UK

United Kingdom · Operations · Principal/Manager (12-16 years)

Manager, International Operations Analytics

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  • Experience bandPrincipal/Manager (12-16 years)
  • Direct reports3-5 reports
  • Reports toDirector, Global Operations Intelligence
  • UK framework levelUsually a manager, or the deepest specialist in a team

Also advertised as Operations Analytics Lead · Head of Operations Data & Insights · Senior Manager, Global Operations Intelligence

Built on 43,079 real UK job descriptions we analysed · grounded in what real qualifications cover

Two short quizzes about you

1From this job to a course

The qualifications matched to this job

Pearson BTEC Level 5 Higher National Diploma in Computing for England Pearson Education Ltd · Level 5 · covers 4 of 10 standards
Pearson BTEC Level 5 Higher National Diploma in Digital Technologies Pearson Education Ltd · Level 5 · covers 2 of 10 standards
NOCN Level 4 certificate for Data Analysts NOCN · Level 4 · covers 7 of 10 standards
OTHM Level 7 Diploma in Data Science OTHM Qualifications · Level 7 · covers 6 of 10 standards
Pearson BTEC Level 4 Higher National Certificate in Computing for England Pearson Education Ltd · Level 4 · covers 3 of 10 standards
BCS Level 4 Diploma - Digital Modular Programme for Data Analysts BCS, The Chartered Institute for IT · Level 4 · covers 2 of 10 standards

Matched from the standards this job is measured against: a suggestion, not an official ruling.

The units you would start with

Data Analytics Pearson BTEC Level 5 Higher National Diploma in Computing for England
Data Analytics Primer NOCN Level 4 certificate for Data Analysts
Data Analysis and Visualisation OTHM Level 7 Diploma in Data Science
Data Analysis BCS Level 4 Diploma - Digital Modular Programme for Data Analysts

The future skills this job leans on

AI Fluency working with AI as a thinking partner
Data Fluency turning numbers into a decision
AI Governance Fluency using AI responsibly
Automation Fluency building AI into how work runs
Trust Fluency keeping the digital world safe
Your Plan Illustration

Built for Manager, International Operations Analytics

4 units that map to this job, from the qualifications that cover it.

  1. Data Analytics Pearson Education Ltd · covers 4 of 10 standards Level 5
  2. Data Analytics Primer NOCN · covers 7 of 10 standards Level 4
  3. Data Analysis and Visualisation OTHM Qualifications · covers 6 of 10 standards Level 7
  4. Data Analysis BCS, The Chartered Institute for IT · covers 2 of 10 standards Level 4
These are the real units behind this job, in the order they rank for it. Nothing here is marked done, because this plan has not been started by anyone yet. Yours would fill in as you go.

2AI and this work

Will AI change your work as a Manager, International Operations Analytics?

Nobody can say exactly how. Here is what this job is being asked for next, and where to start.

The new skill this role is being asked for

  • AI Strategy & Ethical Deployment
Why each one is rising

The future skills this job leans on

We'll only ever tell you what we can actually back up. No hype, no scare tactics.

What happens when you start

Next, a free account. We build your Manager, International Operations Analytics plan as you set up, starting with the free Automation Fluency module. No card.

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3What this role really is

Leads a team of operations data analysts, using data to make international operations run more efficiently.

4What you'd actually use

The tools this job runs on, and how well you'd need to know each one.

SAP S/4HANA / Oracle NetSuite (Strategic Oversight) Strategic Oversight

Involved in ERP module implementation/upgrade decisions, understanding how ERP data architecture impacts enterprise-wide analytics and guiding your team on data extraction best practices.

MS SQL Server / PostgreSQL / Snowflake (Architectural Input) Architectural Input

Designing data schemas for analytics marts, making decisions on database technology (e.g., Snowflake vs. Redshift) for operational data warehousing, and ensuring data accessibility for your team.

