Fostering a data-driven culture within your organization is a challenge many companies face.
Learn from Erica Eischeid, Analytics Consultant at Adobe, how to:
- Understand key areas of data democratization
- Mature your organization's overall data governance practice
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Hi everyone. My name is Erica Eischeid. Thank you for joining me at the Virtual Analytics Summit. And today I'm going to be speaking with you about creating a data-driven culture through data democratization. So what does data democratization mean? We aren't talking about democratization and getting into the exciting area of politics in this space. What I mean is democratization in that true sense of the word: Is this data available to all? So you've got analytics tools that are in place. Users have access to it when they need it. Training is available so that they can up-level their knowledge and reporting is shared regularly throughout your organization. How does this fill a data-driven culture? Essentially the availability and access to analytics makes it possible so that people can make decisions based on data. They can celebrate wins with data and it can become woven into the fabric of your business.
There are six key areas of data democratization that I want to talk through today. Tools and infrastructure, data delivery, enablement and communication, value realization, user administration and access. And then accountability is going to be a layer through each of these. So let's start by talking about tools and infrastructure. This refers to the actual ] systems that you have in place collect data and the tools that you're using to report on that data. In this initiated sort of crawl phase, your analytics tools might exist for major channels but you don't have anything for your smaller channels or people are just kind of ad hoc using what they need to. And visualization tools are usually limited to out-of-the-box capabilities when an organization moves into an emerging area in this next phase, analytics tools exist for more, but not all the channels. Usually there aren't integrations in place between offline data or different digital tools and visualizations.Tools might be in place, but they're used in a pretty limited capacity. In an advanced capacity, your analytics tools are going to be well-defined and you're going to be able to look at reporting and data from a holistic standpoint. When I work with clients that are in the advanced capacity, they're usually using things like EDWs and data lakes and they're pushing their visualization boundaries and working with tools like Tableau, Power BI and those different types of tools. So how do you know where your organization is? Start by asking yourself some simple questions. Do you know what your company systems of record are for analytics, CRM, ad performance, and so on? Can you report across these tools? Are you using just out-of-the-box reporting or have you guys started to work with some of those advanced visualization tools? And do you know who is accountable for analytics and reporting tools? Do you know who's accountable to make sure that they're implemented and established in your organization?
Steps you can take to move yourself along the maturity curve. If you are in that initiated phase, start with simple steps like creating an inventory of tools so that everyone in your organization can know, "Hey, I need to report on site analytics. What is the tool we use?" And then start establishing visualization tools of record, especially for different report types. You know, if you are sending out an email with reports that are attached, make sure that it's established that "Hey, we attach things in a PDF format. When we create a dashboard, we do that in an Excel format." When you start moving from emerging into advanced, you can start looking at those different integrations between tools. Start combining data between your site analytics, your digital ad campaigns, your CRM initiatives, and work on deploying some advanced visualization tool, Tableau, Power Bi, that I've mentioned maybe it's, you know, as simple as creating spark pages that people can refer to.
If you are in an advanced capacity, that doesn't mean, "Hey, okay, we're done. We don't have to do anything to push us forward." You still want to continue to innovate. And that will mean expanding on connected data capabilities, continuing to mature the tools your organization has implemented and driving things forward. The benefits that you're going to realize are being able to really use advanced methods of leveraging and visualizing your data, having that holistic view of what's happening when you start crossing the tools and platforms and then having that robust visualization library that you have access to.
So let's talk data delivery. This refers to exactly that, the data that is delivered throughout your organization. In that initiated phase, you likely have ad hoc reports in place, but nothing regular or scheduled. When you get to an emerging level, you likely have more reports in place, but they're not going to be tailored to audience needs. Sort of a one size fits all. Executive reporting really comes into mind here. Executives need very succinct reports and you know, they typically want something that they can look at over coffee quickly and, and not have to invest too much time in it. It's one of the things that my clients typically, it'll be one of the first things they ask that we put in place. And then emerging, you know, phase, this is gonna start being in place, but not necessarily routinely scheduled. When you get to that advanced capacity, executive reporting will be in place along with other regular reports that are geared to specific audiences.
