{"id":1000,"date":"2022-12-26T09:54:00","date_gmt":"2022-12-26T09:54:00","guid":{"rendered":"https:\/\/wp.memri.io\/?p=1000"},"modified":"2022-12-26T09:54:00","modified_gmt":"2022-12-26T09:54:00","slug":"improve-your-retrospectives","status":"publish","type":"post","link":"http:\/\/159.223.219.139\/index.php\/2022\/12\/26\/improve-your-retrospectives\/","title":{"rendered":"Improve Your Retrospectives: Here\u2019s how you can use Machine Learning in your organization"},"content":{"rendered":"\n

Within Memri we do retrospectives at the end of each sprint (every 2 weeks). We know that it helps us find things we can improve on, learn from and identify what is going well. But still, doing the same type of retrospective each sprint can feel boring after some time. The result? People zone out, leading to more superficial insights. In an attempt to make those retrospectives more fun, and therefore more valuable we used some of the magical AI tools out there and that has worked! Here\u2019s how we did it. <\/p>\n\n\n\n

How our retrospectives work <\/h3>\n\n\n\n

When facilitating it is best to help people take a step back and reflect on what they\u2019re doing during the retrospectives. At times that can be quite a challenge, it\u2019s easy to focus on that one ticket that wasn\u2019t closed yet and start discussing what things need to happen to close it. That\u2019s not what the retrospectives are for. Instead we believe it\u2019s more valuable to look at  the reasons why the ticket wasn\u2019t closed. Was it because we scoped it wrong? Was it because we prioritized other things? Was the team sick? Unmotivated?  <\/p>\n\n\n\n

To help the team take a step back, we start by doing simple creative exercises. \u201cDraw what this sprint was like for you\u201d has been one of my favorites and led to quite hilarious drawings. Some in our team can draw really well,, and some, including me, are terrible at it. Luckily that doesn\u2019t matter. Everyone gets a chance to explain what they\u2019ve created and more importantly, explain their reasoning behind it. That\u2019s where the real information lies. <\/p>\n\n\n\n

When everyone has had a chance to explain their drawing, we continue to a simple Start, Stop, Continue(& Appreciation) format<\/a>. Everyone leaves their thoughts individually, after which we go through them, cluster into topics and add concrete action points we can take forward. The appreciation category is there to actively remind us of sharing appreciation for your colleagues publicly as well.<\/p>\n\n\n\n

Machine Learning during your retrospectives <\/h3>\n\n\n\n

Even though the process of drawing worked to get the conversation to a different level, some colleagues were still uncomfortable about their drawing skills. That\u2019s when we started using Machine Learning tools. <\/p>\n\n\n\n

Instead of drawing the image, we now create an image out of thin air by using any AI image generator we can get our hands on, Stable Diffusion<\/a>, Dall-E<\/a>, Midjourney<\/a>, anything will work. The drawing is replaced by simply creating a prompt of the image that describes your sprint best. Again it\u2019s not the actual image, it\u2019s the reasoning that has the most value. The additional benefit is however clear, there\u2019s a lot more laughing. <\/p>\n\n\n\n

The image generators are really impressive, but can also lead to hilarious and even creepy creations. Sharing those failed prompts is of course highly encouraged. Here are some gems. <\/p>\n\n\n\n

\"\"
Representing a sprint where someone had a lot of zoom meetings<\/figcaption><\/figure>\n\n\n\n
\"\"
A sprint where we worked together really well<\/figcaption><\/figure>\n\n\n\n
\"\"
A sprint during which we focused on releasing our app<\/figcaption><\/figure>\n\n\n\n

Template & Instructions for facilitating a retrospective that includes Machine Learning in your organization<\/h3>\n\n\n\n
    \n
  1. Create a collaborative working space yourself or use our template for Figma<\/a>, or Google Drawing<\/a>. <\/li>\n\n\n\n
  2. Create a Workflow at forehand. Create your own, or just copy our workflow from <\/li>\n\n\n\n
  3. Provide links to AI image generators, there are plenty of demo\u2019s available for free find an overview here!<\/li>\n\n\n\n
  4. Give people 10 minutes to create and add their images <\/li>\n\n\n\n
  5. Discuss images, capture insights, summarize the main insights from all what was shared. <\/li>\n\n\n\n
  6. Move to Start, Stop, Continue & Appreciation section. <\/li>\n\n\n\n
  7. Give everyone 15 minutes to add tickets to the board. <\/li>\n\n\n\n
  8. Go through the tickets for Start, Stop, Continue, ask someone from the group to read them out and help with clustering <\/li>\n\n\n\n
  9. Once those three categories have been completed. Go to the topics and ask what action needs to be taken. Make it concrete, add an owner and add deadlines. <\/li>\n\n\n\n
  10. Go to the Appreciation category, ask people to read out their appreciation. We often try to create a \u201ctrain\u201d. Person A appreciates person B, Person B shares their appreciation for Person C, Person C shares their appreciation etc. No backsies allowed!<\/li>\n\n\n\n
  11. Close the meeting, share the action points in a public place and use that in the next retrospective to see what happened. <\/li>\n<\/ol>\n","protected":false},"excerpt":{"rendered":"

    Within Memri we do retrospectives at the end of each sprint (every 2 weeks). We know that it helps us find things we can improve on, learn from and identify what is going well. But still, doing the same type of retrospective each sprint can feel boring after some time. The result? People zone out, […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-1000","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"_links":{"self":[{"href":"http:\/\/159.223.219.139\/index.php\/wp-json\/wp\/v2\/posts\/1000","targetHints":{"allow":["GET"]}}],"collection":[{"href":"http:\/\/159.223.219.139\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/159.223.219.139\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/159.223.219.139\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"http:\/\/159.223.219.139\/index.php\/wp-json\/wp\/v2\/comments?post=1000"}],"version-history":[{"count":0,"href":"http:\/\/159.223.219.139\/index.php\/wp-json\/wp\/v2\/posts\/1000\/revisions"}],"wp:attachment":[{"href":"http:\/\/159.223.219.139\/index.php\/wp-json\/wp\/v2\/media?parent=1000"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/159.223.219.139\/index.php\/wp-json\/wp\/v2\/categories?post=1000"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/159.223.219.139\/index.php\/wp-json\/wp\/v2\/tags?post=1000"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}