Organizational Re-design
Solving low product adoption by re-defining and scaling the problem
Combining existing foundational research insights with design thinking, our small product team made a case for restructuring the way the internal Data & Analytics function at McKinsey was organized and drove the effort.
The opportunity presented itself as an unforeseen outcome of our team's continuous research into our self-serve analytics tools portfolio. As we started mapping the larger end-to-end analytics journey of our analytics colleagues, their unmet needs and opportunity for change became very clear.
The outcome of this transformation was a drastic simplification of the internal organizational structure for the Data & Analytics function, combining the efforts of multiple teams from 3 departments into one consolidated Data & Analytics group. This lead to 10% client-facing efficiency increase and 25% FTE reduction in the D&A function, and an improved and simplified experience for McKinsey's consultants.
SECTOR - Data & Analytics / Technology
TEAM - Sr PM, Tech lead, UX Researcher
EXTENDED TEAM - Data & Analytics Leadership and stakeholders, Department leaders, Risk function
MY ROLE - Foundational Research, Transformation Strategy, Change Management, Senior Stakeholder Management, Implementation and Organizational Design of the new D&A function
LEAD TIME - Foundational research (pre-requisite/driver for change): 1 year - Advocating and PS: 9 months - Implementation and Standing up Group: 3 months
COMPLEXITY - Very high
Business problem
In my first role at McKinsey & Company as a UX Research Manager, I was part of a project team dedicated to increasing the adoption of Tableau and Alteryx, two key data analytics tools used by the company's consultants.
Through robust user testing, we identified that multiple teams were addressing only fragmented segments of the end-to-end analytics journey. This fragmentation resulted in efficiency losses, a suboptimal experience for consultants, inconsistent data handling, increased administrative overhead, delayed insights, and hindered decision-making. Moreover, varying quality and difficulties in scaling processes impeded innovation and effective solution implementation.
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To address these issues, we decided to leverage these insights to initiate an internal transformation aimed at streamlining the organization. This effort was led by our PM, tech lead, and myself.
Approach
To address the issues uncovered through continuous UX research, we decided to use these insights to drive an internal transformation aimed at streamlining the organization.
This initiative, led by our PM, tech lead, and myself, involved consolidating five distinct teams within the Data & Analytics space into a single, cohesive group, which in some cases required relocating teams to different departments.
The process included stakeholder management, extensive networking, backlog creation, discussions with consultants (end users), and leadership conversations. The entire transformation took nine months, followed by an additional three months to establish the new group.
Although this initiative was outside my typical responsibilities as a UX Research Manager, it emerged from our data and discovery efforts, and the compelling evidence justified our decision to act on it.
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Activities
Pre-phase
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Foundational research self-serve analytics tools (Tableau, Alteryx)
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End-to-end analytics journeys for generalists and advanced analytics data experts
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Problem and opportunity identification
Transformation Strategy
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Gathering and syndicating Firm-wide research insights on colleagues working with data
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Organize and lead 3-day strategy workshop for analytics function - Discuss options for collaboration and merger
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Make a case with leadership
Pre-implementation
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Convene and lead virtual analytics group with Analytics and Risk leadership and stakeholders (30 participants)
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Create and manage backlog of work for the group
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Go/no-go decision
Implementation
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Internal strategy discussions
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Design organization structure for new Data & Analytics group
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Determining and finalizing role descriptions, headcount and staffing needs
Data & Analytics group organizational design
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Stand up Group processes (Meeting structures, Agile rituals, Governance, Backlog, etc.)
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Mission/Vision/Strategy
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Roadmaps
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Hiring and on boarding team members
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Internal comms on new group
Key take aways
To address the issues uncovered through continuous UX research, we decided to use these insights to drive an internal transformation aimed at streamlining the organization.
This initiative, led by our PM, tech lead, and myself, involved consolidating five distinct teams within the Data & Analytics space into a single, cohesive group, which in some cases required relocating teams to different departments.
The process included stakeholder management, extensive networking, backlog creation, discussions with consultants (end users), and leadership conversations. The entire transformation took nine months, followed by an additional three months to establish the new group.
Although this initiative was outside my typical responsibilities as a UX Research Manager, it emerged from our data and discovery efforts, and the compelling evidence justified our decision to act on it.
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Personal take aways
This project stands out as one of the most impactful, challenging, and rewarding experiences in my career. Despite, or better, because it was outside our team's scope, our data-driven approach and the collective commitment of our team made it a valuable and memorable learning experience.
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Following this project, I immersed myself in transformation training and skill-building. I participated in two additional engagements at McKinsey focused on change management and transformations:
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Restructuring of McKinsey’s procurement function: Collaborated closely with senior leadership to achieve $35 million in savings. I initiated and led the Project Management Office (PMO), driving digital transformation by managing projects that facilitated the adoption of new technologies and processes.
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Transformation of internal work processes and culture change 'Way We Work': Spearheaded the digital transformation of our internal processes to enhance efficiency and effectiveness.
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Related Certifications
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Performance Management and Tracking (Metrics, KPIs) – McKinsey Academy, 2023
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Leading Transformations: Manage Change – Macquarie University via Coursera, 2023
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McKinsey Transformation L1 Program – McKinsey (internal expert training), 2022
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Certified Agile Leadership – Scrum Alliance, 2019
FRAMEWORKS
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The Influence model. McKinsey & Company. The four building blocks of change
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5 Frames of Performance and Health. McKinsey & Company. A better way to lead large-scale change​
"One of our team’s greatest achievements was our initiative to drive a cross-function merger of multiple McKinsey Data & Analytics teams. Marianne’s UX research insights were essential because they revealed opportunities for better alignment of a new, streamlined Data & Analytics organization structure; one that also drove increased internal efficiency."
Brian Bussing, PM, Analytics Team