United Kingdom · Internal consulting · Senior (5-8 years)

Senior Data Insights Consultant

Here is the whole job, in plain words. What it is, what you decide, how you're judged, how people get here and where they go next. Then the part no course gives you: twelve AI tutors who learn your work.

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One email: what AI is changing in this job, and where to start free. With a link back here. Nothing else follows unless you confirm your address.

Also at another level: the Data Insights Consultant job description.

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Experience bandSenior (5-8 years)
Direct reportsNo direct reports
Reports toLead Data Insights Consultant or Principal Data Insights Consultant
UK framework levelUsually a manager, or the deepest specialist in a team

Also advertised as Senior Analytics Consultant · Senior Business Intelligence Consultant · Senior Strategy Analyst

Built on 43,079 real UK job descriptions we analysed · grounded in qualifications employers recognise

Two short quizzes about you

1From this job to a course

The qualifications matched to this job

NCC Education Level 5 Extended Diploma in Computing with Data Science NCC Education Limited · Level 5 · covers 4 of 10 standards

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 5 of 10 standards

Pearson BTEC Level 4 Higher National Certificate in Computing for England Pearson Education Ltd · Level 4 · covers 3 of 10 standards

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

The units you would start with

Introduction to Data Science and Big Data NCC Education Level 5 Extended Diploma in Computing with Data Science

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

The future skills this job leans on

AI Fluency working with AI as a thinking partner

Data Fluency turning numbers into a decision

Systems Fluency seeing the whole picture

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Your Plan Illustration

Built for Senior Data Insights Consultant

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

Introduction to Data Science and Big Data NCC Education Limited · covers 4 of 10 standards Level 5
Data Analytics Pearson Education Ltd · covers 4 of 10 standards Level 5
Data Analytics Primer NOCN · covers 7 of 10 standards Level 4
Data Analysis and Visualisation OTHM Qualifications · covers 5 of 10 standards Level 7

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 Senior Data Insights Consultant?

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

The new skills this role is being asked for

Prompt Engineering & LLM Integration
Causal Inference & Experiment Design

Why each one is rising

The future skills this job leans on

AI Fluencyworking with AI as a thinking partner
Data Fluencyturning numbers into a decision
Systems Fluencyseeing the whole picture

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 Senior Data Insights Consultant plan as you set up, starting with a Future Fluency module on using AI in your job. No card.

Your first Future Fluency module is free. After that, your AI tutor is £70 a month.

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3What this role really is

A Senior Data Insights Consultant takes a messy business problem, works out the real question behind it, and digs into the data to find answers.

4What you'd actually use

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

SQL (PostgreSQL, MS SQL Server) Expert

Designing and optimising complex queries to extract, transform, and load data for various analytical projects. You'll be debugging and refactoring others' code, understanding indexing, and thinking about execution plans to make queries run faster.

Python (pandas, NumPy, scikit-learn) Advanced

Building custom data manipulation pipelines, developing predictive models (regression, classification), and validating their performance. You'll be writing clean, efficient, and well-documented Python code for complex analyses.

Tableau / Power BI Expert

Mastering advanced features like LOD expressions in Tableau or DAX in Power BI. You'll design complex data models and create compelling, interactive dashboards that tell a clear story, moving beyond basic charts to truly impactful visualisations.

Microsoft Excel Expert

Using VBA for automation, building robust, auditable business case models that integrate data from multiple sources. You'll be the go-to person for complex formulas, scenario analysis, and ensuring the integrity of financial models.

Miro / FigJam Facilitator

Designing and leading virtual whiteboarding sessions to structure analytical problems, map out project plans, and facilitate collaborative brainstorming with cross-functional teams. You'll use these to bring clarity to ambiguous situations.

Snowflake / Databricks User

Leveraging platform-specific features (e.g., Snowpark, Databricks notebooks) for large-scale analysis, understanding how to connect to and query data efficiently from our enterprise data platform. You'll be comfortable working with big data environments.

Confluence / Notion Owner

Establishing and maintaining the knowledge base for your projects or workstreams, ensuring a 'single source of truth' for methodology, findings, and recommendations. You'll make sure insights are easily accessible and reusable for the wider team.

