Save time, empower your teams and effectively upgrade your processes with access to this practical Data Monetization Toolkit and guide. Address common challenges with best-practice templates, step-by-step work plans and maturity diagnostics for any Data Monetization related project.
Download the Toolkit and in Three Steps you will be guided from idea to implementation results.
The Toolkit contains the following practical and powerful enablers with new and updated Data Monetization specific requirements:
STEP 1: Get your bearings
Start with...
- The latest quick edition of the Data Monetization Self Assessment book in PDF containing 49 requirements to perform a quickscan, get an overview and share with stakeholders.
Organized in a data driven improvement cycle RDMAICS (Recognize, Define, Measure, Analyze, Improve, Control and Sustain), check the…
- Example pre-filled Self-Assessment Excel Dashboard to get familiar with results generation
Then find your goals...
STEP 2: Set concrete goals, tasks, dates and numbers you can track
Featuring 994 new and updated case-based questions, organized into seven core areas of process design, this Self-Assessment will help you identify areas in which Data Monetization improvements can be made.
Examples; 10 of the 994 standard requirements:
- Can data standardization be achieved through a cloud-based or as-a-service model, where standardized data capabilities are provided as a centralized service to different business units or teams, and if so, what are the benefits and limitations of this approach?
- Can data standardization be achieved through a decentralized or federated approach, where different business units or teams are responsible for standardizing their own data, and if so, what are the benefits and drawbacks of this approach?
- What is the role of data governance in informating our approach to data-driven product and service development, and how will we ensure that our data governance policies and procedures are aligned with our development roadmap?
- Can data standardization be achieved through a hybrid approach, combining standardized data models with customized or bespoke data analytics capabilities, and if so, what are the benefits and limitations of this approach?
- What are the key performance indicators (KPIs) that we should use to evaluate the success of our data experimentation and innovation initiatives, and how will we balance these KPIs with those of stability and reliability?
- In what ways can data standardization enable or restrict collaboration and knowledge-sharing between different business units or teams, and how can we optimize standardization efforts for cross-functional collaboration?
- What is the role of customer education and support in the development and launch of new data-driven products and services, and how will we ensure that customers are able to effectively use these products and services?
- How can we balance the need for data standardization with the need for domain-specific or specialized analytics capabilities, and how can we optimize standardization efforts for specific business domains or use cases?
- What kind of transparency and trustworthiness will we provide in circumstances where our data analytics and machine learning capabilities are used in decision-making processes that affect large populations or groups?
- What are the benefits and drawbacks of adopting a layered or hierarchical approach to data standardization, where standardized data models or taxonomies are applied at different levels of granularity or abstraction?
Complete the self assessment, on your own or with a team in a workshop setting. Use the workbook together with the self assessment requirements spreadsheet:
- The workbook is the latest in-depth complete edition of the Data Monetization book in PDF containing 994 requirements, which criteria correspond to the criteria in...
Your Data Monetization self-assessment dashboard which gives you your dynamically prioritized projects-ready tool and shows your organization exactly what to do next:
- The Self-Assessment Excel Dashboard; with the Data Monetization Self-Assessment and Scorecard you will develop a clear picture of which Data Monetization areas need attention, which requirements you should focus on and who will be responsible for them:
- Shows your organization instant insight in areas for improvement: Auto generates reports, radar chart for maturity assessment, insights per process and participant and bespoke, ready to use, RACI Matrix
- Gives you a professional Dashboard to guide and perform a thorough Data Monetization Self-Assessment
- Is secure: Ensures offline data protection of your Self-Assessment results
- Dynamically prioritized projects-ready RACI Matrix shows your organization exactly what to do next:
STEP 3: Implement, Track, follow up and revise strategy
The outcomes of STEP 2, the self assessment, are the inputs for STEP 3; Start and manage Data Monetization projects with the 62 implementation resources:
- 62 step-by-step Data Monetization Project Management Form Templates covering over 1500 Data Monetization project requirements and success criteria:
Examples; 10 of the check box criteria:
- Probability and Impact Matrix: What should be the gestation period for the Data Monetization project with this technology?
- Stakeholder Management Plan: What potential impact does the Data Monetization project have on the stakeholder?
- Procurement Audit: Must the receipt of goods be approved prior to payment?
- Cost Estimating Worksheet: Will the Data Monetization project collaborate with the local community and leverage resources?
- Quality Audit: How does your organization know that its system for attending to the health and wellbeing of its staff is appropriately effective and constructive?
- Scope Management Plan: Has the scope management document been updated and distributed to help prevent scope creep?
