Hi Everyone, thank you for joining me today. My name is Erin Haselkorn and I am a self-proclaimed data quality evangelist here at Experian Data Quality.
We are here today to talk about a rising trend, the chief data officer, and how it is going to affect marketers. The title of the presentation, A marketer’s new best friend: the chief data officer, is meant to show marketers that they have nothing to fear from this emerging c-suite position. Rather, if your company has a CDO or is thinking about one, this could really help you out in terms of getting better access and insight from your data assets.
The goal of today’s presentation is to cover off:
The challenge marketers face today with their data
What is a CDO and how are they starting to change some common issues around information access and quality
How the CDO differs from the CIO
Tips on how you can work with the CDO in your organization
And Finally, if you don’t have a CDOs, steps you can take to improve your data now
Erin:
Let’s start with the data landscape and the challenges marketers face.
I have pulled some data throughout this presentation from two primary reports. One was a global research study we conducted this past winter where we surveyed 1,400 people globally across a number of verticals and it included marketers, it professionals, finance folks, really anyone who had ties and an understanding of data practices.
The second study was of 200 CIOs around their pressures around data and the rise of the CDO.
As we know, marketers are using data today more than ever before. But what are they trying to use it for?
Insight.
Data strategies are ultimately put into place to turn data into actionable insight.
Not surprisingly, the biggest drivers for better data practices are very customer-focused. Respondents from the global study named finding new customers, retaining customers, understanding customer needs, and increasing the value of each customer as important reasons to leverage data.
These certainly hit home for marketers
Outside of these drivers, however, the need for better data analytics and management lie in very business-oriented factors. Increasing business growth, securing future budgets, reducing risk, and complying with government regulations are among the business-oriented factors compelling organizations to focus more on better data management.
An evolution in data usage is taking place in all businesses, no matter the size or vertical.
Data is essential to decision-making around customer sales, organizational effectiveness, and ultimately, a business’s overall strategy. Eighty-four percent of businesses believe data to be an integral part of forming a business strategy.
The increase in data usage is due to the belief that the key to consumers’ hearts—and subsequently the key to increased sales—is accomplished by providing an exceptional customer experience. The mantra of ‘customer first’ will only continue to grow in relevance.
Now in many instances, the marketers are the key to that initial customer experience when we look at digital channels
Data can be very powerful in helping provide that tailored experience. However, it can also hurt the experience when we get it wrong.
75 percent of organizations believe inaccurate data to be undermining their ability to provide an excellent customer experience.
Now, my guess is, most of us are not achieving the level of insight that we need from data. In fact, many of us are probably undermining our customer experience with inaccurate data
That is because data is largely an untapped resource.
Now the CIOs we spoke with do think data is changing the way they do business. I don’t think that would surprise any data-driven marketer in here.
However, data isn’t always reliable, accessible or trustworthy. Because of that, there is a lot of room for improvement around data usage.
The CIOs we surveyed in our study realize there is significant room for improvement and you can see it in some of the stats on the screen.
Four out of five (83%) see data as a valuable asset that is not being fully utilized within their organization.
Three in five (64%) believe their organization is not making optimal use of data to drive their business forward.
Lastly, this data isn’t free. 76% say they have underutilized data that is costing the business money to store.
While we may collect a lot of data for consumers and it could be useful, it isn’t just free to do so, especially when we think about the volumes of data we have today.
There are many challenges around using data and why it remains an untapped resource.
First, there are a lot of issues around company culture that create problems when it comes to utilizing data. The main challenge is that there is a lack of ownership around data. Everyone wants to use it, but no one wants to take responsibility for it.
The majority of CIOs we talked to face barriers in this respect, with 68 percent struggling to find stakeholders who take anything other than a siloed view of data management. Organizations without a CDO have an ambition to capitalize on data, but CIOs struggle to implement data-driven decision making because no one seems to own the process. This is true for a notable 70 percent of respondents.
More on that a little later and how CDOs are trying to combat this issue.
But this lack of data ownership is also leading to inaccuracies in the information.
There are a lot of inaccuracies in information, but when we asked the global respondents what were the top errors, this is what we got
I am sure many people in the room can identify these. There is a lot of incomplete or missing data fields, information becomes outdated as well.
In fact, at one point I saw a statistic that contact data decays about 2% each month with people moving, changing jobs, etc.
A lot of businesses also have problems with duplicate data, this can be in a single system or across the organization.
And these errors are blamed many times on human error. Someone, be it an employee or a customer, putting in information inaccurately.
Most of the time this isn’t on purpose, they just fat finger the information or leave it off because they don’t want to provide it.
But all of this inaccurate data does cause challenges.
You can see from the chart that organizations are seeing difficulty in using data for strategic decision-making, regulatory risk, damage to the customer experience and much more, all as a result of inaccurate data.
In today’s market, it’s essential that companies get data right. Far beyond a mere compliance issue, data accuracy can boost profitability. The majority of organizations believe they could increase profits by an incredible 17 percent if their data were of the highest quality.
This shows how widely we want to use data and how when it is wrong, it now affects core business processes.
Luckily, the chief data officer is coming to the rescue.
