Successful Tag Management Is Impossible Without These Two Prerequisites
I talk a lot about Adobe’s tag management solution. That’s my job, and it’s also my passion. But I hate it when companies struggle with implementing tag management for reasons that are avoidable. There are two critical needs that every enterprise has but no tool or system can address: data governance and management.
It matters not if you have the best implementation or the best group of analysts out there. If you don’t have a handle on your data governance and a management process that is flexible as your digital assets change, you will have problems.
Data Governance: A Presidential Address?
The premise that data governance should look like a presidential address to Congress, where the leader spells out governance objectives, is a commonly held belief. However, the data governance process used by many companies is more like a crowdfunding event where everyone chips in their contributions. Is that an effective approach? No! (And not for the obvious reason: lack of directional focus.) The outcome of a poor data governance policy is a landfill of data – a massive, jumbled mess of pretty much useless information.
There is a way out of the data landfill and back to a place where you can uncover the nirvana of digital intelligence and be able to use the data you’ve collected data to find real and actionable insights you believe in. How do you get on the right path to this data governance nirvana? I have worked with many companies helping them on this journey, and while the trip is different for everyone, there is a set of core elements your data governance plan should have.
Core Data Governance Elements
Here are what I see as the fundamental elements of a solid governance plan:
Who are all of the stakeholders in your organization that need to be sold on the governance plan (or at least agree to the steps involved)? Have you met with them all? Do you plan to keep meeting with them to update on changes or modifications to the plan? Hint: you should.
How is workflow managed? You need to have request tracking, response processes, testing, all within defined task sets. And there needs to be accountability within the workflows. Read another way: blame. Who is responsible for maintaining or enforcing this data governance plan? Does that person have the right clout within your organization to do this job or will he or she be railroaded, pushed around to the point where they are not able to be effective?
Important to workflow is quality assurance. Too often, QA – real QA – is an afterthought, treated like a formality as part of user acceptance. Testing is simply checking off a box and moving on to the next step. But if you do not have a well thought-out test plan and a defined process for what steps to take when things break or fail testing, you are just begging for problems.
You’ve got to have the right support systems in place to facilitate the tag management process. Is there a workflow management system in place? Does coding documentation exist in a fluid, collaborative, and accessible location? Or is your infrastructure documentation sitting in someone’s email inbox or buried somewhere on their hard drive? Make sure organizational infrastructure is in place before you bite the bullet on a TMS solution.
Data Management: Are You Coding to Succeed?
A key component of governance is data management. I don’t mean managing the data you have captured in your analytics tool of choice, but rather the management of data or meta information in your digital assets.
Most of the time when I sit down with a client, the data and meta information they want to track looks like a kid’s playroom at the end of a play date – stuff is everywhere. The floor is covered with mismatched toys, game pieces, doll accessories, etc., all sitting around in no particular order. The same holds true when you’ve got disparate assets coded with no semblance of order.
The key items you want to track and measure are in that pile somewhere. Can you easily find them and track with specificity? Or are you tracking everything you see in the hope that you’ll later be able to sift through the bits and bytes and find what is really important to your business?
When you pull reports in your search for insights, you want data lined up so it is easier to read and digest. That takes effort. Unfortunately, most digital teams don’t put that same effort into organizing the data before they collect it.
Chances are good that your IT developers don’t know (or care) what an s_prop or an eVar is. And why should they? They don’t want to make their work more complicated and confusing for the next developer that comes along and has to work on the code. Set a product ID to something that makes sense for anyone who looks at the code (yourcompanynamedataobject.productId, for instance). Then you can tailor your analytics code or TMS system to pull that data object into the data library.
Yes, it takes a lot of time, energy, and money to properly set up a solid data management plan and structure on your digital assets. And, yes, you will get push back from IT, at first. But when you are done, you will have created a very nice, clean, and easy-to-update data layer that is able to be consumed by any tool or script in a much more reliable and stable method that is more resistant to site layout changes. Or you can try and sort through that pile of toys…um, data…on your site to get those pieces of data you really need.
Put Governance and Management at the Front of the Line
So, with all this said, you can probably see that you’ve got to have a solid plan in place before you even look at a tag management system. Of course, I’m biased and think our tools are the best. But honestly, no TMS solution – not even Adobe’s Activation – will function effectively without planning how you’re going to use it.