I interviewed Claire McEachern who discussed Data Quality As Part of Any Organization's Supply Chain?
Can you first provide a brief background of yourself?
Sure. Thanks, Dustin. Hello, everyone.Claire McEachern here. I currently work for a sales technology company. DiscoverOrg specializes in sales intelligence. My role here, I cover everything from websites building to SEO to SEM and blogging, PR, social media, content creation. We're also, really, as an organization, and as the marketing department, really focused on lead generation and sales intelligence and big data and data accuracy as part of our core product offering. And also, just as we are a high growth organization, so it's something that we're really very focused on.
Previously, before working at DiscoverOrg, I worked for several years in marketing ecommerce, visual marketing. I did a lot of SEO and SEM before that and within those fields, and where I was working before was primarily in the sustainability realm. So, the products that the companies I worked for produced were in the up cycled space. So, returning what someone else consider to be trash — whether it's just a scrap of leather or it's an unused packaging material, and making that into something that has an even greater value. And prior to that, I worked for a proprietary software company that was focused on employment screening and help solutions. And somewhere during that time, I got my graduate degree in sustainable design and previously, I had an undergraduate degree in sociology.
I have found myself in marketing and working for tech and big data.
Can you explain data quality and why is it part of any organization's supply chain?
I think data quality, no matter what your position is and what your industry is, is absolutely important in ensuring that your business is able to grow, you're able to build strong relationships with your customers and your internal teammates. And that any time that you have good data quality, you're really providing better intelligence to your internal organization so that you guys can grow as well as any of your customers.
In DiscoverOrg, we look at data quality and sales intelligence. So, our particular product is a sales intelligence tool that focuses on the contact data, the direct dials, emails, to a 95% accuracy. And one of the things that is really core to our product, we also turn that information, and we map the org charts of organizations with the intent that sales marketing and staffing professionals are able to look at this data and create better relationships. They know who the decision makers are. They know who to contact. They know what their pain points are to be able to sell them, or really to find a best fit for their product or service and then be able to really help their customers, their future customers, find a solution that helps their day-to-day do better, whether that's cloud computing or security or social media tools, or whatever it is.
One of the big things for DiscoverOrg is that we are really proud of our data quality. And so, one of the things within our industry, in sales intelligence, a lot of our competitors will use crowd scraping. They'll use algorithms to go on LinkedIn or to look at company pages of teams to figure out an email, usually a first-name.last-name@whatever the domain is. But what this does in this non-human verified way of just crowd and computer and cloud scraping of information is that it doesn't actually provide a lot of accuracy. So, without having someone look at the data and really say, "Okay, this makes sense. This isn't just a computer found a pattern and said, 'This is what it is,'" we actually have an in-house team of researchers, about 150 to 200 people that will verify data every 90 days. And so they keep on top of it, so it's not we looked at it five years ago. It was accurate then. But, really, every 90 days.
What this does for our clients is it gives them the peace of mind that when they go in to do their jobs day to day, they're not ending up with a lot of wrong data that's sending them down the wrong path, that they're wasting time. And so, I think, in any business...that's DiscoverOrg's business. But if we look at manufacturing and supply chain, if a manufacturer gets an incorrect material data safety sheet, for example, and that's not correct, it's not filled in, think about how much time that's going to waste for that person's day of having to track it down and connect the dots, cross the T's, make sure that everything is right. If they're not able to trust the data that they're provided by their peers and their teammates, then it can really make the whole house cards tumble, so the speak.
I think for every business, whatever you're doing, data quality and accuracy of data is really, really important.
Can you talk about some success stories you may have with setting up analytic systems for gaining insights? And if you have anything related to supply chain, that would also be interesting.
Some of the analytics...I'm sure everyone these days has heard of big data and predictive analytics. One of the things that our company does, which I think is a really exciting product, it's called OppAlerts. And what it does is it's basically a tool that the end result is to provide people who are looking for opportunities with potential customers of seeing, for example, is IBM, for some reason, looking to switch security partners? So, we've... And we have proprietary algorithms on this. But we are able to look at the content consumption of particular companies. lLt's say IBM all of a sudden, people from that domain start going out and they start looking at a lot of articles and blogs and going to a lot of websites that has to do with cloud security. We take that information, and then, along with our human verification process, it looks like there's a pattern happening here. Let's verify it. Let's see if this is, in fact, true, that they're starting to look at cloud security solutions.
Then if that is true, then we have a product that will then notify our customer who are in cloud security that, hey, IBM happens to be consuming a lot of this content. It looks like there is an opportunity to sell and pitch them on a product that meets these kind of needs. So, that's just an example of how we're using analytics and predictive technology to combine the accuracy in supply chain to, again, make it a much more efficient process for people in sales, marketing, and staffing to have better intelligence, build stronger relationships, and drive faster growth in their own businesses.
Thanks, Claire, for sharing today. Do you have any final recommendations?
I think one of the recommendations, whether you're looking for a data provider or you're looking for a manufacturer, or you're looking for a distributor, is to definitely go out and test whatever their product is. Don't into rely on word of mouth. Make sure that you're able to look at what their data actually is. Make sure that it's accurate. Make sure it is all that they are telling you it is up front, before you go ahead and sign a deal and bring on a new technology or a new process, because I'm sure everyone out there has had some point in their life where they've brought on a new technology or a new vendor or a new whatever it is and maybe they didn't test enough in the beginning, and then they get burned by it three months down. So, think through how much time that is going to waste in your own efficiency and your own processes. So, definitely test, definitely challenge the data. And if anyone is worth their salt, whether, again, it's data, manufacturer, distributor, whatever it is, they'll be able to meet the challenges that you're throwing out there. So, good luck in finding good data.
And thanks for sharing today.
About Claire McEachern
Director, Communications & Creative at DiscoverOrg