepts of business intelligence?
– How stable is it across domains/geographies?
– What is required to present video images?
– Do you offer formal user training?
– Do you support video integration?
– What is your annual maintenance?
– Does your system provide APIs?
Credit card Critical Criteria:
Facilitate Credit card visions and research ways can we become the Credit card company that would put us out of business.
– What are our best practices for minimizing Data Monetization project risk, while demonstrating incremental value and quick wins throughout the Data Monetization project lifecycle?
– If credit card payments are accepted, do we currently have a payment gateway?
– Will mobile payments ever replace credit cards?
– How can skill-level changes improve Data Monetization?
– Who needs to know about Data Monetization ?
Crowd sourced Critical Criteria:
Accommodate Crowd sourced engagements and forecast involvement of future Crowd sourced projects in development.
– For your Data Monetization project, identify and describe the business environment. is there more than one layer to the business environment?
– How do we measure improved Data Monetization service perception, and satisfaction?
Customer experience Critical Criteria:
Mine Customer experience results and report on setting up Customer experience without losing ground.
– Is maximizing Data Monetization protection the same as minimizing Data Monetization loss?
– Do the Data Monetization decisions we make today help people and the planet tomorrow?
– 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?
– How important is real time for providing social media Customer Service?
– What is the difference between customer experience and user experience?
– Will Data Monetization deliverables need to be tested and, if so, by whom?
– 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?
– What is the internal customer experience?
– How can Customer Service be improved?
Data as a service Critical Criteria:
Focus on Data as a service management and get answers.
– 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?
– What sources do you use to gather information for a Data Monetization study?
– Can we do Data Monetization without complex (expensive) analysis?
Data capitalism Critical Criteria:
Consolidate Data capitalism tactics and slay a dragon.
– Does Data Monetization analysis show the relationships among important Data Monetization factors?
– To what extent does management recognize Data Monetization as a tool to increase the results?
– What are the long-term Data Monetization goals?
Data supply chain Critical Criteria:
Communicate about Data supply chain governance and ask what if.
– Do we cover the five essential competencies-Communication, Collaboration,Innovation, Adaptability, and Leadership that improve an organizations ability to leverage the new Data Monetization in a volatile global economy?
– What other jobs or tasks affect the performance of the steps in the Data Monetization process?
– How will you know that the Data Monetization project has been successful?
European Union Critical Criteria:
Accumulate European Union decisions and proactively manage European Union risks.
– Record-keeping requirements flow from the records needed as inputs, outputs, controls and for transformation of a Data Monetization process. ask yourself: are the records needed as inputs to the Data Monetization process available?
– What tools do you use once you have decided on a Data Monetization strategy and more importantly how do you choose?
– Do several people in different organizational units assist with the Data Monetization process?
Federated identity Critical Criteria:
Rank Federated identity projects and oversee Federated identity requirements.
– What potential environmental factors impact the Data Monetization effort?
– Does Data Monetization appropriately measure and monitor risk?
– Have all basic functions of Data Monetization been defined?
Financial services Critical Criteria:
Devise Financial services results and mentor Financial services customer orientation.
– Are we making progress? and are we making progress as Data Monetization leaders?
– What business benefits will Data Monetization goals deliver if achieved?
General Motors Critical Criteria:
Investigate General Motors engagements and get going.
– What are the business goals Data Monetization is aiming to achieve?
– How much does Data Monetization help?
Gramm–Leach–Bliley Act Critical Criteria:
Check Gramm–Leach–Bliley Act failures and pay attention to the small things.
– Where do ideas that reach policy makers and planners as proposals for Data Monetization strengthening and reform actually originate?
– Why is Data Monetization important for you now?
Information banking Critical Criteria:
Contribute to Information banking leadership and tour deciding if Information banking progress is made.
– 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 we aggressively reward and promote the people who have the biggest impact on creating excellent Data Monetization services/products?
– What are the success criteria that will indicate that Data Monetization objectives have been met and the benefits delivered?
Internet of things Critical Criteria:
Deduce Internet of things visions and point out improvements in Internet of things.
– Even the most security-conscious sectors may be unprepared for the security impact that IoT connected devices can have. So what can we do to protect IoT solutions?
– Will IT be a partner, driving business value, building an IoT architecture and collaborating on greenfield projects?
