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  • Gunjan Syal

How The Data Drives Success

Updated: 4 days ago


I started my career by designing, achitecting and operationalizing enterprise-wide data-enabled supply chains. It is no surprise that data has a special place in my heart. This is especially true now, as we use data in novel ways to overcome global supply chain issues and enable new revenue models.


Chris, from 'Interviews with Chris' at Future-proof Container Terminals podcast, recently invited me to share how data drives digital transformation and innovation success. I returned the favour by inviting Chris to co-write this blog post (sharing is caring within our professional community).


Data Drives Digital Transformation Success, by Christopher A. Saavedra Tam

Today more than ever data is essential. It creates a foundation to improve the business performance and the working environment for people. To enable this, companies need to ensure that data is visible, reliable, secure, and scalable so users can improve decision-making. There is no one-size fits all solution when it comes to data management, but in the practice, there are different aspects to cover such as collecting, organizing, protecting, and storing data so the company can analyze it for business purposes.

At the same time, we hear more and more about how the companies are evaluating different levels of digital transformations. The reality is that there are many challenges. A good starting point is to understand the ways of working and identifying the right technology that will enable the company’s targets.

One of the main concerns for users and companies is compliance and privacy regulations. These are keys for success on the digital journey. It is necessary to not only comply with local and international regulations, but also to internally share specific data with specific users. This is why it is so important to be aware of the industry best practices and adapt those into the different journeys.


If you enjoyed this conversation, join the global transform this community for future editions of 'Transformation to Innovation'.


Gunjan's Epilogue

I really enjoyed this conversation with Chris that covers multiple aspects of how the data enables success across digital transformations and innovation. It reminded me of another set of conversations.


This January, I was invited for an informal meeting with a member of the Google Cloud - Office of the CTO (OCTO). She and I had an interesting talk about digital transformations and innovation. I shared my cross-industry experience of over 15 years, supporting almost 40 companies across multiple industries. This included the special context I have developed in the public sector and education industries, among others, during the pandemic.


I shared the types of changes clients wish to make in their post pandemic business models, the challenges in current solution delivery models that lead to failed digital transformation attempts at the cost of long-lasting trust in technology and the hefty financial costs to client organizations, as well as the society.


I also had talks with the members of Google Customer Engineering and the Partnership teams in the Fall 2021, when I was exploring GoEmerald's partnership with tech firms. I had shared thoughts and questions regarding the partnership engagements to better align data lakes and lakehouse solution offerings to the customer organizations.


These are important and high impact conversations, despite the informal meeting settings. These topics enable innovation at scale for effective and accelerated value creation towards a high ROI future. All-hands on deck to enable innovation will be a great accomplishment, when done in a way that acknowledges and rewards the ecosystem stakeholders equitably.


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If you enjoyed this conversation, join the global transform this community for future editions of 'Transformation to Innovation'.


 
Video Transcript (autogenerated, unverified)

