The right conditions
About a month ago we planted grass for a new lawn. It’s been bare dirt for the first 7 months we lived in the house and we’re excited to see something green grow.
We worked with a landscaper to help plant our grass lawn. He was excellent to work with, but the process required a ton of patience.
I first met with him last fall and made a plan for planting grass.
“Can we plant this week?” I asked.
“No, it's too late in the year and a freeze is coming this weekend. We will need to wait until spring.”
So we waited through a long Michigan winter and as soon as it hit April and temperatures reached above 60, I called the landscaper.
“Can we plant this week?”
“No, we need the ground and air temps to be consistently warmer”
So we waited.
By early June it wasn't just warm it was hot.
“Can we plant now?” I asked him.
“No, we haven't had rain in 6 weeks and no precipitation in the forecast. It would be a struggle “
The last week of June he finally came out and on a Friday afternoon prepped the topsoil and planted grass seed.
He pulled me aside when he wrapped up “This evening we have rain coming for the first time in 2 months. More rain is expected throughout next week. I know you had to wait a while but this is the right time to plant.”
The rain came. And within a week we had green grass popping up everywhere across our yard.
We are incredibly happy with the results.
A few different ways this project could have turned out:
I could have planted the grass myself. In spite of all my internet research I likely would have planted too early or too late and failed.
I could have demanded my landscaper plant grass as soon as possible or threaten to find someone else.
I could have hired a different landscaper who would get me a yard in May like I wanted. That also would have failed.
Our landscaper knew that I actually wanted a lush healthy yard, and so he rebuffed my many requests to plant sooner. In the end, it was much better to trust the expert.
What’s the point?
There's a right context for a data project. The temperatures have to be right. You need rain in the forecast.
What could be poor conditions for a data project?
Leadership transitions
Budget cuts
Substantial hiring initiative
Organization and team realignment
A team that’s happy with the status quo.
Pushing ahead with a cloud migration or data platform overhaul when conditions are poor will leave you over budget and underwhelming results.
Finding a data consultant (or landscaper) who will tell you “No, now's not the right time” can save you time, money, the trust of leadership, and maybe the future of your team.
It was good to see you today,
Sawyer
