Save time, empower your teams and effectively upgrade your processes with access to this practical Computational biology Toolkit and guide. Address common challenges with best-practice templates, step-by-step work plans and maturity diagnostics for any Computational biology 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 Computational biology specific requirements:
STEP 1: Get your bearings
- The latest quick edition of the Computational biology 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 633 new and updated case-based questions, organized into seven core areas of process design, this Self-Assessment will help you identify areas in which Computational biology improvements can be made.
Examples; 10 of the 633 standard requirements:
- Who will be using the results of the measurement activities?
- Is the team adequately staffed with the desired cross-functionality? If not, what additional resources are available to the team?
- How do we link Measurement and Risk?
- We picked a method, now what?
- Why is Computational biology important for you now?
- In a project to restructure Computational biology outcomes, which stakeholders would you involve?
- Are there any disadvantages to implementing Computational biology? There might be some that are less obvious?
- Is a solid data collection plan established that includes measurement systems analysis?
- What is the purpose of Computational biology in relation to the mission?
- Is there a standardized process?
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 Computational biology book in PDF containing 633 requirements, which criteria correspond to the criteria in...
Your Computational biology 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 Computational biology Self-Assessment and Scorecard you will develop a clear picture of which Computational biology 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 Computational biology 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 Computational biology projects with the 62 implementation resources:
- 62 step-by-step Computational biology Project Management Form Templates covering over 6000 Computational biology project requirements and success criteria:
Examples; 10 of the check box criteria:
- Stakeholder Management Plan: What is the difference between product and Computational biology project scope?
- Assumption and Constraint Log: Have the scope, objectives, costs, benefits and impacts been communicated to all involved and/or impacted stakeholders and work groups?
- Stakeholder Analysis Matrix: Do the stakeholders goals and expectations support or conflict with the Computational biology project goals?
- Probability and Impact Assessment: Which of your Computational biology projects should be selected when compared with other Computational biology projects?
- Procurement Audit: Is an appropriated degree of standardization of goods and services respected?
- Schedule Management Plan: Who is responsible for estimating the activity resources?
- Stakeholder Analysis Matrix: Who is influential in the Computational biology project area (both thematic and geographic areas)?
- Project Scope Statement: Is there a Quality Assurance Plan documented and filed?
- Stakeholder Management Plan: Why is it important to reduce deliverables to a smallest component?
- WBS Dictionary: Does the contractor use objective results, design reviews and tests to trace schedule performance?
Step-by-step and complete Computational biology Project Management Forms and Templates including check box criteria and templates.
1.0 Initiating Process Group:
- 1.1 Computational biology project Charter
- 1.2 Stakeholder Register
- 1.3 Stakeholder Analysis Matrix
2.0 Planning Process Group:
- 2.1 Computational biology project Management Plan
- 2.2 Scope Management Plan
- 2.3 Requirements Management Plan
- 2.4 Requirements Documentation
- 2.5 Requirements Traceability Matrix
- 2.6 Computational biology 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 Computational biology 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 Computational biology 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 Computational biology project or Phase Close-Out
- 5.4 Lessons Learned
With this Three Step process you will have all the tools you need for any Computational biology project with this in-depth Computational biology Toolkit.
In using the Toolkit you will be better able to:
- Diagnose Computational biology 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 Computational biology 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 Computational biology investments work better.
This Computational biology 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.