Alter Everything

MaddieJ · ‎08-17-2020

Analytic Process Automation™ (APA) drives business and people outcomes all across the globe. In this episode, we hear from Middle East thought leaders Fahad Alsaawi and Nawar Hasan as they share why APA is crucial to adopt from a leadership perspective, and how they’re using advanced analytics to fight COVID-19.

Panelists

Maddie Johannsen - @MaddieJ, LinkedIn, Twitter
Fahad Alsaawi - LinkedIn, Twitter, Lean Business Services
Nawar Hasan - @nhasan1, LinkedIn

Topics

Copy of LinkedIn resize OTP -2.png

Transcript

Episode Transcription

MADDIE: 00:00	Welcome to Alter Everything, a podcast about data science and analytics culture. [music] I'm Maddie Johannsen, and for this episode, I spoke with two analytics thought leaders from the Middle East: Fahad Alsaawi calling from Saudi Arabia--
FAHAD: 00:14	Okay. So this is Fahad Alsaawi. I'm from Saudi Arabia. I'm currently holding a chief data officer position on one of the government companies that focus on healthcare and managing digital platform within the healthcare industry. And I have around 16 years of experience focusing on data and analytics.
MADDIE: 00:40	--and Nawar Hasan calling from Dubai.
NAWAR: 00:43	So you're having Nawar Hasan. So I manage the Alteryx Middle East for government sector., and I have been working closely with Fahad and many government entities in Saudi for the past year and so.
MADDIE: 00:59	Our chat is focused on analytics culture in the Middle East, how Fahad is using advanced analytics to fight COVID-19, and why analytics process automation or APA is crucial to adopt from a leadership perspective. Let's jump into it.
MADDIE: 01:17	That's great. Yeah. I'm so happy for you guys to be here. And I want to talk about analytics culture in the Middle East because, to be perfectly honest, we haven't had many, if any of our guests on, who are driving analytics in your region. So I'm really excited to hear your perspectives and just have you share about your everyday work in building analytics culture. And to be clear, Nawar, you're in Dubai, and Fahad, you're in Saudi. But since you're both leading on a regional level, I'd really love to hear just some background on the current landscape of analytics culture in the Middle East
FAHAD: 01:56	Okay. So when I go back and remember, before 2013, I hardly hear about analytics in Saudi. It's all basic BI function. However, after 2013, 2014, and the new trend of analytics and implementation of large analytics projects in Saudi, the culture of analytics and understanding of analytics took a different path. And suddenly within this then one year, everyone was very interested in implementing analytics and utilizing analytics to come up with better decisions and drive business actually. When I compare 2013 to 2020, it's a totally different era, to be honest. Back then, having just regular reporting and standard reporting is the goal of any entity or a company where it's just showing descriptive numbers. However, now it's different. When you come and meet with the government or private companies, the first thing that they will talk about is how we can utilize AI, machine learning, and advanced analytics to drive the direction of the business decisions within the company or the government company.
FAHAD: 03:30	And it's surprising that the adoption of analytics started heavily in government rather than private sector, at least in Saudi. Now, the culture is totally different about how they address data, how they address analytics. And it's due for so many reasons. However, one of the largest drivers is the vision of 2030 where the whole ecosystem of Saudi is transforming now toward becoming a different economy that is not only driven by oil, rather by industry and manufacturing. And data is an enabler and a driver for this transformation. So it's quite interesting to see and live this journey before and see it now on implementation on larger scale on different government and private companies.
NAWAR: 04:32	Yeah. Yeah. I totally agree. And I remember the first meeting that I had with Fahad, beginning of 2019, maybe the first one to meet with when I joined Alteryx. What Fahad mentioned is straight to the point. They began this transformation, whether in Saudi or across the Middle East, when it's focusing on the data, starting from having this data available to start enriching the data and then at the layer of the advanced analytics and machine learning-- I would call it the advanced analytics in general, whether from a data science perspective or from enrichment, so that we can come up with more tangible information that helps organization to take decisions based on that and see this current situation-- we see that live today in the market. We see that in the organization, taking decisions on data, becoming a data-driven organization rather than being reactive to the data and look at it from an exploration perspective to be fully data-driven. And I would be ignorant if I don't mention that one of the thought leader in that space was Fahad, from the early beginnings until today, whether driving from Lean perspective or being a true advocate for such a transformation. And here we're not focusing on the Alteryx piece but the overall landscape from data spectrum and data stack. I mean, many of our existing customers, many of the organizations in government sector in Saudi today have been listening to such thought leaders and built their strategy based on it.
NAWAR: 06:24	One of the stories, and this has happened last month, is with the Ministry of Health where we managed to save lives. We reached to the level where we're saving lives with the ministry so that we can limit the infection rates within COVID-19 as part of the pandemic that we're all experiencing and we're part of it to deliver it where I heard the customer saying, "I had a dream since 2012. Today, I have successfully implemented that dream or completed my dream from a data perspective." And this matches exactly what Fahad said that 2013, it might be the early beginnings; no one was paying attention to it. Today's it's the key driver for any organization, any success and especially when it comes-- from a nationwide perspective when you look at, for example, Saudi as a transforming-- the national transformation initiatives that we have across, the key processes with it, it's all related to data and enhance all this kind of processes within data domain.
MADDIE: 07:31	Yeah. I think that's all so interesting, and I have so many follow-up questions. And I think to start, I would love to stay on this kind of talking about COVID-19 and the healthcare work that you are seeing unfold and how data is playing such a huge role in that. And I feel like that's something that at Alteryx we've talked about a lot. We've seen a lot of people really leaning on Alteryx as such a powerful platform to help fight the infection rate. And I just want to hear a little bit more about that because it sounds like it really aligns with what you were saying about Vision 2030 about how from a government level it's this huge push across all industries. So it's interesting to see-- I wonder if maybe-- I don't know if COVID has accelerated the transformation in healthcare that aligns with Vision 2030, or how those two have worked together since the pandemic has surfaced.