Your analytics practitioners are gonna likely need quite a bit more detail. Recurring reports will be in place. It should be quickly and easily accessed by different users. Such as, you know, maybe mobile-friendly reports, the reports that are sent via email that don't require logins and passwords. and then of course dashboards that are based in, in the tool. So how do we know where we're at along the maturity curve for data delivery? Consider if, you know, if you have well-defined reporting on audiences and a clear understanding of what their needs are and the questions that they're trying to answer. Do you know how they plan on consuming the data? Do you know if they're going to look at it on a tablet, on a phone, via email? Do you know if they want to see something weekly, quarterly, monthly?
What's that frequency of schedule that they're looking for? Then also consider if there are dashboards that are in place and reporting templates. This will help you keep integrity for your brands with your reports, but also allow your analysts to spend less time building reports and more time analyzing data. We want to make sure that we're focused on working smarter. So steps we can take so that we can move ourselves along this maturity curve. Start by creating and scheduling recurring reports and dashboards that are sent throughout your org. If those aren't in place, start by scheduling those and then develop that executive high-level dashboard as you know, your first step. If you're moving, if you're in an in an emerging capacity and you're moving to advance, start defining those report data points and the key questions that you want to have answered so that the reports are really starting to be anchored to those tangible questions people are asking.
Develop easily updated templates. Have those in place so that there is that library that people can ask that. And then start to innovate. How are you delivering these? Maybe it is something that you look at building a spark page, something new and different. Maybe it's driving things forward with Tableau. When you're in that advanced capacity, you know you're going to work on continuing to refine this as needs evolve and change. I really encourage people to look at updating and automating as much as you can. Again, you want your practitioners working on analyzing data and not actually building reports. And then you also want to make sure that you continue to provide data in the most easily extractable manner. So that you don't have people who are locked out and can't see things because they didn't have a password, a login, things like that. Benefits that you're going to realize. So the right reports created with the right tools available to the right audience.
I think that's the best way to put this. We've all been in a position where you know, you've got a C-level executive requesting data that they needed five minutes to go. If you have a good data delivery program in place, you're going to be able to answer those needs quickly and easily and it's going to be something that looks great, you know, that does have that brand integrity. from an accountability standpoint, there always should be someone in your org that you have established that says, "Here's the way we deliver our reports. Here's the way we create them, here's what they look like, here's the formats and so on."
Let's talk about enablement and communication. So when I'm thinking about enablement and communication, this refers to both how we're sharing within our organization the analytics tools and data that's available to everyone or communicating, "Hey, you guys, we have all this available," and we're enabling people to use it with an the necessary skills that they need. When you're in that initiated phase, your analytics team will know what the tools are, but they're not necessarily going to be circulated broadly throughout the org. When you get to that emerging, you're going to layer in that kind of reactive training, but not on a regular basis. This is where I see the most of my clients. They look at learning to use the tools in a very reactive way. It gets deprioritized for urgent needs. I as, you know, a champion of analytics do see learning and enabling people on these as urgent, but it's not the same as you know, when you know there's a wound that's bleeding.
This is, you know, more of a slow build and you know, as it gets deprioritized, it becomes more and more urgent. So making sure that it is, is prioritized to be a proactive area is really important. When we get to that advanced capacity, your org is going to be prioritizing that. It's going to be part of the culture to be enabling and training users on analytics and the tools. Investing that time up front and on a recurring training program I think often saves time in the end, but it does require that planning. From an accountability standpoint, again, as we're layering in accountability across each of these, you need to have an owner that will, that will make sure that there are regular enablement touch points throughout your organization. Somebody who is responsible for setting up that curriculum and continuing to make sure it's available for users.
So how do we know where we are on the enablement communication maturity curve? Is everyone aware of the analytics tools that are available to them and what they can do? Are users trained in the tools? Are there opportunities to increase tool knowledge and really start driving this practice forward? Our analytics wins share throughout the organization and you know, that's really a way to communicate and get buy in so that your stakeholders, your executives", your steering committee is going to say, Hey, we're seeing the value analytics. We made this investment. We understand how it can pay off." The benefit of a good enablement program is really going to be that efficiency and ability to keep driving things forward. So let's talk about steps can take, how do we start moving your organization forward? So your enablement and communication is initiated, just start with sharing wins, illustrated with data.