welcome everyone to this future-proof container terminals episode today we got a really interesting guest Gunjan Syal, these days leading goEmerald as founder and chief strategy officer and especially these days that we're hearing more about digital transformation uh all these changes due to the global pandemic is really important for us how important is the role of data how data is changing affordable working and how can we benefit from data so with that being said gunjan welcome to the stage thank you so much chris i know you and i have been talking probably for about an year and a half now and it's so exciting to be here having a formal conversation and share with people some of the conversations you and i've been having offline thank you for having me that's great gunjan and i am really excited to hear about your thoughts regarding data and all your experiences you are constantly getting together with your customers so okay yeah so before before starting the the hardcore questions gunjan that the plan for today is that we have been putting together some questions not only from my side but also based on your experiences and the plan is to go through them and uh just feel free to share your lesson learns experiences and thoughts so if that's okay for you let's go for it absolutely let's get ahead great so good and for those who haven't got the chance to to meet you yet could you share a little bit more about the who is gunjan absolutely thank you chris so i'm known as gunjan from goEmerald i have 15 years of experience delivering digital transformations for 27 clients in nine industries go emerald is a data obsessed transformation innovation firm and we focus on delivering high roi innovation and transformations for clients these days so that's consultant speak for i solve really really complicated business problems with strategy data and technology these days in such a way that the end result is visible measurable and repeatable i also host global tech circles conversations which is really very near and dear to my heart because i'm very passionate about responsible and inclusive innovation and it's always amazing to me to hear point of views from different parts of the world how they relate to each other and also sometimes how they differ based on the lifestyles and the challenges people have in different parts of the world awesome awesome going in and i can also share that i got like common common passions together with you and uh i am one of your frequent users absolutely and it's always a pleasure to have you chris great and and you know you mentioned a lot of stuff about the digital transformation data but i always like to ask this question so how would you describe the role of data on digital transformation absolutely that's a wonderful question uh chris so sometimes we get too hung up on specific uses of data within a company right but it's so much more than that the overall role of data in a digital transformation actually is to be that decision driver and that's how i take data to be so we can identify what are the driving forces behind that digital transformation measure them and drive behavior and changes that we're making in our company using that data that's the role of data for me in that digital transformation world more than one word but decision driver yeah i can understand that it's quite tricky to define yeah in one word you know because when we talk about data we are touching different aspects of many elements here but yeah and then gunjan i would like also to to understand a little bit more why do we need to focus on that and now and not in the future right that's a great question chris so from my point of view there's the way we have approached digital transformation and business in past versus now the big difference is using data to make decisions and not intuition right um the reason for that is we talked about how many times and how many different types of changes we have seen due to pandemic in the customer preferences in the economic world in many different factors that affect a business it's impossible for any one person to sit down and have that intuition in their gut and be making those decisions right and in a larger company in a larger organization that's going through transformation you can't have any set of people that have that intuition so the only way to do that is by collecting data to understand what's happening in the market what's happening inside our business what are our customers looking for what's happening at the local level versus global levels right um i could give you one simple example if you even think about the way that our governments and our stakeholders are controlling the whole pandemic situation right now right the way that the policy is being designed it's all based on data isn't it the covid tracing apps that we talked about there's a lot of privacy type conversations there as well but if you don't have data how are you going to make those decisions right how would you safeguard the public so these are all the reasons why data has so much more focus on it now is forming a foundational backbone if you will for how you run your business how you may run your country for that matter as a leader right yeah and i am totally aligned with you and especially well you know i am involved in the maritime industry with the terminals and especially for operations you need real-time data you need quality data is not only generating data and storing data it's how do you make this data visible and useful at the right time so it is really interesting all this topic around dram data and uh and gunjan you have been leading go emerald these days you know before the pandemic through the pandemic let's say almost post pandemic what is your why at guava what is your purpose of right so that's a great question right so let me put this in context of a digital transformation itself which is which is what we do um so the way that ad go emerald and our customers approach digital transformation in past would have been through alignment of people process technology right and i know chris you and i have had many conversations about that what does that mean in terms of process people technology because oftentimes people tend to focus more on the technology piece of digital transformation and in past we've had problems aligning processes and people and the stakeholders outside of that technology team to it but what's happened during pandemic