Power BI / Tableau / Domo (Enterprise Strategy) Enterprise Strategy

Managing the BI platform (e.g., Power BI Premium capacity, Tableau Server), setting enterprise-wide standards for data visualisation and governance, and using tools like Domo for executive-level reporting.

Excel (Strategic Modeling) Strategic Modeling

Using Excel for high-level scenario planning and strategic modelling, but also pushing for scalable, enterprise solutions like Anaplan for core planning processes, and guiding your team on robust model design.

Python (Pandas, NumPy, scikit-learn, PM4Py - Strategic Application) Strategic Application

Championing the use of Python for advanced analytics like predictive modelling (e.g., scikit-learn for demand forecasting) and process mining (e.g., PM4Py), and guiding your team on best practices and code quality.

Blue Yonder / Oracle TMS (Platform Evaluation) Platform Evaluation

Leading the evaluation and selection process for new TMS/WMS systems, focusing on data accessibility, analytics capabilities, and ensuring integration with our existing data ecosystem.

5What you get to decide, and how that grows

Power in a job isn't your title. It's what you're allowed to decide. Here's how it grows as you move up.

The choiceComing in Where you are nowThe step above
Project Prioritisation Follows manager's prioritisation. Proposes prioritisation for own tasks, manager approves. Prioritises own workstreams, consults manager on conflicts.
Technical Approach & Methodology Uses prescribed methods, asks for help. Chooses appropriate standard methods, escalates novel challenges. Designs and implements complex technical approaches, consults on major deviations.
Budget Allocation (Team/Project) No budget authority. No budget authority. Recommends software/training spend up to £5K, requires approval.
Team Hiring & Performance No authority. No authority. Provides input on junior hires, mentors new joiners.

6How you'll be judged

The scoreboard, and what is not on it. The hard targets, how often each is actually looked at, and the quiet signals that never reach a dashboard.

Identified & Validated Cost Savings
The total annualised cost savings directly attributable to insights and recommendations from your team's analytical projects.
Target · Identify and validate >£2M in annual cost savings.

Your team's analysis of carrier performance on the Europe-APAC lane leads to a renegotiation that saves £750K annually, and a new inventory model reduces holding costs by £1.5M.

Demand Forecast Accuracy (MAPE)
Improvement in the Mean Absolute Percentage Error (MAPE) of key product demand forecasts across international markets, driven by your team's models and methodologies.
Target · Improve MAPE on top 20 SKUs by 10% year-over-year.

Through new models and better data, your team reduces forecast error from 15% to 13.5% for critical products, leading to fewer stockouts and less excess inventory.

Operational KPI Improvement
Direct contribution of analytics initiatives to a measurable improvement in core operational KPIs like On-Time In-Full (OTIF) delivery, Inventory Turns, or Warehouse Throughput.
Target · Analytics initiatives directly contribute to a 5% improvement in a key metric (e.g., OTIF).

Your team's analysis identifies bottlenecks in a key distribution centre, leading to process changes that boost throughput by 7% within six months.

Team Project Delivery Rate
The percentage of agreed-upon strategic analytics projects completed on time and within scope by your team.
Target · Achieve 85% on-time, in-scope delivery for strategic projects.

Out of 10 planned projects for the quarter, 9 were delivered as agreed, with the remaining one being deprioritised due to a valid business shift.

Team Development & Engagement
How effectively you mentor, coach, and develop your team members, fostering a culture of continuous learning and high performance. Also, how engaged your team feels.
  • Regular 1:1s with clear development plans. At least one team member promoted or taking on significant new responsibilities annually. Positive feedback in skip-level meetings and annual engagement surveys (e.g., team engagement scores above 75%).
Strategic Influence & Collaboration
Your ability to build trust and influence senior operational leaders, ensuring your team's insights are integrated into strategic planning and decision-making.
  • Operations Directors proactively seek your team's input on new initiatives. Your team's work is regularly cited in leadership presentations. Strong, positive feedback from key stakeholders on the clarity and impact of your team's recommendations. You're seen as a trusted advisor, not just a data provider.
Analytics Roadmap & Innovation
The clarity and ambition of the analytics roadmap you define for your area, including the introduction of new methodologies, tools, or AI applications that enhance our operational intelligence.
  • A well-defined, documented roadmap for the next 12-18 months. Successful pilots and implementation of new analytical techniques (e.g., process mining, advanced ML forecasting). Regular presentations to leadership on future analytics capabilities.