– What are the organizations that are using the Internet of Things using it for?
– Disaster recovery site–what happens if contractors server is destroyed?
– Do you monitor the effectiveness of your Data Monetization activities?
– How would a society benefit from an AI that passes the Turing test?
– What are the expectations regarding the protection of the data?
– Have you established a Center of Excellence (COE) for the IoT?
– What does a good Internet of Things strategy include?
– Design for networking agnosticism: what is in a thing?
– Which user group(s) will have access to the system?
– How can the RoI of IoT applications be assessed and measured?
– What market segment(s) are served by the company?
– What are the major components of IoT?
– What customer support will be needed?
– How do I find sensor services?
– What can we do to protect IoT solutions?
– How will you access customers?
– What does a sensor look like?
– How to define the iot?
Location data Critical Criteria:
Think about Location data failures and visualize why should people listen to you regarding Location data.
– Who is responsible for ensuring appropriate resources (time, people and money) are allocated to Data Monetization?
– Risk factors: what are the characteristics of Data Monetization that make it risky?
– How to deal with Data Monetization Changes?
Market share Critical Criteria:
Consult on Market share projects and correct Market share management by competencies.
– 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?
– Is there a Data Monetization Communication plan covering who needs to get what information when?
– In what ways are Data Monetization vendors and us interacting to ensure safe and effective use?
– What drives market share?
Mobile devices Critical Criteria:
Devise Mobile devices strategies and forecast involvement of future Mobile devices projects in development.
– 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?
– Among the Data Monetization product and service cost to be estimated, which is considered hardest to estimate?
– Who sets the Data Monetization standards?
Patient privacy Critical Criteria:
Depict Patient privacy adoptions and oversee Patient privacy management by competencies.
– What is the source of the strategies for Data Monetization strengthening and reform?
– Is Data Monetization Realistic, or are you setting yourself up for failure?
– How is the value delivered by Data Monetization being measured?
Personal cloud Critical Criteria:
Probe Personal cloud tactics and separate what are the business goals Personal cloud is aiming to achieve.
– Is there any open source personal cloud software which provides privacy and ease of use 1 click app installs cross platform html5?
– Can Management personnel recognize the monetary benefit of Data Monetization?
Personal data vaults Critical Criteria:
Reconstruct Personal data vaults failures and finalize the present value of growth of Personal data vaults.
– How does the organization define, manage, and improve its Data Monetization processes?
– What will drive Data Monetization change?
– Why should we adopt a Data Monetization framework?
Privacy rights Critical Criteria:
Weigh in on Privacy rights strategies and learn.
– Are there any disadvantages to implementing Data Monetization? There might be some that are less obvious?
Real time Critical Criteria:
Generalize Real time projects and get going.
– 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?
– How do we know that any Data Monetization analysis is complete and comprehensive?
– Is it important to have access to information in real time?
– What are some real time data analysis frameworks?
– How to Secure Data Monetization?
Retail banks Critical Criteria:
Review Retail banks projects and forecast involvement of future Retail banks projects in development.
– When a Data Monetization manager recognizes a problem, what options are available?
Reward programs Critical Criteria:
Depict Reward programs projects and work towards be a leading Reward programs expert.
– What are your most important goals for the strategic Data Monetization objectives?
– Who will be responsible for documenting the Data Monetization requirements in detail?
– What is Effective Data Monetization?
Risk factors Critical Criteria:
Demonstrate Risk factors adoptions and interpret which customers can’t participate in Risk factors because they lack skills.
– How do we Improve Data Monetization service perception, and satisfaction?
– How do we manage Data Monetization Knowledge Management (KM)?
– How can you mitigate the risk factors?
The Guardian Critical Criteria:
Differentiate The Guardian risks and assess what counts with The Guardian that we are not counting.
– How can you measure Data Monetization in a systematic way?
Trade value Critical Criteria:
Unify Trade value quality and drive action.
– What are our Data Monetization Processes?
United States Congress Critical Criteria:
Shape United States Congress issues and create United States Congress explanations for all managers.
– Does Data Monetization create potential expectations in other areas that need to be recognized and considered?
– What are the barriers to increased Data Monetization production?
– Which Data Monetization goals are the most important?