- Lessons Learned: What would you like to see better documented about how to use existing processes on this type of Data Monetization project?
- Activity Duration Estimates: Which best describes the relationship between standard deviation and risk?
- Scope Management Plan: Are calculations and results of analyzes essentially correct?
- Team Member Performance Assessment: To what degree is the team cognizant of small wins to be celebrated along the way?
Step-by-step and complete Data Monetization Project Management Forms and Templates including check box criteria and templates.
1.0 Initiating Process Group:
- 1.1 Data Monetization project Charter
- 1.2 Stakeholder Register
- 1.3 Stakeholder Analysis Matrix
2.0 Planning Process Group:
- 2.1 Data Monetization project Management Plan
- 2.2 Scope Management Plan
- 2.3 Requirements Management Plan
- 2.4 Requirements Documentation
- 2.5 Requirements Traceability Matrix
- 2.6 Data Monetization project Scope Statement
- 2.7 Assumption and Constraint Log
- 2.8 Work Breakdown Structure
- 2.9 WBS Dictionary
- 2.10 Schedule Management Plan
- 2.11 Activity List
- 2.12 Activity Attributes
- 2.13 Milestone List
- 2.14 Network Diagram
- 2.15 Activity Resource Requirements
- 2.16 Resource Breakdown Structure
- 2.17 Activity Duration Estimates
- 2.18 Duration Estimating Worksheet
- 2.19 Data Monetization project Schedule
- 2.20 Cost Management Plan
- 2.21 Activity Cost Estimates
- 2.22 Cost Estimating Worksheet
- 2.23 Cost Baseline
- 2.24 Quality Management Plan
- 2.25 Quality Metrics
- 2.26 Process Improvement Plan
- 2.27 Responsibility Assignment Matrix
- 2.28 Roles and Responsibilities
- 2.29 Human Resource Management Plan
- 2.30 Communications Management Plan
- 2.31 Risk Management Plan
- 2.32 Risk Register
- 2.33 Probability and Impact Assessment
- 2.34 Probability and Impact Matrix
- 2.35 Risk Data Sheet
- 2.36 Procurement Management Plan
- 2.37 Source Selection Criteria
- 2.38 Stakeholder Management Plan
- 2.39 Change Management Plan
3.0 Executing Process Group:
- 3.1 Team Member Status Report
- 3.2 Change Request
- 3.3 Change Log
- 3.4 Decision Log
- 3.5 Quality Audit
- 3.6 Team Directory
- 3.7 Team Operating Agreement
- 3.8 Team Performance Assessment
- 3.9 Team Member Performance Assessment
- 3.10 Issue Log
4.0 Monitoring and Controlling Process Group:
- 4.1 Data Monetization project Performance Report
- 4.2 Variance Analysis
- 4.3 Earned Value Status
- 4.4 Risk Audit
- 4.5 Contractor Status Report
- 4.6 Formal Acceptance
5.0 Closing Process Group:
- 5.1 Procurement Audit
- 5.2 Contract Close-Out
- 5.3 Data Monetization project or Phase Close-Out
- 5.4 Lessons Learned
Results
With this Three Step process you will have all the tools you need for any Data Monetization project with this in-depth Data Monetization Toolkit.
In using the Toolkit you will be better able to:
- Diagnose Data Monetization projects, initiatives, organizations, businesses and processes using accepted diagnostic standards and practices
- Implement evidence-based best practice strategies aligned with overall goals
- Integrate recent advances in Data Monetization and put process design strategies into practice according to best practice guidelines
Defining, designing, creating, and implementing a process to solve a business challenge or meet a business objective is the most valuable role; In EVERY company, organization and department.
Unless you are talking a one-time, single-use project within a business, there should be a process. Whether that process is managed and implemented by humans, AI, or a combination of the two, it needs to be designed by someone with a complex enough perspective to ask the right questions. Someone capable of asking the right questions and step back and say, 'What are we really trying to accomplish here? And is there a different way to look at it?'
This Toolkit empowers people to do just that - whether their title is entrepreneur, manager, consultant, (Vice-)President, CxO etc... - they are the people who rule the future. They are the person who asks the right questions to make Data Monetization investments work better.
This Data Monetization All-Inclusive Toolkit enables You to be that person.
Includes lifetime updates
Every self assessment comes with Lifetime Updates and Lifetime Free Updated Books. Lifetime Updates is an industry-first feature which allows you to receive verified self assessment updates, ensuring you always have the most accurate information at your fingertips.