7Would you like it

Both sides. What people enjoy, and what grinds them down.

What people enjoy
Building & Developing a Team

You'll spend a good chunk of your day in 1:1s, coaching sessions, or helping your team solve complex problems. You'll get a real buzz from seeing your analysts grow and take on bigger challenges.

An analyst you've been mentoring successfully leads their first major project presentation to a Director, and you feel immense pride in their achievement.

Driving Strategic Impact

You're motivated by seeing your team's work directly influence major business decisions, leading to tangible improvements in operational efficiency or cost savings. You want to be at the table where big choices are made.

Your team's network optimisation model gets approved, leading to a multi-million-pound investment that you know will reshape our logistics for years.

Solving Complex, Real-World Problems

The challenge of untangling messy global operational data to find hidden opportunities is what gets you up in the morning. You love the intellectual puzzle of figuring out how to make a sprawling international supply chain run better.

You lead your team through a tricky project to integrate disparate data sources from three different regions, finally enabling a consolidated view of global inventory that wasn't possible before.

What frustrates people
  • Dealing with legacy systems that make data extraction a nightmare, despite your best efforts to push for modern solutions.
  • Getting buy-in from senior leaders who still rely heavily on 'gut feel' or anecdotal evidence over robust data analysis.
  • The constant tension between urgent, ad-hoc requests that derail your team's strategic project plans.
  • Managing team dynamics and individual performance issues, which can sometimes feel like a full-time job in itself.
  • The slow pace of change in large operational organisations, where even a brilliant, data-backed recommendation can take months or years to implement.
What this role does not give you
  • A quiet, heads-down environment for deep technical work – you'll be in meetings, coaching, and stakeholder discussions a lot.
  • Complete control over data infrastructure – you'll influence it, but you won't own the data engineering roadmap.
  • Guaranteed implementation of every single insight your team generates – some will get deprioritised, some will be too complex to implement, and some will simply be ignored.

8Who you work with

This role directly impacts the efficiency, cost-effectiveness, and strategic direction of our international operations. Your team's work will drive decisions on network optimisation, inventory levels, carrier selection, and process improvements, ultimately affecting our bottom line and customer satisfaction across multiple geographies. You're essentially building the intelligence layer for our global operational nervous system.

Inside the business
  • Director, Global Operations Intelligence
  • Regional Operations Directors (e.g., EMEA, APAC, Americas)
  • Head of Supply Chain
  • Head of Logistics
  • Finance Business Partners (Operations)
  • Product Management (for operational tools)
  • IT Leadership (Data Engineering, Infrastructure)
Outside the business
  • Key Logistics Providers
  • Technology Vendors (ERP, TMS, WMS)
  • Industry Bodies (for best practices)

9What you need before you start

Not a wish list. The things you would be expected to already have.

  • Proven experience (at least 3-5 years) leading and developing a team of data analysts or data scientists.
  • A strong track record of delivering impactful, data-driven insights that have led to significant business outcomes, preferably in an operations or supply chain context.
  • Expert-level proficiency in SQL and Python (with relevant data science libraries) – you might not code daily, but you need to be able to review code, challenge methodologies, and guide your team effectively.
  • Extensive experience with BI tools (Power BI, Tableau, Domo) and the ability to set standards for data visualisation and reporting.
  • Demonstrable experience translating complex analytical findings into clear, concise, and actionable recommendations for senior non-technical audiences.
  • A deep understanding of international supply chain, logistics, or manufacturing operations, including common challenges and opportunities.

