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Optimize the value of your data with digital policies

Optimize the value of your data with digital policies Photo by Helloquence on Unsplash

Unless you’ve spent the past few years on a beach with no internet, you know that AI and IoT are the way of the future. Organizations are brainstorming ways to join the party, and they’re coming up with fantastic ideas.

Unfortunately, I am already seeing many running into a brick wall when it comes to implementation. Think about trying to build the Millennium Falcon from a giant tub of Legos®, with all colors, shapes, and sizes mixed together, and you’ll have an idea of what they’re up against: data coming in from numerous sources, with no consistency about what information is collected, how different pieces of data are defined, where it’s stored, etc.

Get your data house in order with digital policies

Before you can roll out the next app or IoT device, you’ll have to make your data usable with digital policies. In other words, you’ll need to make rules about how you’ll sort your Legos®: what you’ll call the categories (shape, color, etc.), how you’ll handle Legos® that fit in more than one category, how people can find the specific Legos® they need, etc. And then you’ll have to decide what to do about that jumbled mess of Legos® you already have.

The topic could fill a book, but here are my suggestions:

Standardize how data is collected

Things like clicks and email opens are standardized by nature, but then there are things like comments and forms. A form’s construction determines the value of the data it provides. Will you use drop-down menus or free-form fields? Free-form fields are less limiting, but they also present problems. If you ask for the person’s highest level of education, for example, they could enter Bachelor, Bachelors, BA, etc.

You need digital policies - or guidance around what must always be done or never be done - that ensure everyone enters the same information in the same way so that all of your data, regardless of collection method and source, will be standardized.

Define how data should be categorized

Enterprise-level organizations use terms like taxonomy and hierarchy, but it just means deciding what to call various categories of data and deciding which are most important. Back to the Lego® example, should shape or color be more important?

Such decisions depend on your organization, how you use your data, and how you think you’ll use it going forward. Keep in mind that no piece of potentially important data should be left out. If it’s important, make a category for it, even if there’s not much to put in it right now.

Make it accessible

Data doesn’t add value if users can’t access it. You’ll need policies on teaching users how to slice and dice the data to find the insights they need. I recommend giving them some kind of takeaway -- a phone book, for an old-school analogy -- that provides the contact information for the data they need.

About that box of Legos®...

As intimidating as it may be, applying your digital policies retroactively is worth the investment, because it makes all of the data you’ve collected over the years as usable as your new data. Dedicate an “task force” (or outsource and augment your existing resources) to sort through your old data and apply the new policies. For instance, they could filter for level of education and apply the chosen format for a Bachelor’s degree throughout. Another task would be to apply the right taxonomy and hierarchy designations.


Developing policies that will untangle all of your data and make sure it stays untangled is no small challenge. But data is what makes the world go ‘round. Take care of it now, because it’s likely that your competition is already on it!


 Kristina Podnar, an advisor, digital-policy consultant and author of the new book, The Power of Digital Policy: A practical guide to minimizing risk and maximizing opportunity for your organization,

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