is um data almost you can think of it like a layer around people process technology right if you don't have data available how are you actually going to build that alignment so these days go emeralds is much more focused on the data side enabling that as well along with that comes public policy and regulations right so if you think about for example the terminals right airports let's talk about them for a second how their business was impacted during pandemic right flights were shut down regulations had to be placed on who can get on a flight and who can't and it's not just the airport that can design that but the policy makers the people that a lot of number of different stakeholders have to come together to make that happen so when i look at the why of go emerald post pandemic it's still to enable those digital transformations still to make companies more innovative but now the focus is let's say one layer is people process technology with data wrapper around it and with focus on public policy and regulations to ensure the inclusion the equity the safety all of those different factors that are needed to make society more productive for everyone right and for businesses and their customers yeah in one word it's like an ecosystem you know that needs to be now totally communicated to to get so everyone can get the benefit of this data and you know i'm really passionate about these uh people process and uh and technology because it's like you need to find the perfect balance between especially people and technology these days because um it's it's also on my day-to-day that even though you got on state-of-the-art uh technology in your terminal you need people yeah to manage that's a very interesting point chris and if i may add something to it right the way that i think about technology now is garbage and garbage out to your point if your people process you know data aside and public policy aside if those two elements are not aligned you are going to use certain assumptions and some constraints to design the technology solutions and you are going to have a whole ton of unintended consequences at the end of that and you won't even know what those risks are or what those the impact if you will of it is going to be if you don't pay attention to all these different five factors that we've talked about right people process technology data and public policy they're not watching them all at the same time there's a risk right there to your business to your customers to overall society right that's right and and that links me to my next question gundian as a chief strategy officer i am aware you are involved in so many industries but uh could you share a little bit more about what are the main challenges you're facing not only within your team but also together with your research customers absolutely that's a wonderful question right so as you said um if i ignore the industries if i ignore even geographical boundaries for a second one fact that's that's very true no matter whether you're a non-profit or a for-profit company or even a government you have data in some shape or form whether you're using it or not right whether you're even tracing it or not even if it's on a piece of paper it's still data still information so all that data flows like a river through your company right and in past we haven't been as cognizant um about what that means right we we have different departments with different mandates the different objectives but it's not really connected so postmanamic there's a lot of need to take all those things and build this alignment and more importantly stay aligned and that's very very complex so it actually starts with understanding what the stakeholders are who are they i should say what are their needs why are they touching that data why do they need that data right what is the series of complex changes that are happening to that data so following that journey as opposed to looking at it piecemeal so that's where it's very important to define the overall data strategy why do you need it when do you need it who will benefit from it some of those type of things and then figuring out how to break down those data silos right oftentimes people get too hung up on data silos and lose sight of the data strategy so i always have to go back and remind people and sometimes even myself right you you get so focused on solving one particular problem you don't want to lose the side of the forest because you're focused on this one tree at the moment so how do you build that alignment then as well overall when i look at it data governance which is all about ensuring once you have made those changes let's say successfully how will you effectively manage the way that you're using data to drive decisions in your company ultimately that's the goal right and this is where some standards some policies whether they're internal or external to your company some constraints that come into place to ultimately use data as an asset for your company instead of a particular department owning it and a lot of data literacy goes along with that as well so i know i threw out a lot of bunch of buzzwords in there but essentially if you think about how you're defining data strategy to break down those data silos and how you're linking that to the data governance you need in place after you have actually accomplished that successfully it's not a project right so very much of a product conversation data needs to be a product within your company how would you leverage that how will you teach people how to use it there would be times when you make changes to it right because something else has changed how will all of that happen really interesting and i can feel your your passion here and and you know gunjan for me supporting customers and on echo efficiency your knees or automation your needs the difference between success and failure is change management so how would you describe the role of change management in in indeed the transformation for example right right so the way that i equate change management people may agree or disagree uh the the change management for data is data governance to be very honest with you um and usually in organizations there will be certain teams that are tasked with data governance i would say 80 of that team's job in the beginning is nothing more than change management right and that means aligning your stakeholders that means understanding through that transformation journey