{"id":6351,"date":"2024-09-19T09:00:14","date_gmt":"2024-09-19T07:00:14","guid":{"rendered":"https:\/\/getnave.com\/blog\/?p=6351"},"modified":"2024-10-03T11:44:33","modified_gmt":"2024-10-03T09:44:33","slug":"cycle-time-spikes","status":"publish","type":"post","link":"https:\/\/getnave.com\/blog\/cycle-time-spikes\/","title":{"rendered":"Cycle Time Spikes? Here\u2019s Why You Shouldn\u2019t Panic Just Yet"},"content":{"rendered":"
<\/div>\n

Let me know if this sounds familiar.<\/p>\n

You\u2019re sitting there, looking at your flow metrics.<\/p>\n

Your cycle time spikes, and your throughput drops compared to last week.<\/p>\n

Your heart sinks, and your first instinct is to think, “Something\u2019s off. Do we need to fix this? Is the team slowing down? Did we drop the ball somewhere?”<\/em><\/p>\n

That gut reaction? I completely get it. I’ve been there.<\/p>\n

But here\u2019s the thing. And this is where the real problem lies:<\/p>\n

When you\u2019re focusing too much on comparing your results side by side <\/span>without stepping back to think about the natural variation that\u2019s always happening in your process, you\u2019re setting yourself (and your team!) up for failure.<\/p>\n

Here\u2019s what typically happens.<\/p>\n

You see that spike in cycle time, and suddenly, you\u2019re in firefighting mode. You start digging, looking for what\u2019s \u201cbroken,\u201d and scrambling to figure out how to fix it. Maybe you even gather the team, telling them the numbers don\u2019t look good this week and something has to change. And the urgency kicks in. Sound familiar?<\/p>\n

Here\u2019s what I want you to understand: not every deviation in your metrics means something is wrong.<\/strong><\/p>\n

Let me say that again\u2014most of the time, those shifts are just part of the normal variation in your workflow.<\/em><\/p>\n

Here\u2019s where things get tricky.<\/p>\n

When you treat every little dip in throughput or spike in cycle time as a red flag, you\u2019re constantly second-guessing yourself, your team, and the process. You end up reacting to the wrong signals and making unnecessary adjustments.<\/p>\n

This is where it gets dangerous.<\/strong><\/p>\n

You might start tweaking the process\u2014maybe adding new policies, changing your WIP limits, or even restructuring your team\u2014all because of something that might not even be a problem.<\/em><\/p>\n

You\u2019re all working harder, but are you really making things better? Not necessarily.<\/p>\n

Here\u2019s what you need to know:<\/strong> not every fluctuation in your data is a crisis.<\/p>\n

Don\u2019t try to fix issues that aren\u2019t really issues. You\u2019re probably making things worse by doing that. You\u2019re spinning your wheels, trying to solve problems that don\u2019t exist, and in the process, you\u2019re creating new ones.<\/p>\n

<\/div>\n

I want to help you break free<\/strong> from that.<\/p>\n

Here\u2019s the truth you need to internalize: variation is normal.<\/strong><\/p>\n

It\u2019s just a part of how systems work. Cycle times will fluctuate. Throughput will go up and down. WIP might spike one week and stabilize the next. These changes are not always signs of a problem.<\/strong><\/p>\n

If your team\u2019s cycle time is a little longer than usual this week, does that automatically mean something is broken? No, it could just be that you had a couple of larger tasks in the queue, or maybe the team was focused on more complex work.<\/p>\n

But here\u2019s the real question: where do you draw the line between normal variation and a real issue that needs attention?<\/p>\n

How do you know when to take action?<\/strong><\/p>\n

You can\u2019t (and shouldn\u2019t!) react to every single change. What you need is a system in place that helps you make the right decisions at the right time. And that\u2019s where setting thresholds<\/strong> comes in.<\/p>\n

Setting a threshold means defining what\u2019s considered \u201cstable\u201d for your process. It\u2019s about understanding the typical range of variation and using that to determine when something genuinely needs your attention because it\u2019s putting your performance into question.<\/p>\n

In the next article,<\/strong> \u201cNatural Process Limits 101: How to Set Thresholds That Drive Continuous Improvement\u201d<\/a>, we\u2019ll dive deeper into exactly how to set those thresholds and figure out what \u201cstable\u201d really looks like for your process. I\u2019ll show you how to use the tools you already have to make reliable data-driven decisions that guide your improvement initiatives.<\/p>\n

But for now, here\u2019s what I want you to do: take a deep breath and remember this\u2014not every bump in the data is a reason to sound the alarm.<\/strong> Sometimes, it\u2019s just part of the ride. And that\u2019s okay. Let things flow, trust the process, and know when to act.<\/p>\n

Thanks for tuning in, and I\u2019ll see you next Thursday, same time and place, for more managerial goodness! Until then, take care.<\/p>\n

<\/div>\n
<\/div>\n
<\/div>","protected":false},"excerpt":{"rendered":"

Let me know if this sounds familiar. You\u2019re sitting there, looking at your flow metrics. Your cycle time spikes, and your throughput drops compared to last week. Your heart sinks, and your first instinct is to think, “Something\u2019s off. Do we need to fix this? Is the team slowing down? Did we drop the ball […]<\/p>\n","protected":false},"author":1,"featured_media":6350,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"yasr_overall_rating":0,"yasr_post_is_review":"","yasr_auto_insert_disabled":"","yasr_review_type":"","footnotes":""},"categories":[70],"tags":[],"class_list":["post-6351","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-team-performance"],"acf":[],"yoast_head":"\nCycle Time Spikes? 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