Always ask kenapa

Posted by Marcus Hammarberg on December 5, 2014
Stats

At my current client we are gathering the most important data (number of customers) for the company well-being and showing it to all the staff, every morning. This is great and have proven very useful to get the attention and interest for everyone. We have spontaneous applauds when we are doing great - we have discussions (also spontaneous) on days with bad data.

After the morning meeting with the entire staff (quite literally the Morning Prayer, being a Salvation Army hospital :)) we hold a morning briefing with the extended management of the hospital.

Lately I’ve stared those meetings a bit different. Quite simply I just point to the diagram with the data up to yesterday and ask:

Kenapa?

The result was a bit surprising and also rewarding

At my current client we are gathering the most important data (number of customers) for the company well-being and showing it to all the staff, every morning. This is great and have proven very useful to get the attention and interest for everyone. We have spontaneous applauds when we are doing great - we have discussions (also spontaneous) on days with bad data.

After the morning meeting with the entire staff (quite literally the Morning Prayer, being a Salvation Army hospital :)) we hold a morning briefing with the extended management of the hospital.

Lately I’ve stared those meetings a bit different. Quite simply I just point to the diagram with the data up to yesterday and ask:

Kenapa?

The result was a bit surprising and also rewarding Of course (:)) Kenapa means “Why?”. Why did that data happen yesterday? Is there something special that happened?

I noticed that the team was starting to defend bad data, by pointing to the better parts instead; “Yeah, Sunday was bad… but look at the Saturday!”

That’s understandable but not helpful. And there’s a couple of principles around targets and measurements that I took for granted but that was news to my client.

Measure to learn

When we are measuring data like we do, there’s something that needs to be very well-known at the outset; WHY are we measuring this data.

We are not measuring the data to hold people accountable or punish them - we are measuring the data to learn and improve.

I’ve noticed that this has to be communicated over and over. I presume that is because people are used to the opposite; being held accountable for, especially bad performances.

If you can turn this view into instead viewing it as something to learn from there not only a much nicer atmosphere but it’s more fruitful as well. It’s not you reporting to me but us, together trying to improve bad and celebrating good.

There’s only data

There's no good or bad news - there's only news

I don’t known how many times I have restated this, both in Indonesia and in Sweden. This little phrase is one way to remember that we are measuring to learn.

To me it’s also being honest with yourself, and start where you are (like kanban teaches us. There’s no use lying to ourselves and paint a prettier picture than the truth.

This is where we are now - how can we improve. This is the data - what can we learn?

Also, related to this, we need to make sure that everyone understands what we are measuring and what that means. If not you will note that the data is uninteresting and ignored by many. That’s not really useful if you want to learn.

Two data points are not a trend

I’m the biggest sinner here, let that be made clear. I’m so eager to start analyzing and trying to improve. With one bad day of data I want to change things around.

It’s better to play it cool and wait until you have more data. In our case we saw that certain days (Sundays) always was hovering about 1/3 of the patient count compared to the other days. The first Sunday we where really scared. But then the second was the same. And the third. This was a recurring phenomena and the trend was clear - but it took us 3 Sundays to start seeing that trend.

Now; why is that? And what can we do about it? We did somethings about it but we didn’t react on the first occurrence.

Always ask “Kenapa?”

One of the most profound experiences for my client, and that made them realize that me and my team was serious about “measuring to learn”, was when we had an awesome day.

I again started the morning briefing with: “Kenapa” and the looks was just puzzling. I had asked them a couple of times already, on bad days, Why we did as we did. And we have had some fruitful discussions about that and even implemented a couple of countermeasures (as I mentioned above). But now?! We were doing good! Why are you asking us Why?

Well - the data tells us that we are doing something good. Let’s stop and think for awhile what that is. So that we can do more of it and maybe even improve on it. Maybe there’s something that we have stopped doing during these days - let’s make sure that we don’t start doing them again.

Summary

If you go through the trouble of gathering data and if you are serious about using it to improve:

  1. Measure to learn and not to punish

  2. There no good or bad data - there’s just data. Make sure everyone feel safe to report the real data, by emphasizing this.

  3. To act until you have enough data to see the trend

  4. Ask WHY - even on the good days



Published by Marcus Hammarberg on Last updated