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 choice	Coming in	Where you are now	The step above
Analytical Methodology Selection	Proposes options, requires manager approval.	Selects methodology for routine problems, consults manager for novel ones.	Defines and implements methodology for complex workstreams, informs manager.
Data Source Selection & Validation	Identifies potential sources, requires manager validation.	Selects and validates primary data sources, escalates complex issues.	Determines optimal data sources, establishes validation protocols, flags systemic issues.
Project Timeline & Scope Changes (Workstream Level)	Escalates all requests to manager.	Negotiates minor adjustments within pre-approved limits, consults manager for significant changes.	Proposes and negotiates changes for own workstream, consults manager on broader project impact.
Stakeholder Communication & Management	Drafts communications for manager review, participates in meetings.	Leads routine stakeholder updates, drafts key messages for manager review.	Leads stakeholder engagement for workstream, manages expectations, presents findings directly.
Mentorship & Junior Analyst Task Assignment	N/A	Provides informal guidance, helps unstick junior colleagues.	Assigns tasks, provides structured feedback, conducts code reviews, supports development of 1-2 junior team members.

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.

Workstream Delivery & Accuracy

Timely and accurate completion of assigned analytical workstreams.

Target · 90%+ of workstreams delivered on schedule with <1% error rate in core calculations.

Delivered the Q3 customer segmentation analysis two days ahead of schedule with zero factual errors in the final report, as verified by peer review.

Stakeholder Satisfaction (Workstream Level)

How happy internal clients are with your specific analytical output and engagement.

Target · Average project feedback score of >4.5/5 for your workstream contributions.

Received feedback from the Head of Marketing praising the clarity and actionable nature of your pricing elasticity model, scoring 5/5 for 'relevance' and 'impact'.

Insight Adoption Rate

The percentage of your key recommendations that are actually implemented by the business.

Target · At least 60% of primary recommendations from your workstreams are actioned within 3 months.

Your recommendation to optimise marketing spend based on channel ROI led to a £200K reallocation, resulting in a 15% improvement in campaign efficiency.

Mentorship & Team Contribution

The growth and performance of junior team members you mentor.

Target · At least one mentee achieves 'exceeds expectations' rating or receives a promotion annually.

Your consistent guidance helped a junior analyst significantly improve their SQL query optimisation skills, leading to them independently owning a key data pull for the next project.

Problem Structuring & Hypothesis Quality

Your ability to break down complex, ambiguous problems into clear, testable analytical questions.

You consistently present well-defined hypotheses before diving into data. Your project plans show a logical, MECE approach. You can articulate the 'so what?' of a problem before starting the analysis. Peers often come to you for help structuring their own analytical challenges.

Data Storytelling & Communication Clarity

How effectively you translate complex analytical findings into compelling, easy-to-understand narratives for non-technical audiences.

Your presentations are consistently 'deck-ready', following the Pyramid Principle. Stakeholders frequently comment on the clarity of your insights. You can explain a complex model to a Director without using jargon, leading to immediate understanding and buy-in. You anticipate questions and address them proactively in your reports.

Influence & Credibility

Your ability to build trust and influence decisions with project stakeholders and senior leaders.

You're proactively consulted on analytical approaches for new projects. Your opinions are sought in project steering committee meetings. You can gracefully challenge a stakeholder's assumption with data without damaging the relationship. You're seen as a reliable, objective voice in discussions.

Proactive Issue Identification

Your knack for spotting potential problems or opportunities in the data or business before others do.

You flag data quality issues before they impact analysis. You identify an emerging trend in customer behaviour that wasn't part of the initial brief. You suggest a new analytical approach that could yield deeper insights or greater efficiency, even if it means more work initially.

7Would you like it

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

What people enjoy

Solving Complex Business Puzzles

You love taking an ambiguous, 'this just isn't working' problem and breaking it down into manageable analytical pieces. You get a real kick out of the 'aha!' moment when the data finally reveals the root cause or a clear path forward.

Spending a Friday afternoon deep-diving into customer churn data, trying to figure out why a specific segment is leaving, and feeling energised by the challenge rather than overwhelmed.

Driving Tangible Business Impact

You're not just doing analysis for analysis' sake. You want to see your work actually get used, make a difference, and contribute to the company's success. Seeing your recommendations implemented and yielding results is what truly motivates you.

Presenting a cost-saving recommendation to the Operations team and then, three months later, seeing those savings reflected in the quarterly financial reports.

Continuous Learning & Skill Development

You're always keen to pick up new analytical techniques, learn a new tool, or understand a new business domain. The idea of staying stagnant technically or intellectually is a major turn-off. You'll seek out opportunities to expand your skillset.

Volunteering to learn a new machine learning algorithm because you see its potential application to a current business problem, even if it's outside your immediate project scope.

What frustrates people

The Data Scavenger Hunt: The data you desperately need exists, but it's locked in a legacy system, the documentation is missing, and the only person who understands it retired two years ago. Getting a clean data pull can feel like pulling teeth.
Politically Motivated Analysis: Being implicitly (or explicitly) asked to 'slice the data differently' to support a powerful stakeholder's pet project. This forces an uncomfortable conflict between your objectivity and political survival.
The 'Data Janitor' Reality: Realising that 80% of your time is spent on the unglamorous work of cleaning, joining, and wrangling messy, inconsistent data, and only 20% is actual, exciting analysis. Yes, it's tedious, but someone has to do it.
The Moving Goalpost: Your project sponsor changes the core business question two weeks into a three-week project, effectively invalidating all your hard work, but the deadline remains exactly the same. It's frustrating, but it happens.
Explaining the Obvious (to you): Patiently explaining the difference between correlation and causation, or why an average can be misleading, to a room of senior executives for the third time in a month. Sometimes it feels like Groundhog Day.
Ownership Without Authority: Being held accountable for delivering a critical insight but having no direct authority over the data engineering teams you rely on for access, pipelines, and support. You'll need to influence without direct power.

What this role does not give you

A predictable, routine work schedule with no urgent requests. Expect the unexpected.
A role where you only deal with perfect, well-documented data. You'll spend a lot of time cleaning.
A guarantee that every single recommendation you make will be adopted. Some will, some won't.
A quiet, solitary environment. You'll be talking to people constantly, explaining complex ideas.

8Who you work with

This role directly influences strategic and operational decisions across the organisation by providing robust, unbiased data insights. You'll help business units understand their performance, identify growth opportunities, and diagnose problems. Your work helps us avoid costly mistakes and focus our efforts where they'll have the biggest impact, ultimately contributing to the company's profitability and competitive edge.

Inside the business

Director of Internal Consulting
Heads of Business Units (e.g., Marketing, Sales, Operations, Finance)
Project Sponsors and Steering Committees
Data Engineering and IT teams (for data access and infrastructure support)
Peer Senior Consultants across other internal consulting practices

Outside the business

Occasionally external vendors or partners for data integration or benchmarking studies (under guidance)

9What you need before you start

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

Proven experience (5+ years) in a data analysis, business intelligence, or analytical consulting role, ideally within a large organisation or a consulting firm.
Demonstrable track record of leading complex analytical workstreams and delivering actionable insights that have driven measurable business outcomes.
Expert-level proficiency in SQL and at least one major BI tool (Tableau or Power BI), with advanced skills in Python for data analysis and modelling.
Strong understanding of statistical concepts and their practical application in business contexts (e.g., hypothesis testing, regression analysis, A/B testing).
Experience mentoring or informally guiding junior analysts, including conducting code reviews and providing constructive feedback.
Excellent verbal and written communication skills, with a portfolio or examples of clear, impactful data visualisations and presentations.
A degree in a quantitative field such as Mathematics, Statistics, Computer Science, Economics, or a related discipline, or equivalent practical experience.

10What to practise next

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

Advanced Data Engineering Concepts for Analysts

Important within 12 months. As data volumes grow and pipelines become more complex, a deeper understanding of data engineering principles will help you design more efficient analyses, troubleshoot data issues faster, and collaborate more effectively with data engineers. You won't be building pipelines, but you'll understand how they work.

Data Warehousing & Data Lake Architectures · ETL/ELT Principles · Schema Design & Data Modelling · Data Governance & Metadata Management · Cloud Data Platforms (Advanced Features)

This week: Schedule a coffee chat with a data engineer to understand their typical workflow and challenges.
This month: Complete an online course on data warehousing fundamentals or cloud data platform architecture.
Month 2: Proactively suggest optimisations for a slow-running query or a complex data pull, applying data engineering principles.
Month 3: Lead a session for your team on best practices for interacting with data engineering, based on your enhanced understanding.

Quick win: When requesting data, always ask about the data lineage and transformation logic. This immediately signals a deeper understanding and helps prevent errors.

11Staying current once you are in

What people here do to keep up

Regularly attending industry conferences or webinars on data analytics, business intelligence, and internal consulting best practices.
Actively participating in online data science communities (e.g., Kaggle, Stack Overflow) to keep your technical skills sharp and learn from peers.
Taking advanced courses in specific analytical techniques (e.g., time series forecasting, machine learning, causal inference) that align with business needs.
Seeking out opportunities to mentor junior colleagues and present your work to wider audiences to hone your communication and leadership skills.
Reading business strategy books and articles to deepen your commercial acumen and understand the broader context of your analytical work.