FAHAD: 08:34	Okay. Yeah. Talking from real experience on the ground now, the COVID-19 epidemic was a surprise for everyone. Therefore, you don't have time even to think. You need tools, and you need people who can deliver rapidly and fast. And this is the biggest challenge for any organization or any entity that face such a problem like COVID-19 because you will be asked on a daily basis to give answers and to look for gaps using the data that is being collected on a regular basis for this epidemic. And having a tool like Alteryx where you can scale fast and you can develop and publish fastly, either from data wrangling, building data pipeline perspective or even building an advanced analytics and machine learning using whatever data that is available and producing the result as soon as you can.
FAHAD: 09:51	And this is very, very critical in this time. No one can wait, to be honest, to get the result, to get the advice that is driven by data. And when we see the experience across the world, everyone now is using the digital way of fighting COVID-19 because traditional way doesn't work with this virus. So using data, using some of the digital platforms is the only way to control and fight the epidemic. And this is what we manage to do using Alteryx. [music]
FAHAD: 10:39	We develop lots of workflows on a daily basis. We publish it on the Alteryx server where it's-- move data from one place to another place and restructure the data in addition to building advanced analytics models and publishing it on the server to be consumed. We recently even-- we went beyond the usual usage of Alteryx where we built web services integrated with systems because I need to go on production with certain projects, and I don't have the time to go the regular way. So Alteryx give you and enable you to deliver any project related to data in a short period with a robustness way. This is very important because unless you have a robust and optimized tool that you can rely on, especially for utilizing this tool to manage very critical tasks on a daily basis, unless you have a tool that you can trust, then you cannot use it on a regular basis and on a daily basis. So Alteryx in a nutshell became as something essential of our daily work currently in this time.
MADDIE: 12:08	Definitely. Something that really struck me that you really hit on was talking about how fast people need to deliver results. And as you said, Alteryx really helps to streamline, and there's a lot of processes in place that really help that workflow move along, right? But it all kind of reminds too of APA, Analytic Process Automation™, where we're talking about data, process, and people all coming together. And it made me think about how having to deliver at the drop of a hat and having to answer immediately, I think, puts a ton of pressure on people, right, and especially when the stakes are so high when it comes to healthcare or companies surviving and things like that. So I'm curious what kind of scramble are you seeing to upskill, if you're seeing any sort of like upskill urgency? And as a thought leader in the region, how do you manage that, and how do you help upskill people when at the same time you're also expected to yourself deliver insights and still perform at your highest level?
FAHAD: 13:20	Currently, everyone I think in every country is suffering from the shortage of people specialized in analytics and especially advanced analytics. I was in a managerial position since 2016 or 2015, and I had issues in bringing people that focus and work in analytics. Therefore, I decided that the best way is to build a pipeline of people who are very interested in learning analytics and give them kind of a career guidance and upskilling path where they start, and after six months, they suddenly see themselves surprised with the skills that they have added in the past six months. And this is what we did lately in Lean. We have co-op programs, cooperation with universities where senior students can join, selected junior students can join and spend their last semester working and upskilling themselves in multiple tools and multiple areas of analytics. And at the same time, we have an internship program; it extend to six months. So what we do now is we do not hire full-time employees, especially fresh graduates, unless they come and join as an intern for six months where we give them a very clear career path and upskilling courses, trainings, tasks that-- through this way, we make sure that whoever is joining after six months is ready.
FAHAD: 15:17	And I started not to focus, to be honest, on computer science people because what I have noticed-- with tools like Alteryx and the way analytics spectrum is changing, I don't need people from computer science background. When I go back and see my team now, we have people from system engineering, electrical engineering, different majors and different spectrum of education. And all of them have passion to learn analytics. And once they join, they immediately have a way of doing tasks and learning at the same time. So after six months, they are being evaluated and join the company full time. And I'm sure Nawar dealt with some of our employees. One of our brilliant employees is going to be-- and I challenge him all the time that he will be the first ACE, Alteryx ACE in the Middle East. And I'm sure that he will soon. One year and a half ago, he didn't hear about Alteryx. And now, he's doing an amazing project and delivery using Alteryx. So we have people who are passionate, who want to enter to this field; this is what I'm looking for. Once I identify those people, I immediately invest in them from training, upskilling, load them with tasks that is very challenging, which make them decide immediately whether this field is for them or not.
NAWAR: 17:13	Yeah. And I need to comment. So Fahad, you moved the organizations not only from a data-driven-- move it to data-driven organization. You also moved it to subject matter expert working on tools to be able to deliver such, I mean, I would say innovative solutions in the market and use cases for the customers that-- whether the use cases developed for Lean or for other consultative companies that you work for. And this is the power again-- is the Analytics Process Automation™, being able to provide such an easy-to-use tool, code-free, code-friendly. This is the power of it, being able to take anyone with any background to be able to start building their analysis journey, use cases, tangible ROI for organizations to be able to deliver faster insights in different areas and in different segmentation. [music] And this is the exciting part of the engagement with such top leaders. And especially in Saudi, we see this kind of transformation democratizing the data to everyone with their subject matter expertise to be able to build their own analysis and move it forward from an organizational perspective as well.
MADDIE: 18:45	It's funny because I'm always-- I don't know why this is, but I'm always so excited when I hear about just the really thoughtful plans that organizations and thought leaders like yourselves put in place for students. And it blows my mind because-- I mean, I didn't go to school for analytics or anything related to it. And I feel like when I graduated, there was a couple of career paths that I thought might interest me and a couple of steps that I could have taken, but I'd never really had that very clear sight, "Okay. Last semester of school, you can come be an intern. Or you can come work with us, and we'll upskill you and provide you a mentor, and I'll invest my time in you." I never really had that. And I'm curious, Fahad, did you have somebody that invested in you like you're investing in others, or were you kind of--? I have it in my mind-- from what I've heard about you, you're such an analytics legend in the region, and I imagine that you're-- as you mentioned earlier that you were such an early advocate and thought leader for analytics back in 2013. But who was your mentor? Did you have one?
FAHAD: 20:00	I hope it did not seem that I'm an old guy, but I started working with data in 2004.
MADDIE: 20:09	Got it. Yeah. Okay. [laughter]
FAHAD: 20:10	So I graduated in 2004 and immediately started working on data. Most of my colleagues went to finance, banks, financials, etc. But I like data and I like numbers, so I kept working in this field while this field was not that popular back then. No. I didn't have any mentorship or-- but it was an interesting field to me, and I knew that this is the future. So I invested a lot of my time and effort. Maybe I was spending double the time just to make sure that I reach a point where I manage to understand this field and the complexity of this field. And coming from a background not technology rather than business is something that gave me an edge over everyone. So my background is statistics, not computer science, and I have worked with lots of industries: education, health, labor market, etc. So I know the dynamics of data in all industries and all fields, and I talk business mostly. So I mix business with data. And this is the mix that any leader or any pioneer in this field should have because it's not pure technology, and it's not pure business. It's the mix between technology and data and business.
FAHAD: 21:51	But again, answering your question, no. And this is why-- not most of my time rather than some of my time I spend-- it's on Twitter and on LinkedIn answering questions, guiding people. I even spend some of my hours in a weekend answering some of students' questions. Some of them asked, "Okay. Do I specialize in analytics and data or not?" I sit with them even in coffee shops answering some of their questions. I do workshops regularly on universities just to show everyone what is data and what is analytics and what is the future because, again, I don't like to position data and analytics as a regular thing that anyone can do rather than, as Nawar mentioned, finding a problem, having a good solution how to solve this problem, using this solution with the bright minds near to you. So if you have a good solution, you have good people, then you can do anything, and you can solve any problem.
MADDIE: 23:10	Yeah. I think that that's really important, and I love hearing that. And I want to take a little bit of a step back actually and go back to something that, Fahad, you said earlier and that you started out in statistics. And I love that because we've talked a few times on this show about how the first data scientists were statisticians. And it sounds like in your work that you're really striking this balance between being an expert user of the software, a subject matter expert as well as being a business leader and a people person. So I'm curious, would you consider yourself as somebody who was excelling at all three of those from the beginning, or do you think that you initially had a strong suit in one of those categories, and then you wanted to upskill yourself, and you just kind of worked towards striking that perfect balance?
FAHAD: 24:07	It's quite interesting to see and-- go back a few years ago, I didn't even thought that I will be leading a huge team and implementing and being responsible for huge projects such what I'm leading and handling now. I used to be just an expert in the field, and I'm still. I practice and I do technical stuff on a daily basis. This is why I think it's challenging when I do interviews because I'm not really a managerial who is interviewing someone with a technical background. I'm on a managerial level. However, inside me there is a technical guy. So it's quite interesting. But at the end, you need to find the balance how to manage people with different backgrounds, with different technical experience. We have teams who focus on data engineering. We have teams who focus on advanced analytics and data governance, etc. And you need to do a balance of managing them, and at the same time you need to decide on very technical pieces on whatever solution that you want to develop.
FAHAD: 25:32	So I think it's a good mix that I come from a pure technical background and grow with time to deliver and manage projects, then manage portfolio of projects. This, I think, gave me an upper hand on most or at least some of the people in the field because I know I have the technical experience. I know how to build a solution from bottom up. I understand every detail. And at the same time, I know how to pick people and skills to reach a point-- to reach a point that all the team and the skills that they have complete each other. So it comes by nature I think. Maybe I'm lucky that I have this technical background, and I moved to management and-- delivering of projects and being responsible about the project. However, I think it comes natural. I didn't think about it. I didn't plan it, to be honest. It came by nature. Maybe I'm lucky. I don't know. But having a background with a technical experience benefited me a lot, a lot.
MADDIE: 26:59	Totally. Yeah. And I think it's important for people to embrace the skills and, as you mentioned earlier, the passions that they have. And to be clear, I don't think people need to be experts at everything, and I don't think you think that either. But let's say that an analyst does want to upskill their business acumen or vice versa. What tips do you have for people like that who want to explore these other areas? Because you've mentioned that you've had the opportunity with these portfolios that you managed, and you had the technical skills at the beginning. Let's say an analyst who does want to reach that next level. I'm curious how they get those opportunities to start developing that business acumen or those people skills.
FAHAD: 27:46	I think now in our days in Saudi, it's available everywhere to have the opportunity to at least try and see whether you're ready for this field or not, or if you are in this field and you want to upskill yourself and increase your experience in an industry or in a field such as analytics. For example, at Lean, we are open. Anyone who is interested in analytics and he want to spend some of his time to understand, to become more experienced in this field, we have an R&D initiative and program where people who have some ideas and they want to implement it related to healthcare, they can come and build it with-- and the team who has experience can support and help. However, they need to build experience in a specific field.
FAHAD: 28:55	Me coming from different background - I used to work in education field and labor market field and now when healthcare - it benefited me a lot from having a horizontal view. However, if I'm young and I need to learn skills, I need to focus on one industry at least at the beginning and master what's inside this industry from analytics and data perspective. Then after a while, you can expand and explore or explore more. Also, I don't recommend to go and say that they want to learn everything in analytics because analytics is not the analytics that everyone used to know three or four years ago. It's quite different. Now, we have people with dedicated data engineering skills, pure data engineering skills. We have people who are dedicated in advanced analytics and building machine learning and AI models. We have people who are focused only on managing data and documenting and supervising the maturity and the governance of data. So finding the right field, finding the right skills that you need to focus on at least at the beginning gives you and open for you the pathway to analytics to grow and understand more in this interesting field.
MADDIE: 30:30	Awesome. Yeah. That's great advice. Nawar, did you have anything to add?
NAWAR: 30:35	No, not to add. I had a question for Fahad-- when it comes to the current situation that we see. I mean, Vision 2030 might be an anchor in Saudi transformation, especially in the government sector. How do you see that today from transformation perspective? How do you see the adoption of-- not only from analytics perspective but from another-- digital transformation being more open to start leveraging tools as Alteryx and be able to get more insights. How do you see the progress from your perspective? I know that you're connected to most of the thought leaders and the C-level within the government sector, not only on Lean side but also on other government entities. So I'm curious to understand it from your point.
FAHAD: 31:30	Now, everyone is thinking about adopting analytics. Some of the government and even private sectors, especially-- and telecom and finance and banking, now they're seriously investing in analytics and data. Similarly and government agencies, now you will be surprised that you will see chief data officers in some of the government entities where someone is fully in charge of building a full data function within the entity itself. Because they realize that without utilizing the data that they have they cannot move to the next level, especially that now we became more mature from digital transformation and from technology perspective. So as you know, we have mature solution, applications, all government and non-government organization providing their services through digital platform.
FAHAD: 32:43	However, the next step is how to use whatever data that is generated from this platform to enhance the user experience, to enhance the service, and to drive the business itself. And it's interesting. If you go to the major events that is happening in Saudi, it's all managed and driven by data-- like major events, COVID-19 now, etc., you see that the whole driver of everything is the data that is generated. So it's quite interesting, and I think the future is great in our country. When you see everyone on a high level talks about data, this is very promising. This is, I think, encouraging everyone to invest and to put more investment in data analytics and building the foundation for building the advanced layer of analytics and AI.
NAWAR: 33:54	Yeah. Great. I've got also one point. Yeah. So this is definitely-- yeah. This is the movement that we're seeing, and it's very exciting-- the power of data. I mean, now we see the data is the new oil. So this is the trend now, and it's becoming a reality; not just an item that we use, but also it's a reality now that the data is the new oil. Something I would also need to ask is that-- Fahad, what is missing? What is missing from your perspective? Or from your opinion, what is missing now?
FAHAD: 34:31	What's missing now is a couple of things. First, the people with high skills, especially in the area of advanced analytics, AI and machine learning, and leaders who really believe in adopting some of the use cases. So everyone comes and say, "Okay. I want analytics, and then I want AI and machine learning." However, he will be surprised that there is no enough skills available in the market, which the government now is working to solve where they provide training, upskilling programs, etc. And this is what I'm trying to also to drive through having internship program and co-op programs. Secondly is having leaders who really believe in analytics and benefit of analytics; however, define the robust use cases that can be used to drive the business.
FAHAD: 35:42	If you look at all the government entities and private sector, now they have the infrastructure. They have the tools. They have everything. But they reach a point that, "Okay. What is the use case that we can utilize these tools and this data to achieve something to impact the business itself?" So they reach a point that they want to collect the results, but there is no people with business backgrounds, technical background that-- industry, SMEs that they can mix data with problems and technology and come and say, "Okay. We can do this to solve this problem." And I'm talking about big problems, big issues like education, healthcare, etc. So in my opinion, it's not the technology or availability of data and infrastructure. It's there now. However, people with experience that can mix all of this and solve the challenging issues and the challenging problems in front of either government or non-government--
NAWAR: 37:03	Definitely. And I totally agree. And part of our focus is the upskilling resources as part of the APA messaging-- one of the key pillars from Alteryx perspective is the people, right, and upskilling resources. And this is where Alteryx come with a lot of initiatives when it comes to-- Alteryx ADAPT, we're helping people that have been affected during the COVID-19, whether loosing their jobs or they need to look for more opportunities, and they need to upskill themselves. So Alteryx give this kind of opportunity to enroll for ADOPT and upskill your technical and your skills overall so that you can be ready for your next challenge. Along with that, we have also the Alteryx Discover free trainings platform for any customer who's interested to enroll and upskill. Along with it, of course, the community and have this kind of rich content that is available for anyone to use it and anyone to enroll for Alteryx courses and be able to map that to their subject-- I mean, to their expertise and background so that they become the next subject matter expert equipped with tools and technologies that they can deliver on top of--
MADDIE: 38:23	Totally. Yeah. I appreciate you calling those programs out, Nawar, because those are super important and also very, very popular. We've had a ton of people super interested in the ADAPT program and just the trainings available across the board that we have. It's something that we're very passionate about at Alteryx in general. It's just giving people what they need in order to upskill them and get them to where they want to be so they can start their analytics career. So we'll be sure to add link to all of those programs in the show notes for anybody out there who's interested. [music]
MADDIE: 39:00	Well, I think that's a great place to sign off you guys. I really appreciate you both being here, and your insights just totally blew me away. And I feel like I have such a good understanding of analytics culture in the Middle East now, and I am so thankful for you both being here today.
MADDIE: 39:21	Thanks for listening. To learn more about Analytics Process Automation™, the Alteryx ADAPT Program, advanced analytics in healthcare, or any other topics you've heard today, check out our show notes at community.alteryx.com/podcast. You can also join us on social media by using the hashtag AlterEverythingPodcast. Thanks.
FAHAD: 39:44	Definitely. Thank you, Maddie. Thank you.
NAWAR: 39:47	Thank you. [Arabic].
FAHAD: 39:52	[Arabic].
NAWAR: 40:23	Thank you, Maddie.
FAHAD: 40:24	Thank you, Maddie. Thank you.
MADDIE: 40:31	Wow. I have the biggest smile on my face. Thank you both for doing that. [laughter]
FAHAD: 40:35	No problems. Thank you, Maddie.
MADDIE: 40:38	Yeah. Absolutely. Such a beautiful language. Cool. I will go ahead and stop recording. Stay on the line with me. [music]

MADDIE: 00:00 Welcome to Alter Everything, a podcast about data science and analytics culture. [music] I'm Maddie Johannsen, and for this episode, I spoke with two analytics thought leaders from the Middle East: Fahad Alsaawi calling from Saudi Arabia-- FAHAD: 00:14 Okay. So this is Fahad Alsaawi. I'm from Saudi Arabia. I'm currently holding a chief data officer position on one of the government companies that focus on healthcare and managing digital platform within the healthcare industry. And I have around 16 years of experience focusing on data and analytics. MADDIE: 00:40 --and Nawar Hasan calling from Dubai. NAWAR: 00:43 So you're having Nawar Hasan. So I manage the Alteryx Middle East for government sector., and I have been working closely with Fahad and many government entities in Saudi for the past year and so. MADDIE: 00:59 Our chat is focused on analytics culture in the Middle East, how Fahad is using advanced analytics to fight COVID-19, and why analytics process automation or APA is crucial to adopt from a leadership perspective. Let's jump into it. MADDIE: 01:17 That's great. Yeah. I'm so happy for you guys to be here. And I want to talk about analytics culture in the Middle East because, to be perfectly honest, we haven't had many, if any of our guests on, who are driving analytics in your region. So I'm really excited to hear your perspectives and just have you share about your everyday work in building analytics culture. And to be clear, Nawar, you're in Dubai, and Fahad, you're in Saudi. But since you're both leading on a regional level, I'd really love to hear just some background on the current landscape of analytics culture in the Middle East FAHAD: 01:56 Okay. So when I go back and remember, before 2013, I hardly hear about analytics in Saudi. It's all basic BI function. However, after 2013, 2014, and the new trend of analytics and implementation of large analytics projects in Saudi, the culture of analytics and understanding of analytics took a different path. And suddenly within this then one year, everyone was very interested in implementing analytics and utilizing analytics to come up with better decisions and drive business actually. When I compare 2013 to 2020, it's a totally different era, to be honest. Back then, having just regular reporting and standard reporting is the goal of any entity or a company where it's just showing descriptive numbers. However, now it's different. When you come and meet with the government or private companies, the first thing that they will talk about is how we can utilize AI, machine learning, and advanced analytics to drive the direction of the business decisions within the company or the government company. FAHAD: 03:30 And it's surprising that the adoption of analytics started heavily in government rather than private sector, at least in Saudi. Now, the culture is totally different about how they address data, how they address analytics. And it's due for so many reasons. However, one of the largest drivers is the vision of 2030 where the whole ecosystem of Saudi is transforming now toward becoming a different economy that is not only driven by oil, rather by industry and manufacturing. And data is an enabler and a driver for this transformation. So it's quite interesting to see and live this journey before and see it now on implementation on larger scale on different government and private companies. NAWAR: 04:32 Yeah. Yeah. I totally agree. And I remember the first meeting that I had with Fahad, beginning of 2019, maybe the first one to meet with when I joined Alteryx. What Fahad mentioned is straight to the point. They began this transformation, whether in Saudi or across the Middle East, when it's focusing on the data, starting from having this data available to start enriching the data and then at the layer of the advanced analytics and machine learning-- I would call it the advanced analytics in general, whether from a data science perspective or from enrichment, so that we can come up with more tangible information that helps organization to take decisions based on that and see this current situation-- we see that live today in the market. We see that in the organization, taking decisions on data, becoming a data-driven organization rather than being reactive to the data and look at it from an exploration perspective to be fully data-driven. And I would be ignorant if I don't mention that one of the thought leader in that space was Fahad, from the early beginnings until today, whether driving from Lean perspective or being a true advocate for such a transformation. And here we're not focusing on the Alteryx piece but the overall landscape from data spectrum and data stack. I mean, many of our existing customers, many of the organizations in government sector in Saudi today have been listening to such thought leaders and built their strategy based on it. NAWAR: 06:24 One of the stories, and this has happened last month, is with the Ministry of Health where we managed to save lives. We reached to the level where we're saving lives with the ministry so that we can limit the infection rates within COVID-19 as part of the pandemic that we're all experiencing and we're part of it to deliver it where I heard the customer saying, "I had a dream since 2012. Today, I have successfully implemented that dream or completed my dream from a data perspective." And this matches exactly what Fahad said that 2013, it might be the early beginnings; no one was paying attention to it. Today's it's the key driver for any organization, any success and especially when it comes-- from a nationwide perspective when you look at, for example, Saudi as a transforming-- the national transformation initiatives that we have across, the key processes with it, it's all related to data and enhance all this kind of processes within data domain. MADDIE: 07:31 Yeah. I think that's all so interesting, and I have so many follow-up questions. And I think to start, I would love to stay on this kind of talking about COVID-19 and the healthcare work that you are seeing unfold and how data is playing such a huge role in that. And I feel like that's something that at Alteryx we've talked about a lot. We've seen a lot of people really leaning on Alteryx as such a powerful platform to help fight the infection rate. And I just want to hear a little bit more about that because it sounds like it really aligns with what you were saying about Vision 2030 about how from a government level it's this huge push across all industries. So it's interesting to see-- I wonder if maybe-- I don't know if COVID has accelerated the transformation in healthcare that aligns with Vision 2030, or how those two have worked together since the pandemic has surfaced. FAHAD: 08:34 Okay. Yeah. Talking from real experience on the ground now, the COVID-19 epidemic was a surprise for everyone. Therefore, you don't have time even to think. You need tools, and you need people who can deliver rapidly and fast. And this is the biggest challenge for any organization or any entity that face such a problem like COVID-19 because you will be asked on a daily basis to give answers and to look for gaps using the data that is being collected on a regular basis for this epidemic. And having a tool like Alteryx where you can scale fast and you can develop and publish fastly, either from data wrangling, building data pipeline perspective or even building an advanced analytics and machine learning using whatever data that is available and producing the result as soon as you can. FAHAD: 09:51 And this is very, very critical in this time. No one can wait, to be honest, to get the result, to get the advice that is driven by data. And when we see the experience across the world, everyone now is using the digital way of fighting COVID-19 because traditional way doesn't work with this virus. So using data, using some of the digital platforms is the only way to control and fight the epidemic. And this is what we manage to do using Alteryx. [music] FAHAD: 10:39 We develop lots of workflows on a daily basis. We publish it on the Alteryx server where it's-- move data from one place to another place and restructure the data in addition to building advanced analytics models and publishing it on the server to be consumed. We recently even-- we went beyond the usual usage of Alteryx where we built web services integrated with systems because I need to go on production with certain projects, and I don't have the time to go the regular way. So Alteryx give you and enable you to deliver any project related to data in a short period with a robustness way. This is very important because unless you have a robust and optimized tool that you can rely on, especially for utilizing this tool to manage very critical tasks on a daily basis, unless you have a tool that you can trust, then you cannot use it on a regular basis and on a daily basis. So Alteryx in a nutshell became as something essential of our daily work currently in this time. MADDIE: 12:08 Definitely. Something that really struck me that you really hit on was talking about how fast people need to deliver results. And as you said, Alteryx really helps to streamline, and there's a lot of processes in place that really help that workflow move along, right? But it all kind of reminds too of APA, Analytic Process Automation™, where we're talking about data, process, and people all coming together. And it made me think about how having to deliver at the drop of a hat and having to answer immediately, I think, puts a ton of pressure on people, right, and especially when the stakes are so high when it comes to healthcare or companies surviving and things like that. So I'm curious what kind of scramble are you seeing to upskill, if you're seeing any sort of like upskill urgency? And as a thought leader in the region, how do you manage that, and how do you help upskill people when at the same time you're also expected to yourself deliver insights and still perform at your highest level? FAHAD: 13:20 Currently, everyone I think in every country is suffering from the shortage of people specialized in analytics and especially advanced analytics. I was in a managerial position since 2016 or 2015, and I had issues in bringing people that focus and work in analytics. Therefore, I decided that the best way is to build a pipeline of people who are very interested in learning analytics and give them kind of a career guidance and upskilling path where they start, and after six months, they suddenly see themselves surprised with the skills that they have added in the past six months. And this is what we did lately in Lean. We have co-op programs, cooperation with universities where senior students can join, selected junior students can join and spend their last semester working and upskilling themselves in multiple tools and multiple areas of analytics. And at the same time, we have an internship program; it extend to six months. So what we do now is we do not hire full-time employees, especially fresh graduates, unless they come and join as an intern for six months where we give them a very clear career path and upskilling courses, trainings, tasks that-- through this way, we make sure that whoever is joining after six months is ready. FAHAD: 15:17 And I started not to focus, to be honest, on computer science people because what I have noticed-- with tools like Alteryx and the way analytics spectrum is changing, I don't need people from computer science background. When I go back and see my team now, we have people from system engineering, electrical engineering, different majors and different spectrum of education. And all of them have passion to learn analytics. And once they join, they immediately have a way of doing tasks and learning at the same time. So after six months, they are being evaluated and join the company full time. And I'm sure Nawar dealt with some of our employees. One of our brilliant employees is going to be-- and I challenge him all the time that he will be the first ACE, Alteryx ACE in the Middle East. And I'm sure that he will soon. One year and a half ago, he didn't hear about Alteryx. And now, he's doing an amazing project and delivery using Alteryx. So we have people who are passionate, who want to enter to this field; this is what I'm looking for. Once I identify those people, I immediately invest in them from training, upskilling, load them with tasks that is very challenging, which make them decide immediately whether this field is for them or not. NAWAR: 17:13 Yeah. And I need to comment. So Fahad, you moved the organizations not only from a data-driven-- move it to data-driven organization. You also moved it to subject matter expert working on tools to be able to deliver such, I mean, I would say innovative solutions in the market and use cases for the customers that-- whether the use cases developed for Lean or for other consultative companies that you work for. And this is the power again-- is the Analytics Process Automation™, being able to provide such an easy-to-use tool, code-free, code-friendly. This is the power of it, being able to take anyone with any background to be able to start building their analysis journey, use cases, tangible ROI for organizations to be able to deliver faster insights in different areas and in different segmentation. [music] And this is the exciting part of the engagement with such top leaders. And especially in Saudi, we see this kind of transformation democratizing the data to everyone with their subject matter expertise to be able to build their own analysis and move it forward from an organizational perspective as well. MADDIE: 18:45 It's funny because I'm always-- I don't know why this is, but I'm always so excited when I hear about just the really thoughtful plans that organizations and thought leaders like yourselves put in place for students. And it blows my mind because-- I mean, I didn't go to school for analytics or anything related to it. And I feel like when I graduated, there was a couple of career paths that I thought might interest me and a couple of steps that I could have taken, but I'd never really had that very clear sight, "Okay. Last semester of school, you can come be an intern. Or you can come work with us, and we'll upskill you and provide you a mentor, and I'll invest my time in you." I never really had that. And I'm curious, Fahad, did you have somebody that invested in you like you're investing in others, or were you kind of--? I have it in my mind-- from what I've heard about you, you're such an analytics legend in the region, and I imagine that you're-- as you mentioned earlier that you were such an early advocate and thought leader for analytics back in 2013. But who was your mentor? Did you have one? FAHAD: 20:00 I hope it did not seem that I'm an old guy, but I started working with data in 2004. MADDIE: 20:09 Got it. Yeah. Okay. [laughter] FAHAD: 20:10 So I graduated in 2004 and immediately started working on data. Most of my colleagues went to finance, banks, financials, etc. But I like data and I like numbers, so I kept working in this field while this field was not that popular back then. No. I didn't have any mentorship or-- but it was an interesting field to me, and I knew that this is the future. So I invested a lot of my time and effort. Maybe I was spending double the time just to make sure that I reach a point where I manage to understand this field and the complexity of this field. And coming from a background not technology rather than business is something that gave me an edge over everyone. So my background is statistics, not computer science, and I have worked with lots of industries: education, health, labor market, etc. So I know the dynamics of data in all industries and all fields, and I talk business mostly. So I mix business with data. And this is the mix that any leader or any pioneer in this field should have because it's not pure technology, and it's not pure business. It's the mix between technology and data and business. FAHAD: 21:51 But again, answering your question, no. And this is why-- not most of my time rather than some of my time I spend-- it's on Twitter and on LinkedIn answering questions, guiding people. I even spend some of my hours in a weekend answering some of students' questions. Some of them asked, "Okay. Do I specialize in analytics and data or not?" I sit with them even in coffee shops answering some of their questions. I do workshops regularly on universities just to show everyone what is data and what is analytics and what is the future because, again, I don't like to position data and analytics as a regular thing that anyone can do rather than, as Nawar mentioned, finding a problem, having a good solution how to solve this problem, using this solution with the bright minds near to you. So if you have a good solution, you have good people, then you can do anything, and you can solve any problem. MADDIE: 23:10 Yeah. I think that that's really important, and I love hearing that. And I want to take a little bit of a step back actually and go back to something that, Fahad, you said earlier and that you started out in statistics. And I love that because we've talked a few times on this show about how the first data scientists were statisticians. And it sounds like in your work that you're really striking this balance between being an expert user of the software, a subject matter expert as well as being a business leader and a people person. So I'm curious, would you consider yourself as somebody who was excelling at all three of those from the beginning, or do you think that you initially had a strong suit in one of those categories, and then you wanted to upskill yourself, and you just kind of worked towards striking that perfect balance? FAHAD: 24:07 It's quite interesting to see and-- go back a few years ago, I didn't even thought that I will be leading a huge team and implementing and being responsible for huge projects such what I'm leading and handling now. I used to be just an expert in the field, and I'm still. I practice and I do technical stuff on a daily basis. This is why I think it's challenging when I do interviews because I'm not really a managerial who is interviewing someone with a technical background. I'm on a managerial level. However, inside me there is a technical guy. So it's quite interesting. But at the end, you need to find the balance how to manage people with different backgrounds, with different technical experience. We have teams who focus on data engineering. We have teams who focus on advanced analytics and data governance, etc. And you need to do a balance of managing them, and at the same time you need to decide on very technical pieces on whatever solution that you want to develop. FAHAD: 25:32 So I think it's a good mix that I come from a pure technical background and grow with time to deliver and manage projects, then manage portfolio of projects. This, I think, gave me an upper hand on most or at least some of the people in the field because I know I have the technical experience. I know how to build a solution from bottom up. I understand every detail. And at the same time, I know how to pick people and skills to reach a point-- to reach a point that all the team and the skills that they have complete each other. So it comes by nature I think. Maybe I'm lucky that I have this technical background, and I moved to management and-- delivering of projects and being responsible about the project. However, I think it comes natural. I didn't think about it. I didn't plan it, to be honest. It came by nature. Maybe I'm lucky. I don't know. But having a background with a technical experience benefited me a lot, a lot. MADDIE: 26:59 Totally. Yeah. And I think it's important for people to embrace the skills and, as you mentioned earlier, the passions that they have. And to be clear, I don't think people need to be experts at everything, and I don't think you think that either. But let's say that an analyst does want to upskill their business acumen or vice versa. What tips do you have for people like that who want to explore these other areas? Because you've mentioned that you've had the opportunity with these portfolios that you managed, and you had the technical skills at the beginning. Let's say an analyst who does want to reach that next level. I'm curious how they get those opportunities to start developing that business acumen or those people skills. FAHAD: 27:46 I think now in our days in Saudi, it's available everywhere to have the opportunity to at least try and see whether you're ready for this field or not, or if you are in this field and you want to upskill yourself and increase your experience in an industry or in a field such as analytics. For example, at Lean, we are open. Anyone who is interested in analytics and he want to spend some of his time to understand, to become more experienced in this field, we have an R&D initiative and program where people who have some ideas and they want to implement it related to healthcare, they can come and build it with-- and the team who has experience can support and help. However, they need to build experience in a specific field. FAHAD: 28:55 Me coming from different background - I used to work in education field and labor market field and now when healthcare - it benefited me a lot from having a horizontal view. However, if I'm young and I need to learn skills, I need to focus on one industry at least at the beginning and master what's inside this industry from analytics and data perspective. Then after a while, you can expand and explore or explore more. Also, I don't recommend to go and say that they want to learn everything in analytics because analytics is not the analytics that everyone used to know three or four years ago. It's quite different. Now, we have people with dedicated data engineering skills, pure data engineering skills. We have people who are dedicated in advanced analytics and building machine learning and AI models. We have people who are focused only on managing data and documenting and supervising the maturity and the governance of data. So finding the right field, finding the right skills that you need to focus on at least at the beginning gives you and open for you the pathway to analytics to grow and understand more in this interesting field. MADDIE: 30:30 Awesome. Yeah. That's great advice. Nawar, did you have anything to add? NAWAR: 30:35 No, not to add. I had a question for Fahad-- when it comes to the current situation that we see. I mean, Vision 2030 might be an anchor in Saudi transformation, especially in the government sector. How do you see that today from transformation perspective? How do you see the adoption of-- not only from analytics perspective but from another-- digital transformation being more open to start leveraging tools as Alteryx and be able to get more insights. How do you see the progress from your perspective? I know that you're connected to most of the thought leaders and the C-level within the government sector, not only on Lean side but also on other government entities. So I'm curious to understand it from your point. FAHAD: 31:30 Now, everyone is thinking about adopting analytics. Some of the government and even private sectors, especially-- and telecom and finance and banking, now they're seriously investing in analytics and data. Similarly and government agencies, now you will be surprised that you will see chief data officers in some of the government entities where someone is fully in charge of building a full data function within the entity itself. Because they realize that without utilizing the data that they have they cannot move to the next level, especially that now we became more mature from digital transformation and from technology perspective. So as you know, we have mature solution, applications, all government and non-government organization providing their services through digital platform. FAHAD: 32:43 However, the next step is how to use whatever data that is generated from this platform to enhance the user experience, to enhance the service, and to drive the business itself. And it's interesting. If you go to the major events that is happening in Saudi, it's all managed and driven by data-- like major events, COVID-19 now, etc., you see that the whole driver of everything is the data that is generated. So it's quite interesting, and I think the future is great in our country. When you see everyone on a high level talks about data, this is very promising. This is, I think, encouraging everyone to invest and to put more investment in data analytics and building the foundation for building the advanced layer of analytics and AI. NAWAR: 33:54 Yeah. Great. I've got also one point. Yeah. So this is definitely-- yeah. This is the movement that we're seeing, and it's very exciting-- the power of data. I mean, now we see the data is the new oil. So this is the trend now, and it's becoming a reality; not just an item that we use, but also it's a reality now that the data is the new oil. Something I would also need to ask is that-- Fahad, what is missing? What is missing from your perspective? Or from your opinion, what is missing now? FAHAD: 34:31 What's missing now is a couple of things. First, the people with high skills, especially in the area of advanced analytics, AI and machine learning, and leaders who really believe in adopting some of the use cases. So everyone comes and say, "Okay. I want analytics, and then I want AI and machine learning." However, he will be surprised that there is no enough skills available in the market, which the government now is working to solve where they provide training, upskilling programs, etc. And this is what I'm trying to also to drive through having internship program and co-op programs. Secondly is having leaders who really believe in analytics and benefit of analytics; however, define the robust use cases that can be used to drive the business. FAHAD: 35:42 If you look at all the government entities and private sector, now they have the infrastructure. They have the tools. They have everything. But they reach a point that, "Okay. What is the use case that we can utilize these tools and this data to achieve something to impact the business itself?" So they reach a point that they want to collect the results, but there is no people with business backgrounds, technical background that-- industry, SMEs that they can mix data with problems and technology and come and say, "Okay. We can do this to solve this problem." And I'm talking about big problems, big issues like education, healthcare, etc. So in my opinion, it's not the technology or availability of data and infrastructure. It's there now. However, people with experience that can mix all of this and solve the challenging issues and the challenging problems in front of either government or non-government-- NAWAR: 37:03 Definitely. And I totally agree. And part of our focus is the upskilling resources as part of the APA messaging-- one of the key pillars from Alteryx perspective is the people, right, and upskilling resources. And this is where Alteryx come with a lot of initiatives when it comes to-- Alteryx ADAPT, we're helping people that have been affected during the COVID-19, whether loosing their jobs or they need to look for more opportunities, and they need to upskill themselves. So Alteryx give this kind of opportunity to enroll for ADOPT and upskill your technical and your skills overall so that you can be ready for your next challenge. Along with that, we have also the Alteryx Discover free trainings platform for any customer who's interested to enroll and upskill. Along with it, of course, the community and have this kind of rich content that is available for anyone to use it and anyone to enroll for Alteryx courses and be able to map that to their subject-- I mean, to their expertise and background so that they become the next subject matter expert equipped with tools and technologies that they can deliver on top of-- MADDIE: 38:23 Totally. Yeah. I appreciate you calling those programs out, Nawar, because those are super important and also very, very popular. We've had a ton of people super interested in the ADAPT program and just the trainings available across the board that we have. It's something that we're very passionate about at Alteryx in general. It's just giving people what they need in order to upskill them and get them to where they want to be so they can start their analytics career. So we'll be sure to add link to all of those programs in the show notes for anybody out there who's interested. [music] MADDIE: 39:00 Well, I think that's a great place to sign off you guys. I really appreciate you both being here, and your insights just totally blew me away. And I feel like I have such a good understanding of analytics culture in the Middle East now, and I am so thankful for you both being here today. MADDIE: 39:21 Thanks for listening. To learn more about Analytics Process Automation™, the Alteryx ADAPT Program, advanced analytics in healthcare, or any other topics you've heard today, check out our show notes at community.alteryx.com/podcast. You can also join us on social media by using the hashtag AlterEverythingPodcast. Thanks. FAHAD: 39:44 Definitely. Thank you, Maddie. Thank you. NAWAR: 39:47 Thank you. [Arabic]. FAHAD: 39:52 [Arabic]. NAWAR: 40:23 Thank you, Maddie. FAHAD: 40:24 Thank you, Maddie. Thank you. MADDIE: 40:31 Wow. I have the biggest smile on my face. Thank you both for doing that. [laughter] FAHAD: 40:35 No problems. Thank you, Maddie. MADDIE: 40:38 Yeah. Absolutely. Such a beautiful language. Cool. I will go ahead and stop recording. Stay on the line with me. [music]

This episode of Alter Everything was produced by Maddie Johannsen (@MaddieJ).
Special thanks to @andyuttley for the theme music track, and @jeho for our album artwork.

Alter Everything

Episode Guide

68: Analytic Process Automation in the Middle East

Panelists

Topics

Transcript

This episode of Alter Everything was produced by Maddie Johannsen (@MaddieJ).
Special thanks to @andyuttley for the theme music track, and @jeho for our album artwork.

Alter Everything

Episode Guide

68: Analytic Process Automation in the Middle East

Panelists

Topics

Transcript

This episode of Alter Everything was produced by Maddie Johannsen (@MaddieJ).Special thanks to @andyuttley for the theme music track, and @jeho for our album artwork.

This episode of Alter Everything was produced by Maddie Johannsen (@MaddieJ).
Special thanks to @andyuttley for the theme music track, and @jeho for our album artwork.