10What to practise next

Where the job is going, and what to do about it starting this week.

Data Mesh & Distributed Data Architecture Understanding

As our data landscape grows, central data lakes become bottlenecks. Understanding Data Mesh principles—treating data as a product, decentralised ownership—will be critical for ensuring your team can access and use data efficiently across different operational domains and geographies without being blocked by a central IT team.

Data as a Product · Domain-oriented data ownership · Self-serve data infrastructure · Federated computational governance

  • This week: Read 'Data Mesh: Delivering Data-Driven Value at Scale' by Zhamak Dehghani.
  • This month: Discuss Data Mesh concepts with our Data Engineering team and identify current pain points it could solve.
  • Next quarter: Map out a potential 'data product' that your team could own and serve for a key operational metric.
  • Within 6 months: Advocate for specific infrastructure changes that support a more distributed data ownership model.

Quick win: Start thinking about the core 'data products' your team already implicitly creates (e.g., the weekly carrier scorecard data) and how they could be more formally managed and served.

11Staying current once you are in

What people here do to keep up
  • Regularly attending industry conferences (e.g., Gartner Supply Chain Symposium, Strata Data & AI Conference) to stay abreast of emerging trends and technologies.
  • Participating in leadership development programmes, particularly those focused on coaching, strategic influence, and change management.
  • Engaging with online communities and forums dedicated to operations analytics, data science leadership, or specific technical tools.
  • Mentoring junior professionals outside your immediate team to broaden your leadership experience and perspective.

12The rising capability

The rising capability

Zavmo analysis

What's rising in its place

This is where the work is heading, and the higher pay with it. Get fluent here and the shift stops being a threat and starts being your edge.

AI Strategy & Ethical Deployment

AI isn't just a technical tool anymore; it's a strategic differentiator. As a manager, you need to understand how to identify high-impact AI use cases for operations, assess risks, and ensure ethical deployment. Competitors are already using AI for everything from warehouse automation to predictive maintenance, and we can't afford to be left behind.

  • Identifying high-ROI AI applications in Operations
  • Bias detection and mitigation in operational models
  • Explainable AI (XAI) for operational buy-in
  • Data privacy and security for AI models

13What you’ll use

What you’ll use

Skills this role draws on

Technical

  • Supply Chain Analytics Strategy
  • Advanced Demand Forecasting & Planning (Methodology)
  • Inventory Optimisation Strategy
  • Logistics Network Design & Modelling
  • Process Mining Application
  • Landed Cost Analysis (Strategic Implications)

14The pathway

The pathway

How you actually get there, here

How you become one varies far more by country than what one does. This is the UK route. Most people take one of these ways in; the right one depends on where you're starting from.

  1. 1

    Senior or Lead Operations Data Analyst (Internal Promotion)

    3-5 years as a Senior/Lead Analyst

    Skills to master

    • Beyond technical mastery, you'd need to have demonstrated strong project leadership, informal mentorship of junior colleagues, and a proven ability to influence stakeholders and drive adoption of your insights. Essentially, you've been acting like a manager without the title.

    You're ready to move on when

    • Successfully led multiple complex, cross-functional analytics projects from start to finish.
    • Consistently sought out and mentored junior analysts, helping them grow their skills.
    • Proactively identified strategic analytical opportunities, not just reacted to requests.
    • Received strong positive feedback from senior stakeholders on your communication and influence.
  2. 2

    Analytics Manager (from another industry/company)

    Coming in with 3-5 years of prior managerial experience.

    Skills to master

    • You'd need to quickly get up to speed on our specific operational context, data landscape, and stakeholder dynamics. Your leadership and analytical strategy skills would be transferable, but the domain knowledge would be the learning curve.