challenging part is that even your stakeholders roles are changing right so how will you actually work with them while your own role is changing while their role is changing and the company itself is changing is a very challenging task so even building alignment and data literacy plans within that data governance team it's nothing short of change management over and and you mentioned already quite many times the worst silos you know that's like a cliche like asking you what is a silo but could you describe what is a silo what is the main why does this generate you know how should we have how can we avoid sight loss same question uh chris and very very near and dear to my heart actually um so let's take a step back and look at how this problem happened in the first place right so data silo essentially means that one part of the company or one department has access to certain data that others may not even know about right or maybe they know about it but they don't have access to it somehow so it's at the core of it an access problem right to the data sometimes it may actually be that the data is replicated in two or three different places and that's an issue now right which leads to data quality issues so how does that happen in the first place uh it's very important to understand that before we can actually think about solving that problem so in most organizations they're very projectized right so they would say okay well let's deploy this application on a digital transformation or look at this part of the business from an operations perspective because there's more efficiencies needed there let's take terminals as an example right you may be making changes to baggage claim let's say now apart from the hardware and the the stuff that you actually see in an airport there's a lot of systems a lot of processes behind the scenes correct you know more about it than i do about this stuff right being part of that terminals world um now if you're going to do silo projects they all have a start and an end right so you've been given a mandate go and solve this problem you are going to make certain decisions and you are going to make certain assumptions to accomplish that project which other people outside of that team may or may not be aware of right that's the problem with projects and that's you do that times a hundred times a thousand times which a lot of companies have done right over time you need to do a lot of projects that are focused with certain goals in mind but the the side effect of that is that you're ending up with data that's tied to some applications some systems some infrastructure whatever have you right and that goes the same with people process tech decisions right you've made certain decisions so there's a lot of tech debt and along with that comes in data debt right and that's how you end up with data silos so i hope that gives you some perspective of how this problem happens in the first place and maybe even some thoughts around how to overcome them so you can't really in my opinion run digital transformations as projects anymore you need to think of them very much like a product right that's going to live and breathe so when you're building a product you're building features and certain things on top of it but they're all aligned to a certain goal or a certain product right certain foundational thing what is that thing because data is not really an entity you can look at it as a part of an application or a team even needs to really come together yeah really really clear explanation here about how to how to overcome silos and that's why i truly believe that we need to create this ecosystem where data right can you know navigate through all the ecosystem and everyone can benefit from from data it's not like okay this is my data i will not share because we are basically you know closing the door of all the benefit that that i can can add value to all absolutely operations yeah and i'll just point out one last thing on that topic right uh the importance of processes when breaking down data silos a lot of the times people get very focused on the systems um but we forget about the business rules that are implemented by whether it's an automated process or a manual process right there's there's something happening that data is being processed when it's traveling from let's say one system or one particular part of the organization to another right we put so much focus on these systems because they're tangible things we don't think about the process and how that may need to change too much because a lot of the times data silos come up because as people we get very um cautious of not sharing data unless i have completed my job right i don't want to share something half built with chris or the the job is only half done i haven't gone through the entire process of processing that data and giving you the final outcome but what that's doing is it to your stakeholder it's not giving that full picture right um data should be an open entity inside a company right with privacy concerns and some of those standards and policies aside the access of the data should be an open thing in fact it reminds me of a situation i don't know how long ago that was or maybe i read it in a book or i read an article but the the founder of amazon right jeff bezos at one time wrote a um a memo inside his company earlier on and sent it to everybody and said well you need to open up apis to have people inside the company in other parts of the organization get access to the data and get access to the functionality that you're building because he did not want those silos so people were forced to do their work in such a way that at the end product whatever they design whatever they build it will be accessible to the rest of the company and it's such a great way to think about breaking down silos ahead of the time as opposed to building something and saying okay now how do i make it accessible right really really interesting and you know when when thinking on the terminal environment or or the ecosystem you know you got sales operation and the technical team and maintenance i.t and uh yeah there is as you may know terminal data is generated yeah you know heavily so it is critical that we got all this data share through all departments so we can have like a better decision making so it's really and it becomes very complex if you think about in that particular scenario right think about the privacy