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The 12 ½ labours of WIDE are a set of the major challenges faced by quality referral services and the answers addressed to each one of them by WIDE's platform's roster management functions.
- How to deal with the diversity of rosters and why
- How to integrate the rosters and still accommodate particular requirements
- Why to create common data standards and how
- How to use taxonomy for the skills sets
- How to establish membership criteria
- How to manage the resume self-service entry
- How to manage recommendations
- How to manage queries and referrals
- How to manage communication with roster members
- How to ensure security
- What are the adequate Terms of Service
- How to track the request performance
12 ½. How to migrate data from existing databases
The 12 ½ labours of WIDE were identified throughout the process of the reengineering of WIDE started in November 2002.
- Why so many different rosters?
- Is there a way to improve cooperation in roster maintenance?
- How to consolidate roster management good practices?
- Is there a way to share and protect the investment (money, work, data)?
- Why so many diverse platforms?
- How to build upon experience on roster management?
- Is it better to have large or small data bases?
- Does it have to be separate or integrated?
- How to accommodate specific data requirements?
- Should it supply data to other databases?
- Can we have access to other databases?
- Can members migrate from one roster to others?
- Can the same expert be listed in different rosters?
- Can recommendations also migrate?
- How can we compare different resumes?
- How to map competencies?
- How can we exchange data?
- How can we preserve the data collected?
- How can we preserve the investment on collecting data in face of future innovations?
- How to facilitate the reuse of provided data to the members?
- How to evaluate quality based on diverse presentations?
- How to focus a roster on specific areas of skills?
- Is there a common way to describe skills, qualifications, experiences or competences?
- How to facilitate the matching of the right profile?
- How difficult is it to change a taxonomy strategy in the future?
- How to ensure common understanding in describing skills? (e.g. languages)
- How to facilitate comparison of different competences in the search for the right expert?
- Is there a common set of criteria?
- Should we have a membership agreement? (Rights to hold and give access to data of members? Certifying of true and complete information?)
- How to evolve judgment with practice?
- How to face reactions of turned-down registrations?
- How to promote consistent roster quality?
- Should we make criteria public?
- Should we include companies? (or just non-profit institutions?)
- Should we mobilize participation pro-actively?
- How to share subjective judgment?
- How to ensure adequate data quality?
- How to guarantee adequate security?
- How to promote updating?
- How to transfer to the members the data entry tasks?
- How to ensure the quality of recommendations?
- Should we keep a roster of recommenders?
- Who should be allowed to recommend?
- How to share the recommendations data entry task with the recommenders?
- How to improve comparability of recommendations?
- Who should be able to query?
- Who answers request of referrals?
- Who should contact members?
- Should we follow-up referrals?
- Should we protect members' privacy? (e.g. e-mail, address)
- What is the best way to communicate with members?
- Is e-mail enough?
- Is there an easy way to manage e-mail? (dynamic sub-set of members)
- Who should be able to initiate communication?
- Who is accountable?
- Should we share it?
- How to share communication templates?
- What are the best ways to mobilize members?
- How to protect the database?
- Should there be a full-time roster manager?
- Should we work with dispersed teams?
- How to distribute the roster manager functions to teams?
- Who will provide support?
- What is the reasonable access availability?
- How to prove quality of reports? (Informal notes)
- Should we confirm referrals?
- Is there a standard/format for referrals?
- How to encourage feedbacks?
- How to maintain meaningful feedback?
- What to do with negative feedback?
- Should we follow-up referrals?
- How can we build upon existing work?
- How can we make the most of the existing data?
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