    You're ready to move on when

    • A demonstrable track record of building and leading high-performing analytics teams in a complex environment.
    • Strong references from previous direct reports and senior leaders.
    • Ability to articulate how your experience in a different industry translates directly to our operational challenges.
    • A clear understanding of the unique challenges of international operations.
  3. 3

    Consultant (with Operations Analytics specialisation)

    5-8 years in a management consulting firm, specialising in operations or supply chain analytics.

    Skills to master

    • You'd bring a strong strategic toolkit and experience in problem-solving, but you'd need to adapt to an in-house, long-term perspective rather than project-based engagements. Building internal relationships and navigating corporate politics would be key.

    You're ready to move on when

    • Experience leading client engagements focused on data-driven operational improvements.
    • Strong presentation and client management skills.
    • A desire to move from advisory to hands-on leadership within a single organisation.
    • Demonstrated ability to build and maintain long-term relationships, not just deliver projects.

15Where this role leads

The long view: This work can lead to a VP, Global Business Operations role, or into a Chief Data Officer or Chief Analytics Officer position.

The ten Future Fluencies

Zavmo analysis

The credential is what you can do today. These are what keep you valuable.

A qualification proves you can do the job as it's defined today. These ten are what decide whether you're still the obvious person for it in five years. They're the capabilities employers are now writing into senior roles faster than people are learning them. Zavmo weaves them through whatever you study, so you come out with both: the credential and the fluency.

The highlighted ones are the Fluencies your role leans on hardest, from how Manager, International Operations Analytics is actually changing.

Where it leads

Roles this leads to

Also named as a next step, with no page in the catalogue yet:

  • Principal Operations Data Scientist (Individual Contributor)

How you would learn this

One to one, on the work you already do

A tutor sets the task against your own job and marks the reasoning, at your pace. There is no cohort to fall behind.

A lesson from Data Analytics, worked against Manager, International Operations Analytics.

Data Analytics Level 5

Applied to your work in Manager, International Operations Analytics

The objective of this unit is to enable learners to understand and apply data analytics techniques for decision-making. Learners will be able to apply descriptive, predictive, and prescriptive analytic methods, utilising statistical methods, to convert raw data into actionable insights and determine the best course of action.

How the thinking builds
  1. 1 Remember
  2. 2 Understand
  3. 3 Apply
  4. 4 Analyse
  5. 5 Evaluate
  6. 6 Create
An illustration of a Zavmo lesson, built from this role’s own route. The unit, its objective and every criterion above are the awarding body’s own words, not an example.

It is £70 a month, billed monthly. Your free first module is Future Fluency, and you can cancel any time.

See Your Progress Grow Illustration
Manager, International Operations Analytics
  • Supply Chain Analytics Strategy
  • Advanced Demand Forecasting & Planning (Methodology)
  • Inventory Optimisation Strategy
  • Logistics Network Design & Modelling
  • Process Mining Application
  • Landed Cost Analysis (Strategic Implications)
This is your Mind Palace on learn.zavmo.ai. Every skill above comes from this role's own record, not an example borrowed from another job. A node lights up when you evidence it, and what you build stays yours between jobs. That is the part a course cannot do.

16The detail, folded away

Everything else the record holds

The career branches in full, how AI is already showing up in the day-to-day, and the questions people ask about this job. Here when you want them, out of the way while you decide.

Where it leads next, rung by rung

Where it leads

The career path, and where it branches

Manager, International Operations Analytics is a start, not a ceiling. Each step below asks for new skills and hands back more autonomy.

  1. Director, Global Operations Intelligence

    3-5 years in the Manager role

    From L5 to L6

    • Defining the multi-year global operations intelligence strategy.
    • Leading major organisational transformation initiatives.
    • Evaluating and integrating M&A targets from an operations data perspective.
    • Representing the organisation externally on operations intelligence topics.

