HR Business Process Lead – SAP SuccessFactors Implementation

Slough
9 months ago
Applications closed

Related Jobs

View all jobs

HR MI Data Analyst, HR Services, 12-month Secondment/FTC

HR MI Data Analyst, HR Services, 12-month Secondment/FTC

HR Systems and Data Analyst

HR Systems and Data Analyst

HR Systems and Data Analyst

HR Systems and Data Analyst

Role Overview
We are seeking an innovative and experienced HR Business Process Lead to design, document, and drive the realisation of end-to-end global HR processes for a transformative SAP SuccessFactors implementation program. This role focuses on process governance, optimisation and data stewardship, balancing global standardisation with local business and regulatory needs. The ideal candidate will bring a mindset of continuous improvement, leveraging tools like business process modelling, process mining, and Lean Six Sigma methodologies to create efficient, user-centric processes that enhance both business outcomes and employee experience.
Key Responsibilities

  1. Process Governance and Ownership
  • Establish and enforce process governance frameworks to ensure consistency, compliance, and scalability across global HR operations.
  • Act as the process owner, responsible for designing, documenting, and overseeing the implementation of global HR processes.
  • Collaborate with Global Process Owners (GPOs) and stakeholders to align processes with strategic objectives, KPIs, and local regulatory requirements.
  1. End-to-End Global HR Process Design
  • Lead process analysis and process mining exercises to map current workflows, identify inefficiencies, and uncover improvement opportunities.
  • Use business process modeling tools, brown paper exercises, and Lean Six Sigma methodologies to design streamlined and effective processes.
  • Facilitate design workshops to capture input from stakeholders, ensuring processes balance global efficiency with local compliance.
  • Manage and analyse Requests for Change (RFCs), incorporating them into process enhancements.
  1. Process Implementation and Realisation
  • Partner with the inhouse team to drive the realisation of processes in SAP SuccessFactors, ensuring system capabilities align with business requirements.
  • Define and execute Standard Operating Procedures (SOPs), training materials, and KPI reporting frameworks to support successful implementation.
  • Oversee process changes, ensuring their seamless integration into existing workflows while maintaining operational excellence.
  1. Continuous Improvement and User Experience
  • Foster a culture of continuous improvement, regularly reviewing and refining processes to adapt to evolving business needs and user feedback.
  • Place user experience (UX) at the core of process design, ensuring intuitive, employee-friendly solutions.
  • Utilise process performance data to identify trends, root causes of inefficiencies, and opportunities for further optimisation.
  1. Data Stewardship and Ownership
  • Take ownership of the data produced by HR processes, ensuring its accuracy, compliance, and strategic alignment.
  • Collaborate with IT and HR teams to ensure data integrity and seamless integration with other business systems.
  • Leverage analytics to generate actionable insights that support decision-making and process improvement.
  1. Stakeholder Engagement and Collaboration
  • Partner with senior leaders to develop and execute the project deliverables, fostering strong partnerships to ensure successful delivery of process solutions.
  • Build and maintain effective relationships across global and local teams, addressing diverse needs and perspectives.
  1. Training and Change Management
  • Develop and deliver comprehensive training materials and sessions tailored to diverse stakeholder groups.
  • Lead change management efforts, articulating the value of transformation and ensuring strong adoption across the organisation.
  • Use tools like WalkMe or WhatFix to design user adoption journeys and measure their success through metrics such as engagement and NPS.
    Required Skills and Experience
    HR and Process Expertise:
    Proven experience in designing and implementing HR processes in a global context.
    Expertise in process analysis, business process modeling, and tools such as BPMN or Visio.
    Knowledge of Lean Six Sigma methodologies and process improvement frameworks.
    Familiarity with HR/ERP systems, particularly SAP SuccessFactors.
    Data Stewardship and Analytics:
    Strong capability in managing data integrity, compliance, and analytics for process optimisation.
    Understanding of data aggregation from multiple data sources – quantitative and qualitative.
    Continuous Improvement and User-Centric Design:
    Demonstrated ability to lead continuous improvement initiatives, focusing on user experience and operational excellence.
    Experience in mapping and enhancing user journeys for HR personas, such as HR Admins, Managers, and Employees.
    Communication and Collaboration:
    Excellent written and verbal communication skills, with a proven ability to engage and influence stakeholders across global and local teams.
    Strong interpersonal skills to foster collaboration and build relationships in a multicultural, remote-working environment.
    Planning and Organisational Skills:
    Exceptional attention to detail with the ability to manage complex tasks and deliverables in a fast-paced environment.
    Strong planning and project management skills to drive successful outcomes.
    What We Offer
    The opportunity to lead the transformation of global HR processes as part of a flagship SAP SuccessFactors implementation program.
    A dynamic, collaborative work environment that values humility, integrity, courtesy along with innovation, excellence, and user experience.
    Competitive compensation and professional growth opportunities within a forward-thinking organisation

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Data Science Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Thinking about switching into data science in your 30s, 40s or 50s? You’re far from alone. Across the UK, businesses are investing in data science talent to turn data into insight, support better decisions and unlock competitive advantage. But with all the hype about machine learning, Python, AI and data unicorns, it can be hard to separate real opportunities from noise. This article gives you a practical, UK-focused reality check on data science careers for mid-life career switchers — what roles really exist, what skills employers really hire for, how long retraining typically takes, what UK recruiters actually look for and how to craft a compelling career pivot story. Whether you come from finance, marketing, operations, research, project management or another field entirely, there are meaningful pathways into data science — and age itself is not the barrier many people fear.

How to Write a Data Science Job Ad That Attracts the Right People

Data science plays a critical role in how organisations across the UK make decisions, build products and gain competitive advantage. From forecasting and personalisation to risk modelling and experimentation, data scientists help translate data into insight and action. Yet many employers struggle to attract the right data science candidates. Job adverts often generate high volumes of applications, but few applicants have the mix of analytical skill, business understanding and communication ability the role actually requires. At the same time, experienced data scientists skip over adverts that feel vague, inflated or misaligned with real data science work. In most cases, the issue is not a lack of talent — it is the quality and clarity of the job advert. Data scientists are analytical, sceptical of hype and highly selective. A poorly written job ad signals unclear expectations and immature data practices. A well-written one signals credibility, focus and serious intent. This guide explains how to write a data science job ad that attracts the right people, improves applicant quality and positions your organisation as a strong data employer.

Maths for Data Science Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are applying for data science jobs in the UK, the maths can feel like a moving target. Job descriptions say “strong statistical knowledge” or “solid ML fundamentals” but they rarely tell you which topics you will actually use day to day. Here’s the truth: most UK data science roles do not require advanced pure maths. What they do require is confidence with a tight set of practical topics that come up repeatedly in modelling, experimentation, forecasting, evaluation, stakeholder comms & decision-making. This guide focuses on the only maths most data scientists keep using: Statistics for decision making (confidence intervals, hypothesis tests, power, uncertainty) Probability for real-world data (base rates, noise, sampling, Bayesian intuition) Linear algebra essentials (vectors, matrices, projections, PCA intuition) Calculus & gradients (enough to understand optimisation & backprop) Optimisation & model evaluation (loss functions, cross-validation, metrics, thresholds) You’ll also get a 6-week plan, portfolio projects & a resources section you can follow without getting pulled into unnecessary theory.