Implementation Plan - from Strategy to Practice

Objective

Background

June 2018: EMC approves the PSC Data Management Strategy*

Fall 2018: A GC Data Strategy Roadmap is released

Winter 2018:

*Please refer to Annex A for the Data Management Strategy drivers and vision.

GC Data Strategy Roadmap

Formally known as the “Report to the Clerk of the Privy Council: A Data Strategy Roadmap for the Federal Public Service”, the GC Data Strategy and its recommendations were submitted to the Clerk and accepted in fall of 2018.

The Roadmap provides 21 recommendations that are structured around four themes:

Departmental requirements by September 2019:

PSC Context

In 2014-2015, the PSC conducted a review of its policy and oversight frameworks. The objective of the review was to strengthen the staffing system’s responsiveness to organizational context and operational risks.

The result of this review, a New Direction in Staffing, was a sensible deregulation of the staffing system which aims to provide hiring managers with the discretion to choose the resourcing strategy that best supports their organizational outcomes.

For hiring managers, exercising greater discretion will entail a transition from supporting a values-based staffing system in a regulated environment to values-based decision making where competing values may be at play.

Why is data important for the PSC?

Although our staffing environment has changed, the desired outcomes of the staffing system remain the same:

Leveraging data to ‘nudge’ the staffing environment

To keep in mind as we move forward

It is by optimizing the use of its data that the PSC will be better positioned to develop relevant and innovative products, services and guidance to assist departments in addressing their operational realities.

In planning the implementation of the Data Management Strategy, the Executive Management Committee stressed the importance of the:

The Human Aspect 

Risk tolerance for an error

Ethical use of data remains a priority

As interest in staffing data increases, a reflection that goes beyond privacy and security issues is required to better define the conditions under which PSC data can and should be used and shared.

Guidelines and templates for Data Sharing Agreements will be developed to capture:

In addition, we will:

Where are we now?

Data Management:

Page Break Data Infrastructure:

Data Users:

Proposed Phases and key deliverables

(See Annex B for priorities and timelines)

Phase 1: Establish the Foundation (2019-2020)

Phase 2: Build Momentum (2020-2021)

Phase 3: Assess Progress and Adjust (2021-2022)

Next Steps

  1. Develop Project Charter
  2. Establish Project Plan
  3. Report on progress to the data governance

Annex A - PSC Data Management Strategy

Drivers and Vision

PSC drivers for a data strategy

From: 

Trought:

To:

Expected outcomes

Vision: the right data, the right way, in the right hands, at the right time

Figure 1:

Elements of PSC’s Data Management Strategy

Figure 1: Elements of PSC’s Data Management Strategy
Text Alternative

Sub-elements related to Data Infrastructure are definition of Business Requirements, Enabling Technologies and Reporting Tools.

Sub-elements related to Data Users are Self-service, "Open by Default" Culture and Value added data and information.

Sub-elements related to Data Management are Vision & Governance, Roles & Responsibilities and Data Integrity including Quality, Security and Privacy.

The sub-elements related to the Office of Data Management are the Cultural Change, Project Management, Performance Measurement and GOC Alignment.

Foundational elements of data infrastructure

Figure 2:

Data Infrastructure Concept 

Figure 2: Data Infrastructure Concept 
Text Alternative

The data is PSRS, PIMS, PPC Systems, Phoenix and other.

The data holdings (the data lake) are IM compliant, centralize and harmonize.

The analytical hub depersonalizes, transforms, aggregates and analyzes.

Making data available: data is shared and leveraged and is available on a data portal and self-serve.

Users are citizens, management, employees, departments, internal/external business lines, policy makers and researchers.

Annex B - PSC Data Management Strategy Proposed Priorities and Timelines

Phase 1: Establish the foundation - Data management
Actions Activities Timeline
Clarify data responsibilities Define CDO and data actors’ R&R including supporting the PSC data sharing protocol April to May 2019
Assess current situation Assess PSC data risks /self-assessment 1st May to August 2019 and September 2019 to January 2020
Conduct PSC data management maturity diagnostic / self assessment 1st May to August 2019 and September 2019 to January 2020
Develop action plans/mitigation strategies January to March 2020
Review privacy notice statements December 2019 to April 2020
Plan Develop Results Measurement Framework April to August 2019
Develop Change Management/ Communications Strategy June to December 2019
Establish corporate list of data agreements July to September 2019
Create templates and guidelines for data sharing within and outside the PSC July 2019 to January 2020
Implement mechanisms to mitigate duplication of data holdings December 2019 to April 2020
Phase 1: Establish the foundation - Data infrastructure
Actions Timeline
Initiate feasibility assessment for Data Lake - PIMS March to July 2019
Initiate PSC Corporate Data Asset Inventory July 2019 to April 2020
Phase 1: Establish the foundation - Data users
Actions Activities Timeline
Assess state of data literacy Conduct analysis of Baseline Survey results March to April 2019
Develop PSC Data Literacy Plan April to July 2019
Develop data literacy material (one module at a time - start with data quality) July 2019 to January 2020
Deliver learning modules October 2019 to April 2020
Release data of value Engage to provide value-added data March to September 2019
Update open datasets and release new ones September 2019 to April 2020
Strengthen analytical capacity Develop and implement a competency-based framework for data analysts/scientists March 2019 to April 2020
Strengthen analytical capacity Establish sandbox to test and procure advanced analytical and visualization tools March to September 2019
Phase 2 priorities: Build momentum- Data management
Actions Activities Timeline
Develop PSC Policy on Data Quality April 2020 to January 2021
Continue implementation of action plans/mitigation strategies to address Risks findings March 2020 to April 2021
Maturity diagnostic findings March 2020 to April 2021
Implement Change Management/Communications Strategy activities March to October 2020
Assess progress against Results Measurement Framework for DMS October 2020 to April 2021
Phase 2 priorities: Build momentum- Data infrastructure
Actions Timeline
Implement Data Lake environment July 2020 to April 2021
Establish Master Data Management Plan April 2020 to January 2021
Develop PSC Policy on Data Security and Privacy April 2020 to January 2021
Phase 3 priorities: Assess and adjust - Data management
Actions Activities Timeline
Assess PSC data literacy progress Administer and analyze second survey results April to July 2021
Align PSC Data Strategy with GC direction Update PSC Data Strategy and align with GC direction and PSC needs July to December 2021
Phase 3 priorities: Assess and adjust - Data infrastructure
Actions Activities Timeline
Onboard new data holdings in the Data Lake Data holding(s) TBD April 2021 to April 2022
Expand data management practices Establish organizational norms regarding the capture and use of metadata April to October 2021
Implement and standardize Reference Tables for Classifications, Regions, Departments April 2021 to January 2022
Phase 3 priorities: Assess and adjust - Data users
Actions Timeline
Assess the outcomes of the Strategy April 2021 to April 2022
Report a problem or mistake on this page
Please select all that apply:

Thank you for your help!

You will not receive a reply. For enquiries, contact us.

Date modified: