You are listening to QA talks, a podcast for quality assurance executives implementing digital transformation in their organizations. In this show, we focus on the unique pitfalls inherent in quality assurance and quality engineering and how these executives are navigating them to position their organization for the future. Let’s get into the show.  

Logan: Welcome back to QATalks where we’re talking quality assurance, quality engineering, digital transformation, and other topics that are pertinent to IT leaders today. My name is Logan Lyles. I’m the host for today’s episode. Today, I’m joined by Brian Benn of the Atlanta Housing Authority and Cigniti speaker. Gentlemen welcome to the show. How are you today?  

Brian: Doing well, thanks.  

Cigniti speaker: Thank you so much Logan for having us. Thank you Brian for your time. 

Brian: My pleasure! 

Logan: Absolutely, Gentlemen! A little bit of background on each of our speakers today before we jump in. As we mentioned, Brian Benn is the Chief Information Officer and Senior Vice President at the Atlanta Housing Authority. Brian is a technology evangelist and has a passion for bridging the digital divide. In his current role, Brian’s responsible for the development and implementation of technology strategies for the Atlanta Housing Authority. He also volunteers as an executive ambassador for TechBridge and serves on the advisory boards for multiple industry organizations. Gentlemen, obviously a lot of experience between the two of you, so I am really excited to dive in.  

Brian, as we talked a little bit about your current role, I would love to hear some of the recent things that have been going on for you and your organization, some of the key changes that you’ve introduced over at the Atlanta Housing Authority to accelerate digital transformation that seems to always be a consistent theme of this show. Would love to hear, you know, in the recent weeks and months and so far in 2020, how has that played out for your organization recently?  

Brian: Well, a couple of things; when we speak about digital transformation, of course, that differ, that so broad a term and it differs from shop to shop. But I think one thing that resonates, no matter where you’re doing it, no matter what it means for your organization is it’s going to be based on data. I mean, you can’t digitally transform until you have data. So one of the things we’ve introduced here is an enterprise information management strategy and plan, meaning that we want to first corral all the data. We want to reduce the disparate systems. We want to come down to one central source of truth and ensure the accuracy and accessibility of our data so that we can drive decisions down, so we can provide dashboards, and from the highest level to the lowest level in our team, we just want to foster those data-driven decisions. So before we can even talk about digital transformation, which to me is just a symbiotic relationship between people, processes, and technology, one of the big things that we introduced was that EIM strategy and implementation plan. 

Logan: Yeah, I love the way you say that corral the data. It seems like we’re just swimming in data and we need to get it under control so that we can actually get value from it. And I like what you talked about there, Brian, in finding a single source of truth. And normally that means reducing the number of systems in the number of places that data is housed and accessed. Are there some common things where you see organizations run into a brick wall in trying to eliminate systems and consolidate that in some ways that your team has found ways around that? 

Brian: Yeah, well, first we have to identify them. We have to understand what is a data source or what is a database. And so if somebody has a way of working out of an access file, if somebody is over there using an Excel spreadsheet, as these things begin to grow, we have to understand that these are databases, too. I mean, you can have John, you can have something over there behind the woodpile. But if he’s using that as source of data and that’s what he’s providing where we need those reports, whether it’s to her or whether the executive then that, in essence, becomes a database as well. So whether you’re dealing with Oracle SQL, I just think we have to identify of all those disparate sources and the different ones we’re going to use, a sort of a different role that he shops. Just and again, going back to the corralling it before we can even start talking about normalizing it and using it before, whether we’re talking about transactional data or historical data, I think we still have to have that central repository. Now, you’re going to have some offshoots where you are going to need a different database, but we still want that single source of truth, that one central repository that we can build from and grow from there. So I think that’s what we’ve done and where we’ve done a good job is identify those sources, understanding that we’re trying to help, but also understanding we’ve got to corral that. 

Logan: Yeah, maybe not always make those team members feel like the rogue, but just say, hey, we’re trying to be able to make it easier for us all to work with this data together. I like what you said there–  It’s not always your defined databases that are the data sources. It could be that access file, it could be that Excel file something behind the woodshop. I love the way you put that there Brain, such a good visual. Cigniti speaker, you know, as we talk about digital transformation, it’s always this balance of strategy, you know, which is not only the end result but strategy in how you communicated, as Brian was talking about there, is you communicate internally to team members as you try to corral the different data sources. It’s a balance between that strategy and the technology. Where do you see organizations getting this right today as they balance those two in their digital transformation efforts? 

Cigniti speaker: Absolutely. Today, as the COVID situation arose, digital became the main transformation for every organization. So they want to know how they can provide the access to the system, both internal and external, in a digital way. I think that’s the key transformation that’s going on. What we thought the strategy is going to be a two year to three year transformation; today we are seeing that it’s going to get completed by end of this year itself. So a lot of companies buying digital tools today for smart work and for their own salesforce implementation, for their cloud strategies, for migrating their existing legacy transformation into digital transformation world through various factors offered. They’re implementing a lot of technologies like IoT and cloud. They are doing a lot of process automation around it and they want to collect all the data. Rightly said, data is the king today. So they want to see a good amount of data so that they can use the data for predictive analytics. How can they predict the future of their release? How can they predict the future of customer experience? So all these are now driven through this digital transformation. That’s what we are seeing in large organizations implementing it through various tools. And today, the biggest challenge, if you see is access to the skill set. So all of a sudden the digital transformation wave happened. More skilled workforces needed, more tools are needed to help with the transformation. And as you have seen, the cloud companies like Microsoft, Amazon, and Googles of the world, I’ve seen increasing their sales and all you can imagine, right. The number of cloud implementations are going in a big bang way. All these are factored in today’s world. As you mentioned, digital strategy and transformation is the top of the hour. 

Logan: Yeah, as you put it there, the future is really all about data, data is driving everything. And that’s what Brian touched on. First, before you talk about digital transformation, you’ve got to think about what is the data that’s going to drive that.  

Brian, I’d like to talk a little bit about a specific partnership that the Atlanta Housing Authority has recently developed with a local association there in Georgia to improve and employ data-driven processes and support decision making in real estate. Can you tell us a little bit about the background of that partnership and what Cigniti speaker is really talking about at a high level has played itself out in a real-world scenario here recently for the Atlanta Housing Authority? 

Brian: OK, so yeah, we’ve partnered with Georgia Tech and they bring the best and brightest in the industry. And what we’ve learned from the things we’ve done is they have a practicum program for their masters in science and analytics. So we’ve leveraged some of that experience combined with the excellent resources we have here at the Housing Authority and a part of their assignments or class work, a task, I guess, would be a more appropriate term, provides an economic impact analysis, whether we’re talking from payroll, to purchasing, or even real estate development that helps show some of the value that we bring to the city. They’ve also helped develop some key performance indicators (KPIs) and metrics to help understand the Atlanta housing market and then also help form a strategy, help us when we’re trying to collaborate more effectively with partners. So we’re just excited to be able to leverage that expertise along with what we bring to the table and just for the betterment of society and our operations as a whole.  

Logan: Yeah, I love it, Brian. Have there been some interesting things, things that surprised you guys about that partnership and the data that it opened up to you as you seek to add more value from the Atlanta housing authority’s perspective? Anything surprising as you started down the path of this new partnership? 

Brian: Well, not necessarily a surprise, but definitely things that we were happy about. We were happy about the level of expertise that the students brought. We were happy about the marriage in terms of the relationship and the relationship between the students and our staff and how well that worked. And just as we delve into the data, we would just, not necessarily surprised, but happy to start uncovering and just go deeper and deeper and just realizing the things that you don’t necessarily think as data that you can use to inform decisions all of a sudden when you have the access to it and you know the depth and breadth of it. You can actually start to use it to make those as opposed to those data-driven decisions. So not necessarily surprised, but definitely pleased to be able to be part of this relationship. 

Logan: So, yeah, we are maybe not surprised, but delighted. I like the way that you put that there, Brian. You know, you talked a little bit about how the Atlanta Housing Authority is not only looking at digital transformation for the sake of transforming and for the sake of change, but really the impact to the folks that you serve. And I think any IT organization that is really looking to have the maximum impact, it’s really about how do these strategies impact customer service and customer experience? And those might be internal customers as well as external customers. Are there some steps that you recommend to your peers in bridging that divide between those digital strategies and having an impact on the customer service or the customer experience on the front-facing side of the organization?  

Brian: Absolutely. Well, one of the things that this pandemic has definitely taught us is that customer service is king. It has not gone away. It’s not that it’s even more apropos now. And so towards that end and we’re talking to internal customers now that there in some 25 resources here at the housing authority that we serve, one of the things we want to do is we want to make sure we have the services catalog so we even understand what platforms do we offer, what platforms are we using, collaborative platforms that we use internally, externally, when we should use Zoom versus Microsoft teams, we don’t want to be duplicative. So we have the delineation in terms of our services catalog that we rolled out to the entire organization. The other thing is just from our practitioners, we need to be fully aware of our product and service. We should know what we’re offering, we should be able to speak about it, we should have SME or subject matter experts deal with our internal customers so that if they need help, they can respond. The other thing is we’ve got to have that positive can-do attitude. Just thinking the same terms when you go into the store, go into the mall or the kiosk and you’re buying something or you go and get your car service, you want a positive can-do attitude that helps you come back, that brings referrals, and then there’s responsiveness. So if you’re entering something in service now, whatever the ticketing system may be, sometimes you may need to automate and just say, hey, we’ve received a response and make sure those facilities are being met and we’re going to respond based on whatever the request is. We’re going to respond in the next two hours. So, again, depending on the severity of the request. And then, of course, the big thing is that follow up, after all that’s done after these steps are taken, you’ve shown the product and service awareness, you have that positive attitude, you’ve been responsive, you can point them to these services catalogs, you’ve got to follow up. There’s a touch there where you say, “hey, it’s you guys, we understand is your e-mail working now, we understand we just went through Microsoft 365 migration and some of your things weren’t cached. We just want to check in with you and make sure you’re operating on all cylinders now.” So I think all those little points and touches that are not dissimilar from what we do or what we expect from the people we take our cars to and we buy other products from. I think we should have that same mentality coupled with our technical expertise. 

Logan: I love that. Brian. I broke it down into three steps as I was taking notes from what you were saying. It’s letting your internal customers know, make sure they understand all of the services that you offer, pair a knowledgeable subject matter expert, which with each of those so that your customers, internal or external, know where to go when they find what they’re looking for, whether there’s a person attached to that, or at least an inbox where a team can respond and then the attitude that you deliver the services in. And then the crucial part is that follow up, that brings it back to the top  – “hey, here are some other resources you might be interested in, or hey, we know, let’s check in on what we just did, but then let’s also, you know, circle back to some other things that might be affecting you right now and how we can start that service loop over again.” The way that you described it is just very sequential there. 

Cigniti speaker, knowing that Cigniti works with a lot of government organizations like the city of Atlanta and Atlanta housing authority, government organizations similar to them, you’ve probably seen where certain organizations have been able to follow this customer service loop and serve customers with their technology well and some common missteps. What are some of the other keys in  this customer service arena where you see specifically, you know, government organizations are able to go above and beyond and provide a great customer experience for both internal and external customers? 

Cigniti speaker: Oh, yes. I think one great point Brian mentioned about I think is KPI, it is the key. We need to meet that in order for us to better serve the customer. So that’s one. And the other one is about automation of it. I think automation is about, OK, if a customer comes in with a service request and then say, “Hey, I have a problem” and how quickly we can segregate that into a different level so that it could be L1, L2 to L3 or to P1, P2 to P3 depends on how organization wants to categorize them into that. And most of the government institutions want to get those immediate queries addressed within 24 hours of time, as soon as possible. I think that’s what we have seen as the faster response to the customer service model. The other one is about using certain platforms around it. We have seen this customer service  front desk or back-office supports are now automated through various Bots actually. So we have seen bots being installed behind the scene so that as soon as they know anybody comes in and they want to see a faster response. Bots are highly intelligent now and we call this more sort of a robotic process automation now, even one step above to call themselves on hyper automation and the whole process of it is automated and the bots are trying to understand the customer request more in an intelligent way and provide the response in a faster resolution. I think those are some of the technologies that we have seen, even the government institution are trying to adopt. We have seen some of the large RPA and hyper-automation intelligent process automation tools are being bought by state and federal agencies and put them into the customer service platform as well. So that’s something we are seeing as an increased adoption to increase the customer satisfaction and therefore bringing more transparency to the end customers. 

Logan: Yeah, Cigniti speaker mentioned previously in the conversation some of the emerging technologies and you did a great job breaking down there, some of the different automation tools that are serving organizations both in the government sector as well as the private sector. Brian, are there some specifics that you might be able to share within your organization, whether it’s RPA bots or any other sort of automation tool where you’ve been able to apply this technology to customer service in your organization and seen some good results? 

Brian: Yeah, we’ve definitely tested the bots for sure. And we’re happy about that. And one thing I want to mention, though, when we talk about customer service is we do want to come back because Cigniti speaker mentioned KPIs. So we as leaders, we do want to come back and make sure we’re measuring, make sure we measure ourselves and meet those key KPIs or meet those affiliates, rather. And I mean, what gets measured gets improved. But we definitely like the bots in terms of being able to be responsive. It helps you with the responsiveness and it’s a move towards automating some of the larger dynamic things that we talked about in that are mentioned here already, artificial intelligence, predictive analytics, Internet of Things. I mean, these are all directions, things we want to go and directions we’re going in. But again, we realized before you run, you’ve got to be able to walk. And in order for any of these efforts, especially the predictive analytics and Internet of things, to be successful again without, continue to beat a dead horse, you’ve got to have that data centralized, normalized, and be able to ensure that the accessibility and ensure the accuracy of it in order for any of these efforts to be truly effective as part of the Digital transformation.  

Logan: Yeah, Brian, are there some areas where you see other organizations maybe try to run before they walk? Is it mostly in that, you know, getting the data set first? Are there some other areas where you see organizations might skip a few steps trying to apply some new technology before they’re ready for it? Any words of wisdom there in your own experience and kind of testing out new technology that you might give to some of your peers out there? 

Brain: Yeah, I mean, I definitely see it. I see it all the time, actually, because I’ve seen the people are so excited to use these technologies and harness these technologies, they forget some of the foundational principles that need to be in place beyond the infrastructure that needs to be in place before you can really get the true value out of these. But there are also some tricks that practitioners are using and where things are fundamentally changing in order to get access to that data before you’re building it out. Think of it in terms of almost the agile concept where you’re able to be a little more malleable and a little more flexible and agile just in response to some of the needs of the business and the customer. For instance, I grew up hearing the ETL; extract, transform, and load. We grew up hearing about it. Now, if you notice, we’re talking about we will change that dynamic now to ELT. So now you extract it, now you load it, and then you transform the data. So that’s one of the small ways where we’re changing and we’re trying to be a little more aggressive. And as long as there’s a system around it, it can be done. Even look at DevOps as another place that used to be a development house and then it used to be configuration management in between and then operations, even these two practices are getting married. Now, you’re there’s a term recently that’s just DevOps and it’s just become one term. So it’s inevitable that some of these things are going to be rushed and pushed. And I don’t know if it’s any one specific organization or specific field that’s doing it, but that’s the nature of IT, things are coming out so dynamic and you want to be aggressive, which you can as long as you have a strategy and as long as you know those foundational and infrastructure type systems that need to be in place. 

Logan: Yeah, very well said, Brian. You know, Cigniti speaker, quality assurance and testing is a common theme that we seem to hit on in about every episode of this podcast. Where do you see the impact of some of the emerging technologies that we’ve talked about here? AI, machine learning, predictive analytics, where those are being applied to quality assurance and testing processes. Let’s kind of connect those two in this conversation as well today. 

Cigniti speaker: Absolutely. I think quality assurance and testing is an integral part of any IT lifecycle. Even if you get the latest and the greatest technologies like AI or machine learning, predictive analytics or you call cloud or RPA, you need to have quality assurance and testing. So let’s say, for example, if I take a use case, I want to build an AI system with raw data. So without data, you cannot build it. So you need to have a lot of data. As Brian mentioned, about the ETL now transformed into ELT. In both cases, you need to verify the data. You need to make sure that the quality of data is met, the compliance is met, and the security is met. All of these you can do it only through your quality assurance and testing. So it is inevitable that you need to have quality assurance, as a use case for an AI. And the other technology, which Brian mentioned is about DevOps with development and operations coming in, a lot of people have a doubt that where would the testing go? Testing used to be in waterfall as an independent part before, now where would testing fit? Testing is now redefined as quality engineering and it gets fit right from the beginning of your lifecycle. You want to make sure whatever requirements that you are writing is met with a quality standard like a static requirement analyzer. If you build a design unit, make sure that you’ll drive your test driven development. Now, BDD and TTD are concepts on the development side along with the DevOps, you need to make sure that test driven development is also met. Test automation is ahead of your lifecycle, both in terms of functional, API service level of automation. So even in DevOps, testing and quality assurance exist in different form. I think for any industry experts to get into the quality assurance and testing, they have to upskill themselves into the engineering side of the world. They need to learn a lot of these new technologies, new programming tools. They need to equip themselves to understand the development side of the world, infrastructure side of the world, or the data side of the world, or the operations side of the world. So IT, you know, it’s now called a full-stack. And everyone needs to have some understanding of full-stack. While it might be applicable for developer. The full-stack definition may be different for quality assurance people. The full-stack is different for operation, but all of them need to have awareness towards the full-stack in this new IT world. 

Logan: Brian, I noticed you were nodding there as Cigniti speaker was talking about this concept of being taking a full-stack approach. What thoughts do you have there as you’re seeing that within your own organization and some of your peers lately? 

Brain: Well, I mean, just like everything Cigniti speaker said in terms of even with a horse racing and putting different disciplines and practices together, some of the fundamental things are not being cut out. Testing, like you said, quality assurance, whether you call it quality engineering, is still part of it. Whether we’ve moved from waterfall to agile with these fundamental things are still here. You’re still testing your software, you still testing your code before the rubber meets the road. So I just like the fact that even though things have changed and some methodologies are slightly different, some of these fundamental principles have not changed. 

Logan: Yeah, absolutely, Brain, as we close out the conversation today, any final thoughts for IT leaders out there as we’ve talked about the application of new technologies, starting with corralling your data, as you put it, and making sure that you have those foundational elements in place before you start to push forward with new digital transformation efforts or applying new technology that rolls into those strategies. Any parting thoughts for listeners out there today? 

Brain: Yeah, I just think we’d be remiss as leaders if we didn’t understand the importance of a strategy, of making sure that we as IT leaders have a clearly defined strategy and roadmap, and that strategy means nothing if it’s not anchored by the overarching strategy of the organization. And so we should be able to look at the strategy of the organization and create our IT strategy that’s anchored by the strategy and supported by that strategy in order to achieve. And from then, we should be able to carry that into a roadmap that turns in from the strategic to the actual tactical task and projects that we actually perform. And every one in our organization should be able to look at that roadmap and say, hey, this is where I fit in, this is where I add value. And that should be able to be mapped all the way back to the overarching strategy of the organization. 

Logan: And Brian, that is a great way to kind of put a bow on this conversation. We talked about, you know, getting your data together, organizing it from disparate systems, how that then impacts your service agreements with your internal and external customers, looking at applying new technologies. But all of that kind of rolls into the IT strategy has to be derived from the overall business strategy that it’s trying to serve. I think that’s phenomenal advice as we kind of got into the weeds in a number of different areas and bring it back to that foundational element has to be there or else all of these tactics aren’t going to serve the eventual purpose of helping deliver business outcomes, which are the most successful IT leaders are focused on that and therefore generating results for their organization.

Logan: I love it. Brian, for anyone listening to this, you’re new on their radar and they want to reach out to you or learn more about some of the initiatives you guys have going on at the Atlanta Housing Authority. What’s the best place for them to stay connected?   

Brain: LinkedIn is also a good spot. So I am on LinkedIn and I am Brian Benn with the Atlanta Housing Authority on LinkedIn. And you can always go to our website, which is www.atlantahousing.org and find out some of the things we’re doing and we’re excited about. 

Logan: Brian, Cigniti speaker, thank you again so much. And as always, folks, thank you so much for listening. 

Brain: Thanks for having me. It’s been a pleasure!  

Quality assurance is vital to the success of an organization’s digital transformation. Lack of control can quickly derail a company’s technological presence, costing thousands. At Cigniti, our resolution is to build a better world with better quality software. Renowned for the global quality thought leadership in the industry, we draw expertise from over a decade of test engineering experience across verticals. To learn how we do it, visit cigniti.com.   

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