Insights from our team

Welcome to the Hartley McMaster Insights blog. Here you'll find all the latest thoughts, tips, and stories from our consultants, covering data analysis and statistics, data science, and scenario modelling.

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    How to maximise value from data analytics

    Many companies investing in data analytics struggle to achieve the full value of their investment. Read on to understand why and how to avoid this.


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    Five ways data can help your business navigate stormy waters

    We are cursed to live in interesting times. As I write this, a war in Ukraine rumbles on, we sit on […]

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    Quality Assurance of Analytical Modelling: The importance of QA in Model Risk Management

    Quality assurance of analytical modelling in finance and in the public sector is well established. Yet outside these areas it’s often not given the attention it demands.

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    The Future of Impact Investment: Lessons in ESG from Regulatory Investment Planning

    If there seems to be confusion around the practical implications of ESG, much of it stems from the demands it […]

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    Your diversity, equity and inclusion initiatives are missing the point. Here’s how to fix them

    It is very difficult for diversity, equity, and inclusion initiatives to go beyond checklist exercises despite everyone’s best intentions. Much […]

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    Analytical model development and QA: 10 best practice components

    From risk management through to specification, here are the 10 most important things organisations should consider when putting an analytical model development and QA process in place.

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    What the A-level results crisis tells us about responsibility in decision analytics

    There are a lot of hot takes on the current exam results crisis. Amongst the cacophony of critical voices, you will even find a few offering thought-out alternatives. But subject these to any scrutiny and you will see they too have their own significant failings.

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    Benefits management: 5 reasons benefits managers need to hire analysts

    Without an analyst on your benefits team, you could be looking at fuzzy benefits, loose terminology and a shortage of numbers.

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    How NOT to predict football match scores using analytical modelling techniques

    Selecting a poor analytical modelling technique undermines a project before it starts.  Choosing a good technique that’s wrong for the […]

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    Helping RNIB inform their strategic priorities with multi-criteria decision analysis

    We were honoured to work with RNIB on a pro bono project to help identify the charity’s strategic priorities.

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