That's a great place to start. Showing like, "Hey, this is what our organization did." And tying it very clearly back to data. I think data happens to illustrate wins, everywhere around us. But are we really pointing out the role that data plays in there? That's what you can start doing in an initiated phase for aiding reports that are going to highlight analytics. They're tied to and they clearly highlight analytics. And then have a library of those training resources. So, hey, maybe there's not a curriculum with classes in place, but at least people know where to go so they can start looking at things. I'll often direct my clients to start taking a look at YouTube videos. And at Adobe we've created a lot of bite-sized video. They're meant to be able to be watched without a big drain on your calendar and you can start, you know, putting new skills to use right away.
If your organization is emerging, taking it to the next level could be as simple as creating that baseline training and enablement program for users. You know, starting with, here you're new to the tool, here are the steps, the classes, the training that we want you to go through. And then developing a data and analytics newsletter and communication plan. Start sharing on a regular basis. If that means broadly with the organization across the board, here's how we are performing and in these areas and using data to illustrate that. It's going to start communicating to people, "Hey, did you know we have these analytics tools available? Here they are. Would you like to learn how to use them?" and create that interest. In an advanced capacity, training for power users I think is really important. And I always want to encourage my clients to start having that differentiation point where you've got power users that really know how to to drive your tools in an advanced way. I think offering kind of a win for people who have taken their skills forward with, you know, the ability to attend boot camps and industry events is a really great way to keep advancing your practice. That's where a lot of new cutting edge things happen. And you know, even you know, some, it's like this where we're able to talk about what's happening in this area, that can be a great way to advance analytics users. And then I think scheduling regular office hours. Within my team at Adobe, office hours were scheduled, but people weren't attending. We had to find the right lever and make it something that people wanted to join into. And the host of it turned it into a show-and-tell and found people to get together and show something, something interesting that's happened, something new that was created and it's really led to a lot of conversation.
You know, it's really getting people to think creatively about what we can do next. So again, the benefits: access to the tool, people are going to be able to access the tools they need to answer the questions that are out there. And then promotion of that team through the communication and celebration of success, getting people to realize the value of your analytics practice within your organization, the value that's provided with data. That's all going to become a benefit and the value of a good enablement and communication program. So yeah, as we talk about value realization, we'll segue into this as an area specifically.
So value realization is so important because this is the way that you say, "Hey, look at the investment that we've made and what we've been able to do with it. Look at how it's paying off." And that initiated phase, when clients are in this area, it's usually pretty difficult to really tie that back, to really drive that value forward. You know, when we get to you know, the end of the year and people are looking at budget and deciding where we're going to cut, where are we going to invest more? Having a good value realization program in place makes that easier. But I think everyone has been in the position of where they go, "Huh, okay. I know this is valuable, but how do I show that?" That's what value realization means. You're going to tie back the data points to KPIs and really drive that value forward.
If your organization is in an emerging capacity, you're starting to do this. Data occasionally traces back to the company KPIs, the key initiatives that are in place. But only limited value realization is going to happen. High-level KPIs, again, those will probably be known, but it's still going to be kind of that reactive, this is what happened reporting. When you get to that advanced level, reporting is really going to be focused and tied to specific KPIs. Reporting becomes proactive. It speaks to the kids, the businesses, key initiatives and naturally leads into those optimization opportunities. So where is your organization on the value realization maturity curve? Consider if you can name your KPIs and if others in your organization no, what they are. That's a really good place to start. Think about how often you're putting reports together. Are they tied to KPIs or are they kind of just an inventory of here's the data points I had available? You know, I'm reporting on visits, page views, unique visitors. Are there key marketing strategies that are really illustrated when you're putting reports together?
To start moving along this curve, some steps that you can take: from the initiated phase, start communicating with all data and analytics team members what the org's key business initiatives and KPIs are. Make sure they know what they are. Include key data points as the foundation of reports. Make sure that it isn't any longer page views, visits, time on site. Things that create questions and draw confusion. Make sure that they are tied to what is a KPI for us. When you get to that emerging level, you can take things to advanced by you know, creating reports that really show a win and highlight those data points. That's going to help drive the value for it to the organization as well. We know what we're doing well, we know what we need to work on because we're able to realize that value with data. Established reports at regular interval: that might mean that you want to set monthly reporting, you want to set quarterly reporting, you want to have those business checks in place and then build value-based reporting into marketing campaign plans.