Vendor relationship management Critical Criteria:
Substantiate Vendor relationship management visions and display thorough understanding of the Vendor relationship management process.
– What is the purpose of Data Monetization in relation to the mission?
Venture capital Critical Criteria:
Air ideas re Venture capital decisions and correct better engagement with Venture capital results.
– How can you negotiate Data Monetization successfully with a stubborn boss, an irate client, or a deceitful coworker?
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
mnubo – IoT Data Monetization
The Key to Data Monetization – KDnuggets
Business intelligence External links:
Mortgage Business Intelligence Software :: Motivity Solutions
List of Business Intelligence Skills – The Balance
Credit card External links:
Welcome! Manage your Justice credit card Account here.
Value City Furniture credit card – Manage your account
Crowd sourced External links:
Crowd Sourced Analytics – LiveShopper
Customer experience External links:
Customer Experience Is… What, Exactly?
The Truth About Customer Experience
Customer Experience Jobs, Employment | Indeed.com
Data as a service External links:
DaaS: Contact Informatica Data as a Service
BrightPlanet – Deep Web Data Collection & Data as a Service
Data capitalism External links:
[PDF]DATA CAPITALISM – Change This
Data capitalism is cashing in on our privacy . . . for now
Data Capitalism – revolvy.com
Data supply chain External links:
[PDF]Data supply chain in Industrial Internet – cps-vo.org
European Union External links:
European Union (EU) Export Certificate List
EUROPA – European Union website, the official EU website
Federated identity External links:
Federated Identity for Web Applications – msdn.microsoft.com
[PDF]Federated Identity Management – UAH – Computer …
Federated Identity Service | University of Colorado Boulder
Financial services External links:
Honda Financial Services – Official Site
L&N Federal Credit Union – Louisville, KY – Financial Services
Springleaf Financial Services
General Motors External links:
General Motors | Official Global Site | GM.com
General Motors – Home | Facebook
Information banking External links:
[PDF]Income Information Banking Relationships
Internet of things External links:
AT&T M2X: Build solutions for the Internet of Things
Internet of Things – Microsoft Internet of Things Blog
Location data External links:
Home – SafeGraph | High-Accuracy Location Data
Home | Zip Code and Location Data Analytics | CDXTech
Market share External links:
Property Insight : Marketing Products : Title Market Share
Market Share | Title Data
California Insurance Market Share Reports
http://www.insurance.ca.gov › … › Company and Agent/Broker Information
Mobile devices External links:
Microsoft Office 365 for Mobile Devices, Tablets, Phones
Buy LG cell phones, smartphones & mobile devices – AT&T
QuickSale – Payment solutions for all mobile devices
Patient privacy External links:
Index of Patient Privacy Forms – HIPAA Compliance …
Proactive Patient Privacy Analytics | Protenus
Patient Privacy: A Guide for Providers – medscape.org
Personal cloud External links:
Personal Cloud – FREE download Personal Cloud
Personal Cloud Backup Pricing, Plans & Features | Carbonite
Privacy rights External links:
Report a Privacy Rights Violation | Facebook
L.L.Bean: Your Privacy Rights
Privacy Rights Clearinghouse
Real time External links:
Real Time Quotes – NASDAQ.com
Reward programs External links:
Incentive and Reward Programs | Quality Incentive Company
UECU’s Reward Programs | Utilities Employees Credit Union
RewardsNOW, Dover, NH – Reward Programs, Rewards …
Risk factors External links:
WHO | Risk factors
Risk Factors – National Breast Cancer Foundation
Alzheimer’s Disease: Genetics and Risk Factors – WebMD
The Guardian External links:
The Guardian – Historical Newspapers
Genesis HealthCare > The Guardian Center
The Guardian GT Is the Most Bonkers Robot on Earth | WIRED
Trade value External links:
2017 NFL Draft Trade Value Chart
Subaru Trade Value | Guaranteed Trade-In Program
United States Congress External links:
House Resolution 257 – United States Congress
Members of the United States Congress – GovTrack.us
[PDF]UNITED STATES CONGRESS TENTATIVE 2017 …
Venture capital External links:
Healthcare Venture Capital | 7wire Ventures
the PVCA – Pittsburgh Venture Capital Association
Venture Capital – Mashable