- Lisa Bobo, CIO, City of Rochester
- Stephen Burt, Assistant Deputy Minister, Data, Innovation, and Analytics, and Chief Data Officer, Department of National Defence, Government of Canada
- Dr. Irshad Siddiqui, Chief Health Information Officer (CHIO), Blessing Health System
- Head of Enterprise Information Management at an African central bank
- The volume and variety of data that organizations have been collecting and producing have been growing exponentially and show no sign of slowing down.
- At the same time, business landscapes and models are evolving, and users and stakeholders are becoming more and more data centric, with maturing expectations and demands.
- As the CDO or equivalent data leader in your organization, a robust and comprehensive data strategy is the number one tool in your toolkit for delivering on your mandate of creating measurable business value from data.
- A data strategy should never be formulated disjointed from the business. Ensure the data strategy aligns with the business strategy and supports the business architecture.
- Building and fostering a data-driven culture will accelerate and sustain adoption of, appetite for, and appreciation for data and hence drive the ROI on your various data investments.
Impact and Result
- Formulate a data strategy that stitches all of the pieces together to better position you to unlock the value in your data:
- Establish the business context and value: Identify key business drivers for executing on an optimized data strategy, build compelling and relevant use cases, understand your organization’s culture and appetite for data, and ensure you have well-articulated vision, principles, and goals for your data strategy
- Ensure you have a solid data foundation: Understand your current data environment, data management enablers, people, skill sets, roles, and structure. Know your strengths and weakness so you can optimize appropriately.
- Formulate a sustainable data strategy: Round off your strategy with effective change management and communication for building and fostering a data-driven culture.
This guided implementation is a nine call advisory process.
Guided Implementation #1 - Establish Business Context and Value
Call #1 - Understand what a data strategy is and why it needs to be aligned with the organizational strategy.
Call #2 - Identify the business drivers that necessitate optimizing the data strategy.
Call #3 - Create a tactical plan to optimize data architecture across Info-Tech’s five-tier logical data architecture model.
Guided Implementation #2 - Ensure You Have a Solid Data and Resources Foundation
Call #1 - Understand the key enablers of data management as well as the required resources portfolio: people and skill sets.
Call #2 - Determine the current state of your environment: data management enablers, people and data organizational structure, and data culture.
Call #3 - Understand the risk and feasibility as they relate to the data strategy.
Guided Implementation #3 - Formulate a Sustainable Data Strategy
Call #1 - Determine the target state and initialize the corresponding roadmap for the data strategy.
Call #2 - Understand the role of effective change management and communication in operationalizing the data strategy.
Call #3 - Consolidate and refine all findings – formulate the data strategy document for senior leadership consumption.
Book Your Workshop
Onsite workshops offer an easy way to accelerate your project. If you are unable to do the project yourself, and a Guided Implementation isn't enough, we offer low-cost onsite delivery of our project workshops. We take you through every phase of your project and ensure that you have a roadmap in place to complete your project successfully.
Module 1: Establish Business Context
- Establish the business context for the business strategy.
Key Benefits Achieved
- Substantiates the “why” of the data strategy.
- Highlights the organization’s goals, objectives, and strategic direction the data must align with.
Advisory kick-off session with the data strategy sponsor (such as the Chief Data Officer [CDO], Chief Architect, Digital Transformation Leader, CIO).
- Business context and strategic drivers
Executive and senior business stakeholder interviews, one-on-one and small groups, to understand stakeholders’ strategic priorities and the alignment with data, discuss the vision, mission, goals, and principles of the data strategy, and understand the organization’s data culture.
- Defined vision and mission
- Defined principles and goals
- Data Culture Survey diagnostic results analysis
Module 2: Ensure You Have a Solid Data Foundation
- Build use cases of demonstrable value and understand the current environment.
Key Benefits Achieved
- An understanding of the current maturity level of key capabilities.
- Use cases that represent areas of concern and/or high value and therefore need to be addressed.
Build use cases of demonstrable value: Drivers, challenges, and opportunities.
- High-value use cases
Understand the current data environment: Data management enablers.
- High-level evaluation of the current environment
Understand the current data environment: People and organizational structure – key roles and skill sets.
Module 3: Build Your Future State Plan and Initialize the Roadmap
- Build out a future state plan that is aimed at filling prioritized gaps and that informs a scalable roadmap for moving forward on treating data as an asset.
Key Benefits Achieved
- A target state plan, formulated with input from key stakeholders, for addressing gaps and for maturing capabilities necessary to strategically manage data.
Target state plotting: Gap analysis and roadmap planning.
- Target state plan – high-level roadmap
People and organizational structure planning: Key roles, and skill sets.
- High-level RACI for key functional areas
Module 4: Formulate Your Data Strategy
- Consolidate business and data needs with consideration of external factors as well as internal barriers and enablers to the success of the data strategy. Bring all the outputs together for crafting a robust and comprehensive data strategy.
Key Benefits Achieved
- A consolidated view of business and data needs and the environment in which the data strategy will be operationalized.
- An analysis of the feasibility and potential risks to the success of the data strategy.
Build your business-data-needs model.
- Business-data-needs model
Risk and feasibility analysis: Conduct a SWOT analysis.
- SWOT analysis
Initialize the organization’s data strategy.
- Initialized data strategy document