The Straightforward Guide to a Successful Data Rollout

You’ve worked hard to find the right data reporting tool for your team. Now you just have one challenge: rolling it out and getting the whole team to use it.

At Ashby we’ve helped a lot of customers bring new data to their teams through our recruiting analytics product. We often get questions about how to roll out a new data tool within an organization - and we have a lot we’ve learned that can help you with just that. In this post we’ll walk through some straightforward steps that will make a successful rollout of a new tool on your team a lot more likely.

If you’ve ever been through it, you know that rolling out a software tool and encouraging wide adoption isn’t easy. With technical software, like data reporting, it can be even harder.

Luckily, there’s an approach you can use to tailor your rollout and give yourself the best chance of not only getting full adoption of a new tool, but genuine buy-in from everyone using it. This is that approach, laid out step-by-step, so you’ll ask the right questions and find the right answers to set yourself up for success.

This article uses recruiting reporting and data software, such as Ashby, as an example, but this rollout method applies to any analytic tool, from Google Analytics in content marketing to efficiency data for manufacturing. The data may differ, but the rollout methodology remains the same.

Step one: Goal setting

From the start, you need to be thinking about the end. We encourage you not just to think over your goals, but to write them down formally and, as part of your rollout, share them with your team. But more on sharing in a moment.

It isn’t enough to say that you want everyone to regularly use this tool. You need to be specific. In your ideal outcome:

1. Who is using this tool?
2. What do they do with it?
3. How frequently do they access it?

You may end up writing a few different use cases. That’s a good thing, because it gives you nuance in how to approach the rollout with different groups in your organization.

For instance, your answers may look like, “Recruiters are using this hiring reporting tool to help them hire every day.” But, at the same time, they may also look like, “The Head of People is using this hiring reporting tool to see metrics and pull high level reports bi-weekly.” A single tool can do more than one thing for more than one person, and noting the nuance and the various use cases helps you explain the tool more effectively to different groups.

If you find yourself getting stuck on a question, make a note of it and return to it later. Flag who you need to talk to or what information you need to fill in those gaps.

At the end of this step, you should have a strong idea of how your team will use your reporting tool on a daily or weekly basis. Your answers to these questions will inform every other element of your rollout.

Step two: Determining scope

A critical part of a successful rollout is knowing exactly who the stakeholders are. This step is more than an offshoot of goal setting, and should include people who need to buy-in but may not be using the reporting software themselves.

The easiest question comes first: who wants this tool and why? Let’s say the hiring managers on your engineering team are frustrated with a lack of detailed information about their hiring process. They’re the ones who it will be easiest to roll out this tool to, because they’re asking for it.

Next, think of who needs to give their approval on the tool. If this group is not also a user of the tool, they may not be the easiest to convince, but their buy-in is crucial.

Finally, consider who isn’t using the tool, but will still be impacted by it. Maybe you have a small team of interns who will be asked to pull reports, even if they aren’t doing the hiring. This group doesn’t need to be convinced, but they will need to be involved in the rollout.

If you work in a larger organization, it may be helpful to put all these stakeholders in top-down order, to highlight where you need to start to achieve full buy-in. In this case, that would be: Executives > Hiring Managers on Engineering Team > Interns.

Approaching these three groups in the same way won’t get you as much success as taking a look at their unique needs and customizing your pitches and approaches. Maybe the executive team wants to hear about the ROI and hiring improvements this tool will make. Maybe the interns don’t care quite so much about ROI, but will be thrilled to hear that the software is easier to use than the current system. Give each group the story they need to fully buy-in.

The easiest way for you to do this is to make a note of what they’ll need, then gather the data they need to see. Creating a sample dashboard or environment within your new analytics tool for each group is a great way to do this. It feels more tangible and real than numbers in a slide deck. It also lowers the barriers for entry: even if they end up changing things later, you’ve given them a great place to start engaging with the tool. The side bonus of this approach is that it familiarizes you with the tool so you can answer questions more easily.