First, to level set, let’s put up a definition for a chief data officer.
They are a corporate officer responsible for enterprise-wide governance and utilization of information as an asset, via data processing, analysis, data mining, information trading, and other means.
There are clear mandates for the CDO.
Nearly three-quarters of CIOS (70%) consider the CDO to be a ‘trusted advisor’ on data across the enterprise. A further 64 percent view them as a ‘guardian of data quality’. CDOs are also responsible for driving large data-management programs involving multiple stakeholders, according to 59 percent of respondents.
CDOs are becoming more popular across businesses
Gartner estimates that by 2017, half of all companies in regulated industries will have a chief data officer. This role is becoming far more prevalent and affecting a wide range of industries and how they leverage data.
From our own data, we can see that 63 percent of organizations without a CDO would like to see one created. And amongst those who want a CDO, they think this will happen, on average, within the next 18 months.
Now, interestingly, the UK is ahead of the US, expecting a CDO on average within 12 months. This showcases how the more regulated climate in Europe is driving faster adoption of the role in that region.
It’s much easier to justify such a role for regulatory purposes to cover your behind than to research leveraging data in new exciting, transformative ways. It will be very interesting to see how well CDOs can pivot from that initial defensive stance to a more offensive one.
Lastly for the CDOs that are already in place, most are relatively new. A whopping 78% have created the role within the last 6 months.
That’s really exciting. We really are at the dawn of this role becoming more mainstream and making a strong impact on a wide breadth of organizations and industries.
It’s going to take a bit for these folks to get a handle on how best to tackle the organizational issues and find the right balance between small changes and bigger strategic impact. The CDO’s ability to succeed with the help of their peers, and the software and consultant industries, will be key for the role to gain a strong foothold across industry and persist in the future.
Today this role tends to report into the CIO according to the individuals that we surveyed. Now granted we asked a lot of CIOs, so there could be some bias. However, it did line up with the information we saw from the CDOs we talked to anecdotally as well.
CDOs I’ve spoken with believe that they should report directly to the CEO alongside the CIO as an executive peer. They describe the CIO’s role as managing technology, applications, and infrastructure, while they describe their own as responsible for ensuring trustworthiness and availability of the data itself, often housed inside those applications and infrastructure. The two will certainly work hand in hand on key tools and technology, but the CDO must also spend considerable time outside the world of technology on the culture challenges we mentioned before, as well as processes to make sure everything runs well.
The Chief Data Officer can cover areas of data and data management that the CIO may not previously have had time to manage. The CDO role adds value to the CIO. We saw that 86% of those with a CDO role in their organization thought it added value to their data management strategy.
The main reasons for wanting a CDO can be seen on the graph. There is a desire for a consistent approach around de-risking data driven projects, they want the CDO to curb increasing costs due to poor data quality and finally, you see a desire for the CDO to help with data around governance and regulation.
CDOs are especially common in highly regulated industries, like finance and healthcare, so this is really not surprising.
Well when we talked to CDOs, we found that changing the organization’s culture was both the greatest obstacles and also the most important.
The research suggests the creation of a CDO role in businesses would help reduce barriers to data utilization, raise the profile of data among stakeholders, and prevent data silos.
One CDO we spoke with discussed the importance of focusing on culture rather than trying to force processes, rules, and tools that hinder employees’ daily routine. He called this approach the “data police” and explained employees will do anything they can to find shortcuts around the processes. Forcing people to “do data governance” for data governance’s sake isn’t a compelling enough reason for them to comply with new rules and standards and change the way they think about and handle data day to day.
CDOs and data stakeholders are really challenged by driving visionary, transformative change in the way data is leveraged in their business, in order to provide the value expected from the role
Given all of that information, it is clear that the CMO can benefit greatly from the CDO.
Marketers already have a lot of their plate and while data is essential to what we do, we don’t always have the resources or expertise to wrangle data and then gain the analytics from it
Let’s be honest, what all of us want is for the data to arrive clean, accurate, and ready for us to manipulate to better understand the consumer.
There are clear benefits that a person focused on evangelizing data across the business can have for the CMO
First, they can help create a better understanding of the consumer than we have today and also help get other people across the business to come together around this purpose. The tricky thing with marketers and data is that while we do have some minor control over the collection of some data and the third party sources we use to enhance information, there is very little control we have over large portions of first party information across the business.
This new resource of the CDO can help gain control and governance over some of that information.
They can also compile data across sources. It might be a data lake, but to be honest, data across businesses is living in so many different places today. One thing we are starting to hear talked about are systems that will manipulate and control data where it lives. In addition, it can access information for certain analytical purposes without it having to be combined in one single source. That is because the volumes are getting so big it is hard to scale.
The CDO can better help navigate some of those changes.
In addition, their job is data. They can help recommend third-party sources for you to use, but also help you realize what you have across the business already and then what you really need to by.
Next they can help save you money. We all have costs related to poor data quality. That can come from poor contact data, but also missed opportunities and a poor customer experience.
They are going to better help you access data as a service, being able to pull information from across the business for certain analytics exercises.