  2. Principal Operations Data Scientist (Individual Contributor)

    3-5 years in the Manager role

    From L5 to L5/L6 equivalent (specialist track)

    • Designing and implementing highly complex, bespoke analytical solutions for the most challenging operational problems.
    • Evaluating and integrating novel data sources and technologies.
    • Publishing internal white papers or presenting at industry conferences on specific technical advancements.
    • Acting as the technical architect for major analytical platforms or models.
Working with AI on the job

Working with AI

Where AI is starting to help

As a Manager, your focus shifts from individual output to enabling your team. AI isn't just for analysts; it's a powerful tool for leaders to streamline processes, enhance strategic thinking, and free up your team for higher-value work. Imagine your team spending less time on manual tasks and more time on deep analysis and strategic recommendations.

We're building an 'AI Productivity Hub' specifically for our Operations teams. This isn't about replacing people; it's about giving your team superpowers. Here's how AI can transform how your team works and how you lead them, letting you focus on the big picture.

Automated Anomaly Detection (for your team)

Your team can set up AI scripts to continuously monitor key operational data streams – daily shipment costs, transit times, inventory levels. It automatically flags outliers and anomalies that deviate from historical norms, creating a daily 'exception report'. This means your analysts spend zero time manually scanning dashboards and all their time investigating why something is an anomaly, and what to do about it.

Predictive Demand Forecasting (enhanced)

Move beyond basic time-series models. Your team can use advanced AI/ML models (like Prophet or XGBoost) that incorporate external factors such as public holidays, real-time weather forecasts for shipping lanes, and macroeconomic indicators. This generates more nuanced and accurate demand forecasts, reducing the need for manual adjustments and freeing up your analysts for strategic 'what-if' scenario planning.

Executive Summary Generator (for team outputs)

After your team completes a complex analysis, they can paste key data tables, charts, and bullet points into an AI tool. It drafts a concise, business-focused executive summary for their PowerPoint slides or email updates. This translates technical findings into strategic implications, saving hours of crafting and refining, and ensuring your team's insights are always communicated clearly to senior leaders.

Automated Report Generation & Narrative

Imagine your weekly or monthly operational performance reports being drafted almost entirely by AI. Your team feeds in the raw data and key metrics, and the AI not only generates the charts but also writes a narrative explaining the trends, highlights key changes, and even suggests areas for deeper investigation. This significantly reduces the manual effort in recurring reporting, allowing your team to focus on proactive analysis rather than reactive reporting.

Common questions

Common questions

How do you become a Manager, International Operations Analytics?

Common routes in include Senior or Lead Operations Data Analyst (Internal Promotion) (3-5 years as a Senior/Lead Analyst), Analytics Manager (from another industry/company) (Coming in with 3-5 years of prior managerial experience.) and Consultant (with Operations Analytics specialisation) (5-8 years in a management consulting firm, specialising in operations or supply chain analytics.). Times vary with prior experience.

Where can a Manager, International Operations Analytics progress to?

This role can lead on to Director, Global Operations Intelligence (3-5 years in the Manager role) and Principal Operations Data Scientist (Individual Contributor) (3-5 years in the Manager role), depending on the skills you build.

What new skills matter most for a Manager, International Operations Analytics?

Increasingly, AI Strategy & Ethical Deployment. These are the skills our record of this role lists as growing.

Free tools

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Three free tools, no account needed. Each one ends with a role, a level and a way in.

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17Where to go from here

Other roles at Level 5

Same depth of qualification, different job. Useful if the work appeals but this particular role does not.

 More jobs in operations

Stay in the field you know and move sideways rather than up.
If you leave this industry

The skills built here, leading analytical teams, turning data into strategic action, understanding complex global operations, transfer well. They apply to similar leadership roles in retail, manufacturing, pharmaceuticals or logistics, and to broader data leadership roles in tech companies.

This role profile is © 2026 Growth Engineering Technologies Ltd. Built from UK occupational standards and regulated qualification data, and written for Zavmo.

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