Step three: Review your data

Prior to rolling out the tool you will want to do an initial review of your data hygiene.

They say “numbers don’t lie” but real truth in numbers comes from good data hygiene. If you aren’t consistently updating your candidate details as they move through your funnel, the best reporting tool in the world won’t be able to help you track your time to hire. Give data tools clean, clear information to work with.

But be aware that even if you feel good about your data hygiene, reporting tools are likely to find flaws anyway. All analytics tools work like a blacklight: they show you messes you couldn’t see in areas that seemed clean. That’s not a bad thing, in fact it’s almost inevitable, just use some of the time you’re investing to clean up your original data.

The good news is that the higher-quality your reporting tool, the better it will be at cleaning up your data. Make sure to ask your point of contact to see how the tool can help you make this part easier.

Step four: Make a communication plan

Once you have buy-in from your stakeholders, don’t keep them in the dark about what’s coming next.

Create a timeline of your rollout and share it with each group. Your timeline will look different depending on what the tool is, how easy it is to adopt, and how many people will be using. it. Here are some examples of what you might include in yours:

• When will your data tool be available to check out?
• What day(s) will training take place?
• When should the team start using this tool for new info, such as incoming hires?
• How long will customer support be available?
• When will the team stop using old tools entirely?
• What’s the first day that everything needs to be fully moved over?
• What’s the last day data from older tools will be available before access is lost?
• When and how frequently will you be checking in with stakeholders?

Make a note if this timeline has wiggle room or if it needs to remain firm. This helps avoid misalignment surprises later.

A timeline may already be clear to you, but it may be less clear to others at various stages of adoption. An obvious reference document will also help answer questions for you, saving your bandwidth.

Follow-up with your stakeholders as the timeline progresses. You want to be active partners in the rollout, from beginning to end.

Step five: Move with intention

You have a plan, you have buy-in, you know what data you’re working with. Now you need to carry that success through the rollout process.

Rushing a rollout is a good way to fail quickly. Humans have a natural resistance to change, so even the most excited new user may be a little slow to take up some parts of the software. That’s not always because the old method or tool was better, but because it’s familiar. Stay consistent and lean on your new tool’s customer success team, product documentation, and any other tools they’ve offered to help you roll out.

Stay consistent with your setup, too. You’ll likely need to tweak your software as you go, but once it’s set up, change it slowly and not all at once. Good data results develop over time. If you mess with your setup too frequently, it will take longer to see the important info. Be patient as you observe the information develop.

Step six: Avoiding potential roadblocks

Any rollout is likely to encounter a few bumps in the road, no matter how well-planned. The best way to make even these bumps a little smoother is to consider them in advance so they don’t take you by surprise. We’ve outlined a few common hiccups and potential responses to help you troubleshoot.

Changes in management: Keep a paper trail of the decision-making process for your data tool, including notes about what rollout elements have been completed and when. If your leadership changes part-way through the rollout process, you’ll be ready to bring everyone up to speed.

Detractors: Some folks may disagree on the best tool for a job, or be resistant to change no matter how good it is. The best way to respond is to be empathetic and hear out any concerns instead of shutting them down. Make a list of the things you love about this tool in case you need to share it to win someone over.

Data issues: Maybe your use case is an edge case, or maybe something went wrong in the setup leading to unexpected results. Make sure you have the contact details of the tool’s providers, and check ahead of time if you’ll have access to a help desk or a specialist who can help if anything goes wrong. That’s an email you want before you need it!

Frustrating as they may be, these issues and others like them are nothing to worry about if the rest of your plan is solid. The stronger the rest of your rollout strategy is, the more easily you’ll be able to cope with surprises.

Success isn’t far off

A good rollout is almost as powerful as a good new tool. As you may have noticed, the biggest element of a successful rollout is time and planning. You may want the material to be ready yesterday, but going slowly and thoughtfully into a big data tool change is going to make everything else easier in the long run. It’s always worth it to invest real time and thought into doing this right.

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