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.

Prompt Engineering & LLM Integration

Critical within 6 months—this is already happening, not future. Our competitors are using tools like GPT to draft reports in 10 minutes that used to take 2 hours. Analysts who figure this out will outproduce their peers 3:1, freeing up time for deeper, more strategic thinking.

Context Windows & Token Limits
Temperature Settings for Different Tasks
RAG (Retrieval Augmented Generation) Architectures
Output Validation & Hallucination Detection
Prompt Chaining for Complex Analysis

Causal Inference & Experiment Design

Important within 12 months. As our business becomes more data-mature, stakeholders will move beyond 'what happened' to 'what caused it to happen' and 'what will happen if we do X?'. Simple correlations won't cut it. The ability to design robust experiments and infer causality is becoming a key differentiator for strategic insights.

A/B Testing & Randomised Control Trials (RCTs)
Quasi-Experimental Designs
Directed Acyclic Graphs (DAGs)
Propensity Score Matching
Interpreting Causal Models

13What you’ll use

What you’ll use

Skills this role draws on

Technical

Hypothesis-Driven Analysis
Business Case Modeling
MECE Problem Structuring
Data Storytelling
Root Cause Analysis (RCA)
Stakeholder Influence Mapping

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
Internal Promotion (Data Insights Consultant)
2-3 years as an L2 Data Insights Consultant
Skills to master
- Consistently delivering high-quality, independent analytical work. Beginning to informally mentor junior colleagues. Proactively identifying problems and proposing solutions. Taking ownership of entire analytical workstreams.
You're ready to move on when
- You're the go-to person for complex data pulls and analyses on your team.
- You consistently deliver projects on time and with high accuracy, requiring minimal oversight.
- You've started to provide informal guidance and support to newer team members.
- Your manager and project leads trust you to handle significant parts of a project independently.
2
External Hire (Consulting Firms)
5-8 years experience in a similar role at a management consulting firm (e.g., Big Four, boutique analytics consultancy).
Skills to master
- Strong client management skills. Experience with structured problem-solving frameworks (e.g., MECE). Ability to quickly ramp up on new industries/business domains. Excellent presentation and communication skills.
You're ready to move on when
- You've successfully led analytical modules for external clients, managing their expectations and delivering impactful insights.
- You're comfortable presenting complex findings to senior client stakeholders.
- You've worked across multiple industries or functional areas, demonstrating strong learning agility.
- You have a solid toolkit of consulting methodologies and approaches.
3
External Hire (In-house Analytics/BI Teams)
5-8 years experience in a senior analyst or BI developer role within a large corporate environment.
Skills to master
- Deep technical expertise in a specific domain (e.g., marketing analytics, supply chain BI). Strong understanding of business operations and data sources. Experience with end-to-end analytical project delivery.
You're ready to move on when
- You've owned and delivered significant analytical projects from inception to implementation within your previous company.
- You're recognised as a subject matter expert in your previous domain, regularly influencing business decisions with data.
- You have a strong command of SQL, Python, and BI tools, with a focus on practical application.
- You're looking for a role with more variety, strategic impact, and exposure to different parts of the business.

15Where this role leads

The long view: This work can lead into a Principal Data Insights Consultant role, shaping analytical work across several projects, or a Director, Strategic Insights role, leading a portfolio of strategic projects.

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 Senior Data Insights Consultant is actually changing.

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 Introduction to Data Science and Big Data, worked against Senior Data Insights Consultant.

Introduction to Data Science and Big Data Level 5

Applied to your work in Senior Data Insights Consultant

The objective of this unit is to provide learners with a systematic understanding of Data Science and Big Data concepts, including their characteristics and applications. Learners will develop proficiency in data collection, design, and modelling techniques, and will be able to select appropriate tools for data pre-processing and apply analytical techniques to generate insights from data.

How the thinking builds

1 Remember
2 Understand
3 Apply
4 Analyse
5 Evaluate
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.

Start my Senior Data Insights Consultant plan, free

See Your Progress Grow Illustration

Senior Data Insights Consultant

Hypothesis-Driven Analysis
Business Case Modeling
MECE Problem Structuring
Data Storytelling
Root Cause Analysis (RCA)
Stakeholder Influence Mapping

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

Senior Data Insights Consultant is a start, not a ceiling. Each step below asks for new skills and hands back more autonomy.

