{"id":1851,"date":"2019-07-05T21:09:38","date_gmt":"2019-07-05T20:09:38","guid":{"rendered":"https:\/\/marriott-stats.com\/nigels-blog\/?p=1851"},"modified":"2019-07-16T11:38:58","modified_gmt":"2019-07-16T10:38:58","slug":"pay-gaps-9-how-to-close-your-gender-pay-gap-with-dmaic-2","status":"publish","type":"post","link":"https:\/\/marriott-stats.com\/nigels-blog\/pay-gaps-9-how-to-close-your-gender-pay-gap-with-dmaic-2\/","title":{"rendered":"Pay Gaps #9 – How to close your gender pay gap with DMAIC"},"content":{"rendered":"

So you’ve measured your gender pay gap (correctly I hope!) but you don’t know what to do next?<\/p>\n

You are not alone, many employers are still getting their heads around how to interpret their pay gaps and are struggling to work out what it means for them.\u00a0 One outcome is that many consultants are out there waiting to advise you and among them are statisticians like me.\u00a0 But what exactly is it that statisticians bring to the party compared to other consultants?\u00a0 One answer is that statisticians use DMAIC<\/strong><\/span> to help organisations improve the quality of their products, services and processes.<\/p>\n

<\/p>\n

What is DMAIC?<\/b><\/span><\/h4>\n
    \n
  1. DEFINE<\/strong><\/span> the goal to be achieved<\/li>\n
  2. MEASURE<\/strong><\/span> the problem so you know where you are today compared to your goal<\/li>\n
  3. ANALYSE<\/strong><\/span> the data so as identify where & why the problem exist and the relative importance of potential means to reduce the problem<\/li>\n
  4. IMPROVE<\/span><\/strong> the process\/product\/service using an action plan built upon your analysis<\/li>\n
  5. CONTROL<\/strong><\/span>, once the improvements has achieved the goal, monitor and control to prevent it from reoccuring.<\/li>\n<\/ol>\n

    DMAIC<\/strong><\/span> is used by many practitioners<\/a> who seek to improve the quality of a business’s product, service, process or outcome.\u00a0 A gender pay gap can be regarded as a measure of the quality of an employer when it comes to diversity and therefore the full gamut of statistical tools and approaches can be applied to reducing and eliminating pay gaps.\u00a0 These tools and approaches come under a statistical heading of Quality Improvement.<\/p>\n

    The Quality Improvement Section<\/strong><\/span><\/h4>\n

    I am an active member of the Royal Statistical Society<\/a><\/strong><\/span> and until last year, I was the Chair of the Quality Improvement Section (QIS)<\/strong><\/a> <\/span>which advises the RSS on statistical issues within this field and also organise events to improve the skills of its practitioners.\u00a0 This year, QIS produced a video explaining what the section does and I appear in this video (1 min 13 secs in) and talk about how employers can use DMAIC<\/strong> to close their gender pay gap<\/a>s.\u00a0 Please do have a look to hear what I & my colleagues in QIS have to say!<\/p>\n

    What do Statisticians add to DMAIC?<\/strong><\/span><\/h4>\n

    Perhaps you might be saying to yourself, “DMAIC is obvious!\u00a0 Many consultants use something like that even if they use different words”<\/em>.\u00a0 I don’t disagree with that sentiment but I would like to go through the 5 steps again and illustrate the advantages that statisticians have over other areas of expertise.<\/p>\n