When a new plan and strategy is put in place, right away in the beginning say, "Okay, right, we need to know what the KPIs are and we need to make sure that we're establishing from the start, what are we going to report on, what do we consider to be success? How often are we going to report on it?" A culture that is data-driven, is going to have data embedded into marketing campaigns. In that advanced capacity, you want to just kind of continue to embed that KPI-based reporting into those marketing initiatives, make sure that doesn't fall away and continue to illustrate the value, especially to executives with that routine and campaign reporting. You know, make sure that you've gotten buy-in from the top data used throughout your organization.
So the benefits: you have data, people know what the wins are, they know what the key performance indicators are and you're able to optimize your digital marketing with that data. You can clearly identify wins, they're attributed to key actions. Value is easily communicated to executives on a regular basis. And so on. So let's talk how about user administration. Most clients that I work with are in an initiated position on the maturity curve. Basically it's ad hoc. Somebody requests access, they're given access. And that's really the extent of it. In an emerging capacity, your org may have realized the need to tighten down access to your data and needing to up-level permissions the different team members have. Loosely defined plans will probably be in play, but they might not always be followed. When you reach that advanced capacity, there's usually a well-defined process that assigns permissions and access to data across the organization and it's regularly siloed. So this is really important, especially for clients that have security teams involved, brand access guidelines that they need to have in place or they have concerns with reports and user skills after, you know, a few bumps in the road with data being looked at differently.
How do you know where your user administration is on the maturity curve? So consider, do you know who has access to your tools and how often they're using them? Do you know what their different roles are, do you have different roles or is everybody granted the same permission across the board? Is there a process in place, not only for granting those new users, but also for revoking access if necessary or changing permission level? And how often is that reviewed? How often do users have to create a new password or share their certification on a certain scale?
Depending on where you're at, there's a few simple steps that you can put in place. Simply starting with developing a plan for granting user access. Who is it requested from and what is the process? Did they fill out a form? Did they send an email? H]ow do you add new users? And then define those user permission levels. Even if it starts with just a user and administrator level. Once you reach that emerging point continue to finesse those roles based on what the organization's needs are. It likely will evolve. Create a schedule for auditing your users if it happens once every six months, quarterly, monthly, whatever those needs are. And make sure that there's well-defined guidelines for updating. And accessing passwords. Once you're in that advanced level, you really just want to make sure you continue to ensure user access is audited. That's really the most important thing. And that you work with the business, technical, and security teams to refine your process for user administration.
The benefits: you know who has access to your data and what their permissions are. Clearly defined admin roles are in play. You've got a process for managing users and essentially, you know, who has access, you can remove access, you can grant access. You just have a clear picture of, of who can get to your data and what they can do with it. Well, let's talk about building a data democratization roadmap. What do you do to start moving your organization forward? Start by reviewing where your org is for each of those areas and establish their priorities. And that means reaching out to people in your organization and asking them, "Hey, do you think we're initiated? What kind of score would you give us?" What areas are the most critical for your organization? Is security most critical or do you really need to work on getting your reporting in better shape?
And then consider what areas could see the most impact with the least amount of effort. That's always a good way to understand what can we do. And then use those two levers to build a short-term, near-term, long-term strategy that moves your org along the maturity scale. Short-term, near-term, long-term in my opinion, I think having a plan for the next 6 months, the next 12 months, and the next 18 months and where you want to go makes sense. Define tasks that are going to increase your maturity in each area and establish that accountability. And those tests could be as simple as, you know, the examples that I have in this presentation. And then at the end of the short-term phase, the near-term, the long-term, go back to those people that you talk to and ask them "Where do you think we're at? Let's review where we're at on the maturity curve." And then continue to communicate progress with key stakeholders and your executive sponsors so you can keep having that buy in. So, democratization key takeaways in a nutshell: use the right visualization tool, work with leveraging automated dashboards and templates, specific audiences, make sure that people have access when they need access. Tie successes back to those documented KPIs that really shows the value of the data. You can show where your wins are. Have that user creation and management plan in place so that you can keep a handle on who has access to your data and what their access is. And accountability. That's key. And that runs through each level of data democratization as you're working to build a data driven culture. Thank you very much. This is data democratization in a nutshell.