Lead Data Insights Consultant (L4)
3-5 years as a Senior Data Insights Consultant

This is a significant step, moving from leading workstreams to leading entire analytical projects and potentially managing a small team of direct reports.
- Analytical Architecture Design Designing the overall analytical approach and data strategy for large-scale consulting projects.
- Budget Management Managing project budgets (typically £50K-£500K) and making resource allocation decisions.
- Hiring & Onboarding Participating in the recruitment and successful onboarding of new team members.
- Vendor Management Evaluating and managing relationships with external data or analytics vendors.

Working with AI on the job

Working with AI

Where AI is starting to help

Let's be honest, a big chunk of a Senior Data Insights Consultant's time goes into repetitive tasks, searching for information, and drafting communications. What if you could get those hours back? Our internal AI Productivity Hub is designed to do just that, giving you more time for the truly strategic, impactful work you love.

We're not talking about replacing your brain; we're talking about giving you a powerful co-pilot. Imagine AI handling the grunt work, leaving you free to focus on the 'so what?' and the 'now what?'. Here's a glimpse of how AI can transform your day-to-day as a Senior Data Insights Consultant:

Automated Data Dictionary Creation

Use an AI tool to scan database schemas and sample data, then auto-generate clear, plain-English documentation. It translates cryptic column names ('CUST_LST_TRN_DT') into understandable descriptions ('Date of customer's last transaction') and flags potential data quality issues, saving you hours of manual discovery and documentation per new dataset. It's like having a data librarian who never sleeps.

Hypothesis Generation Engine

Feed a problem statement (e.g., 'Investigate Q3 customer churn') and a summary of your dataset into an LLM. It'll generate 10-15 potential, testable hypotheses (e.g., 'Hypothesis: Churn is higher for customers who haven't contacted support in the last 6 months'). This cuts down initial brainstorming and problem-structuring time by hours, helping you get to the core questions faster.

Internal Knowledge Synthesizer

Leverage a RAG model trained on our company's internal SharePoint, Confluence, and past project archives. Ask it complex questions like, 'Summarise previous findings on the effectiveness of our loyalty programme in the APAC region.' You'll get an instant, sourced summary, saving you 5-10 hours of searching for prior work and preventing you from reinventing the wheel on every new project.

Executive Summary & Narrative Drafter

After your analysis is complete, feed your key findings, charts, and data points into an LLM with a prompt like, 'You are a McKinsey consultant. Draft a one-page executive summary for the CFO based on these results, following the pyramid principle.' This can save you 2-4 hours of painful wordsmithing and slide-crafting per presentation, letting you focus on refining the message.

Common questions

How do you become a Senior Data Insights Consultant?

Common routes in include Internal Promotion (Data Insights Consultant) (2-3 years as an L2 Data Insights Consultant), External Hire (Consulting Firms) (5-8 years experience in a similar role at a management consulting firm (e.g., Big Four, boutique analytics consultancy).) and External Hire (In-house Analytics/BI Teams) (5-8 years experience in a senior analyst or BI developer role within a large corporate environment.). Times vary with prior experience.

Where can a Senior Data Insights Consultant progress to?

This role can lead on to Lead Data Insights Consultant (3-5 years as a Senior Data Insights Consultant), depending on the skills you build.

What new skills matter most for a Senior Data Insights Consultant?

Increasingly, Prompt Engineering & LLM Integration and Causal Inference & Experiment Design. These are the skills our record of this role lists as growing.

You're not behind. You're right on time. The shift is only just beginning. Your role won't look the same in two years. Be the one who leads the change, not the one it happens to. Start my Senior Data Insights Consultant plan, free What happens next: a free account, then we build your plan as you set up. No card. Build your plan, see your roadmap and meet the twelve tutors matched to you. All free. When you're ready to start learning, it's £70 a month, billed monthly. Cancel any time and billing stops.

Senior Data Insights Consultant

Where should we send it?

Two short quizzes about you

Will AI change your work as a Senior Data Insights Consultant?

What's rising in its place

Prompt Engineering & LLM Integration

Causal Inference & Experiment Design

Skills this role draws on

Technical

How you actually get there, here

Internal Promotion (Data Insights Consultant)

External Hire (Consulting Firms)

External Hire (In-house Analytics/BI Teams)

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

Roles this leads to

One to one, on the work you already do

Everything else the record holds

The career path, and where it branches

Lead Data Insights Consultant (L4)

Where AI is starting to help

Automated Data Dictionary Creation

Hypothesis Generation Engine

Internal Knowledge Synthesizer

Executive Summary & Narrative Drafter

Common questions

Want a read on where you stand?