31:T426,md`**How can we use this chart?** Let's make this chart actionable! If we could jump back to 07 Jul an analyse this chart on that day, we could check with the team what are the items in progress for more than 28 days (around 40% red). By understanding what is the work and why it's taking too long, this can help to identify some improvement opportunities, blockers or hidden dependencies, and then, come up with actions to tackle these points. Apart from the above conversation, one clear action to perform is to prioritise these older items over the younger ones. With this prioritisation call, we can have an agreement with the team to focus on getting the work done instead of starting new ones or focusing on the fresher ones, in other words, limit work in progress. By doing these actions, we should have a greener chart and this may help the team to deliver value faster to the customer. (Of course, there are other factors that impact the ability to deliver value faster to the customer, but in this context, we are focusing only on the aging work.)`32:T7c6,picasso.chart({ element: container, data, settings: { collections: [ { key: 'stacked', data: { extract: { field: 'Date', props: { line: { field: 'Band' }, end: { field: 'Percent' } } }, stack: { stackKey: d => d.value, value: d => d.end.value } } } ], scales: { y: { data: { collection: { key: 'stacked' } }, invert: true, expand: 0.2, min: 0, max: 100 }, t: { data: { extract: { field: 'Date' } } }, color: { data: { extract: { field: 'Band' } }, type: 'categorical-color', range: ['#E74C3C', '#F5B041', '#ABEBC6', '#2ECC71'] } }, components: [ { type: 'axis', dock: 'left', scale: 'y' }, { type: 'axis', dock: 'bottom', scale: 't' }, { key: 'lines', type: 'line', data: { collection: 'stacked' }, settings: { coordinates: { major: { scale: 't' }, minor0: { scale: 'y', ref: 'start' }, minor: { scale: 'y', ref: 'end' }, layerId: { ref: 'line' } }, layers: { curve: 'monotone', line: { show: false }, area: { fill: { scale: 'color', ref: 'line' } } } } }, { type: 'grid-line', x: { scale: 'x' }, y: { scale: 'y' }, ticks: { show: true, stroke: 'grey', strokeWidth: 0.2, strokeDasharray: '3, 3' }, minorTicks: { show: false, stroke: 'grey', strokeWidth: 0.2 } } ] } })33:[] 2f:{"title":"How to tackle Aging Work?","cells":[{"id":0,"value":"md`# How to tackle Aging Work?`","pinned":false,"hidden":false,"mode":"ojs"},{"id":421,"value":"html`
`","pinned":false,"hidden":false,"mode":"ojs"},{"id":6,"value":"md`Knowledge work is a term used to refer to some professions that produce knowledge as the main outcome. Knowledge work is perishable, which means it loses value over time. Thus, the fresher the work the more value can be delivered to the customer.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":375,"value":"md`A good way to keep the work in progress fresh is to constantly assess how long has each piece of work been in progress. One effective technique to do this is using the Aging Work chart.\n\nWith the Aging Work Chart, it's possible to see how fresh is the work being done by a specific team. Let's check now how to read the information contained in this chart.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":389,"value":"md`Imagine you have 4 different bands. Each band considers a specific group of tasks in progress. Each group is organised by how long has each piece of work been in progress. For example, band 4 (green) aggregates tasks that have been in progress less than 7 days, band 3 (light green) between 7 and 14 days, and so on.\n\n(*The rationale behind this visualisation I got from a tool called Mazzlo - https://www.mazzlo.co, which supports teams in their continuous improvement process by providing some analytics and coaching.*)`","pinned":false,"hidden":false,"mode":"ojs"},{"id":400,"value":"html`
`","pinned":false,"hidden":false,"mode":"ojs"},{"id":380,"value":"md`\n\nFor the chart below, we are going to use this specific configuration:\n\n*Band 1 (red): Items in progress over 28 days.*\n\n*Band 2 (orange): Items in progress between 14 and 28 days.*\n\n*Band 3 (light green): Items in progress between 7 and 14 days.*\n\n*Band 4 (green): Items in progress for less than 7 days.*`","pinned":false,"hidden":false,"mode":"ojs"},{"id":111,"value":"html`

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":361,"value":"md`## Aging Work chart`","pinned":false,"hidden":false,"mode":"ojs"},{"id":175,"value":"//html`

`\ncontainer = html`

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":112,"value":"html`

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":406,"value":"md`The x-axis represents the time frame in days.\n\nThe y-axis represents the percentage of items in progress for each band.\n\nSo, we can say that on 07 Jul we had more than 40% of the work in progress being in progress for more than 28 days, which is a huge amount of work that is aging.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":436,"value":"md``","pinned":false,"hidden":false,"mode":"ojs"},{"id":430,"value":"$31","pinned":false,"hidden":false,"mode":"ojs"},{"id":471,"value":"md``","pinned":false,"hidden":false,"mode":"ojs"},{"id":474,"value":"md`In the chart below we have a real example of a team that has started analysing the Aging Work to identify opportunities for improvement. (*This is a Mazzlo \"Work Age\" chart.*)`","pinned":false,"hidden":false,"mode":"ojs"},{"id":460,"value":"md`

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":497,"value":"md`The story behind this chart is that an experienced Iteration Manager was allocated to support this team on Aug 01. He helped the team to visualise the Aging Work and they agreed on limit work in progress and to focus on tackling the blockers and issues associated with the oldest work items. The result was fantastic. It's pretty easy to visually identify the improvement on the chart above.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":508,"value":"md``","pinned":false,"hidden":false,"mode":"ojs"},{"id":500,"value":"md`Things like that actively help teams to achieve another level in their improvement process and also help them to release the pressure that often impacts underperforming teams.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":501,"value":"md`Tackling Aging Work alone is not going to have an enormous impact on a team's ability to deliver value to the customer. However, when used in conjunction with other techniques, such as Cycle Time Scatterplot analysis and Throughput Run chart, it can be truly powerful.`","pinned":false,"hidden":false,"mode":"ojs"},{"id":405,"value":"html`

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":24,"value":"$32","pinned":false,"hidden":false,"mode":"ojs"},{"id":273,"value":"data = {\n const arr = [['Date', 'Band', 'WIP', 'Percent']];\n\n await d3.csv(\n \"https://gist.githubusercontent.com/gabovailati/c0adc579b96354caba4c3ee3e705a410/raw/83a605b2c170eaa2bdf056079688722624958944/agingwork.csv\",\n function(d) {\n arr.push([\n d3.timeParse(d.date).toLocaleString(\"en-GB\", {\n day: \"2-digit\",\n month: \"short\",\n timeZone: \"Australia/Sydney\"\n }),\n d.band,\n +d.wip,\n +d.percent\n ]);\n\n return {};\n }\n );\n\n return [\n {\n type: 'matrix',\n data: arr\n }\n ];\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":9,"value":"d3 = require(\"d3@5\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":167,"value":"picasso = require(\"picasso.js\")","pinned":false,"hidden":false,"mode":"ojs"}],"files":"$W33","stdlib":"1","titling":"auto"}