TL;DR? There are four things you can do to make a huge project not only seem manageable but be manageable, even as you keep saying to yourself, “What was I thinking taking this on?!?” (1) Know what you’re trying to do and break it down into manageable steps as soon as possible. (2) Track your progress in a way that fosters momentum. (3) Be realistic about your energy levels. (4) Plan for implementation in a way that, as much as possible, lets you be mindful but thoughtless (i.e., well-considered but requiring no real decision-making when it comes time for application).
Do you ever overthink or overanalyze to the point where you stop making decisions and taking action? Where you’re afraid that the choice you’re about to make isn’t the BEST choice, so you wait it out a little more, and maybe research a little more, and maybe gather together more data … just so you can be SURE? That’s called analysis paralysis.
Debunking the myths of being data driven and being successful can set you free.
If you’ve ever targeted an email marketing campaign to a specific demographic, assigned a category to your blog post, or chosen a hashtag for your social post, you’ve used data classification. Classification is basically the process of chunking up or organizing your data, into different groups or under different labels, so that you can quickly isolate and bring together all of the things that belong to that group, so that you can do something with that group:
- monitor it as part of a metric,
- investigate it and compare it to other groups,
- work with it, like with targeted marketing campaigns, or
- plan with it.
In this post, I’ll discuss the problems that arise from unclassified or improperly classified data, and give some pointers on how to create and apply your own classifications.
In order to effectively close the gap between where you are now and where you want to be, you need to know that the gap exists and how big or small it is. One way to do this is with a reporting tool called a scorecard. Much like the checked and unchecked items on a to-do list, a scorecard gives you a snapshot of the gap between where are you now and a target, where the target can be a growth goal you’ve set for yourself, or a projection of where you think you’ll be by a certain date, all things considered.
TL;DR? Big data knows what questions people have, and you can capitalize on that to generate an endless list of answer-focused content ideas that draw from and showcase your experience, knowledge, and expertise. Scroll down to the section titled ‘Bringing it together’ for a quick list of the steps. Scroll back up for the nuance.
There’s nothing new under the sun, so what could you possibly have to offer the world that hasn’t been addressed before?
I’m always a big advocate of asking people for help when I get stuck, and, as it turns out, people are telling you what they want you to talk to them about all of the time. If you’re systematic about how you listen, you’ll build up quite a data store to flip through the next time you’re missing your muse and staring down a blank page and a deadline.
You want data insights at a glance, but it’s hard to digest and process a large volume of data, and you’re creating and collecting more data all of the time. You’re suffering from DRIP: you’re data rich but information poor. To get information, you turn to dashboards, but, if you don’t design them correctly, you can become dashboard rich but information poor, what I’ll call DRIP 2.0.
In this post, I’ll talk through 3 steps, with guides, for designing dashboards to generate insights for business decisions while all forms of DRIP.
TL;DR? You can grow your YouTube channel without falling prey to cheap clickbait tricks and other “dark side” habits; the secret is providing value with your content and being strategic with your content-packaging SOPs. Scroll down to the Video Packaging Essentials Checklist for some content packaging points for your own YouTube upload checklist.
How do you choose your next step? You’d like to do more of what’s working, but sometimes you’re not sure what parts of what you’re doing are working, or whether that pivot you’re considering might resonate with your target market, so you’re not sure what you should do more of or where to focus your efforts. In this post, I demonstrate three ways to use surveys to quickly get the data you need to make an informed next step.
This is a story about how I pulled together my historical data and my company’s philosophy and mission statements to adapt and generate virtual presentation SOPs for the pandemic and beyond.
When we talk about Diversity, Equity and Inclusion (DEI) efforts, we frequently turn to the data to see how we’re doing relative to our own internal goals, and, as possible, how our efforts and relative success rates compare to those in our local communities and others in our industries. That is, we typically talk and think in terms of benchmarks and progress towards a target percentage. But we don’t just need to wrangle and analyze the data. We also need to communicate the findings of the analysis so that we can figure out what to do next, and this is where choosing the right visualization comes in. In this post, I discuss how different visualization choices enable different understandings of the data, and different conversations and decisions around the data.