And then finally, they are going to help centralize data management and data governance policies to help improve the trust around information.
Marketers can benefit greatly from a CDO, but we do have a few tips for improving that working relationship.
When it comes to working with a CDO, it’s crucial to remember their motivations and goals. As self-proclaimed “data guardians,” they see themselves as upholding the integrity of the organization’s data. So it’s important to show that you’re on the same page when it comes to the need for data quality and its implications on business-wide initiatives.
The best way to do this is to become the data evangelist on your marketing team, spreading the word and building support for data quality within your department. Once support is garnered, you can begin encouraging collaboration between departments to ensure marketing is getting the most out of your data resources.
The CDO is trying to implement systemic change to the way employees use their data, which will require substantive cultural changes. To do this, it is essential that the CDO is brought fully into the C-suite so they can become integrated with your corporate culture. Encourage this, and treat the CDO as an executive peer within your organization. This will empower them to begin changing the existing principles around data use and quality practices.
However, we certainly realize that not everyone has a CDO and there are some marketers that need to work to improve the quality of their data now. To help with this, we put together 4 simple tips to help you better manage data and improve the quality.
The first step is to assess the quality of your data in the first place.
Where does the information that you use live, what is the quality of it, what steps are in place to ensure information is accurate as it is captured and maintained over time.
Taking stock of your information is the first step. This may require more technical expertise, but you can also tell some now based on the quality of your marketing efforts. Things like bounce backs and returned mail can give a simple overview of the data.
Once you identify what is wrong, you can prioritize your clean-up based on what is most important.
The concept that data is going to be 100% accurate all the time is just not true. However, the data does need to be good enough for what you are trying to accomplish. You don’t have time to maintain data at 100% accuracy, but you can prioritize your most important assets and make sure they are accurate.
By assessing the accuracy of your data you can start taking proactive steps to remediate the root causes.
Going right along with this, you need to understand the value of given data assets.
This takes a bit of assessment and sitting down with your team
For now to demonstrate how to do this, I am just going to pull out basic contact data and some demographic information in terms of what is captured for a loyalty program.
So first, it is important to know what you need. For this particular loyalty program and the actions we want to take, we need the items on the first line: name, postal address to send fliers, email address for events and coupons and then finally date of birth for special birthday offers
Then look at what is being captured. In this instance, we are capturing name, address and email, but we are also capturing mobile phone and gender. However, we are not taking in the date of birth.
Now that we have this information, score each data set in terms of importance. How much does it matter to have this information correct.
So name is very important, postal is important because we not only send information to it, but we use it to help us append information from Experian so we will keep that. Then email is the most popular form of communication so it is very important that we have an email.
Then we start to get different scores. Mobile phone is being captured and while we don’t use it today, it might be good to have on file for SMS messages and other communication. So we will rate it as a 5.
Date of birth is very important, but we aren’t capturing that today. Clearly that means we need to change our process and start capturing that information
Finally gender, we don’t really need it for what we do, it isn’t helping, so why are we wasting the client’s time asking for it.
Now this is a very basic example, but understanding the value of your data assets allows you to make sure one that you are capturing everything that you want, but two you can prioritize what to clean and what assets are most important for you to have accurate and on file at all times.
This goes into my next section, fix the data that matters
You need to fix the information that matters most to your business and marketing team. Only you and your team can answer that question.
However, contact data historically has problems and duplicates are an issue from the research we have done and the clients we talk to.
Accurate customer information is critical to the success of your marketing campaigns, so staying on top of the quality of your contact information is essential. For existing data, you should look for a contact validation tool that can verify email, phone numbers, and mailing addresses. Email validation will ensure that you are sending to deliverable addresses, reducing your bounce rate and protecting the ever-important sender reputation. Phone validation can help you to identify the correct numbers for customers, while also identifying mobile numbers vs. landline for TCPA compliance. Mailing address validation can reduce costs related to returned mail and time spent on rework. Validating your existing customer data will make a big difference in the efficiency of your marketing campaigns.
You should also use a profiling tool to identify duplicate customer information or outliers in your database. Duplicate customer records can prevent you from achieving a single customer view, and making it difficult to provide a tailored experience to that customer. Outliers in your database could represent misplaced information or incorrectly formatted entries (such as a birth year with only the last two digits).
Finally, take a holistic approach.
Whenever you look to make changes to your data quality program, it’s absolutely crucial that you consider all aspects of the business that touch your data. Approach your initiatives in a consistent, enterprise-wide way. This includes identifying the people, processes, and technology you’ll need to implement a successful data program. All three of these components will need to be addressed as part of an overall data quality initiative.
Your people will need to be trained on data quality best practices and governance requirements that are specific to your organization. You’ll also want to establish a culture of data quality, so good data quality practices become habitual rather than a requirement.
Your processes will need to be updated to account for your new data quality practices. For example, if you’re asking data creators to follow certain standards, then the processes by which they do that should be clearly defined and intuitive.
Your technology will also need to be upgraded to account for your data quality practices. This doesn’t necessarily mean overhauling your existing hardware, though. By investing in the right data quality tools, you can get on your way to assessing your data quality and remediating issues.