concerns that may be there when that data is traveling the security concerns uh what happens to data quality because as it's traveling it's collecting more and more attributes right along with it that's right um so think about even your own experience as walking into a terminal right traveling through the security gate getting your ticket validated walking over to the gate figuring out what you're going to do doing some other activities if you have time before you get on a plane so if you even think about that experience quite complex experience right so it only scratches the surface of how complex people's jobs are people like yourself yeah i can say that that quite quite many of uh of my colleagues will define terminals as a complex a complex operation but yeah i can say it's not only due to the nature of the operation but also due to the challenging times where we're also facing but not only that the maritime industry many others industries so absolutely and that's where policies come in right regulations and policy changes because as a business um if you're not aware of them what constraints you need to watch right it's not just up to the leadership right it's up to every single team even yourself when you're advising your clients if you're advising on the design and you're not taking that into consideration that won't help them so you have to be watching that data and watching um certain type of factors that are changing all around us awesome awesome and well we have talked about the the importance of data um why we should avoid cylos um but gunjan for a company that is not a data driving company and uh how should they start all these all this journey it's a great question actually chris it can be very overwhelming right to think about going from a zero to a hundred right you can't just say okay today i'm a data driven company let me think in terms of data collect all the data that i need and start using it to make decisions i think that's actually the wrong way to do it um the first thing you need is actually a vision right and in order to inform some of these conversations and help make it less overwhelming if you will at go emerald we've actually started a data driven workshop series um to cover some of these topics so every month sort of handling a little piece of it and helping our customers through that so as a starting point i can share some very very high level thoughts right that don't even begin to scratch the surface of some of the complexities that are around this but it would help bring the teams that step-by-step approach if you will how to start instituting that data-driven culture if you will right it's a culture that you're changing um being more aware first of all of how you currently make decisions is very important right are you already using certain types of facts and data as your bases where is that data coming from what are you actually relying on that would give you a good baseline right it would also in turn help you think about what assumptions and constraints you may have in place right taking that different point of view to say so i'm making this particular unsaid assumptions is that really true across the company or is this particular department making different assumptions than that other one because it would be very difficult to have that alignment conversation or even identify data that these two teams can use to work together if those assumptions and constraints are not aligned right in the decision making process and then when you look at the two things that i just mentioned being aware of how you make decisions and questioning your assumptions and constraints once you have done that you would get a really good sense of where you are as far as data maturity level is concerned in your company so i like to use two words here one is called data produce right and the other one is data use so every company is a data produced company right if you're selling something you're a data produced company but are you doing something with that data that'll make you a data use company once you've defined yourself as a data use company what is your goal and objective why do you even need the data because a lot of the times we get so hung up on um a mandate that some leader may come up with in a company right they may say well i want to make my company data driven company well why is that why do you even need data to make those decisions how will your customer benefit from this how will your company benefit how will your partners benefit as you said earlier how will the entire ecosystem benefit that vision needs to be really really very specific it's really just very crystal clear about what objectives you are marching towards great gunjan and we're almost reaching an end here but uh i would like to close uh with i would like to to hear your thoughts regarding this one and you know for me when evaluating uh the different level of automation something that i may see in the in the market is that you know sometimes customers are seeing that the neighbors are already automating you know and they you know they got this feeling that oh i need to automate as soon as possible and uh probably they will try to copy-paste the enable solution and i think that's that's that's a big mistake you know the baseline is to understand your way of working and what would be that the level of automation that will match your operational kpis you know and many other kpis so i can expect it's the same for you right on the digital transformation absolutely right there's no such thing as a copy paste right i mean the way that one retail company would use their data is very different from what the other company would use and that's all based on how are your customers thinking about it right they may be fighting over the same customer sometimes you may even be offering the same product but that doesn't mean that you are the same company if you were then every company under the sun in a particular industry would look exactly the same right um it's so much more as you said about the culture of the company how you work the the ways of working as you described um the customers that you're the experience if you will right is the right way to put it that you're trying to provide your customer the data strategy has to be very very aligned to that and digital transformation for that matter and the innovation strategy as well right all of these things are intertwined and that's where the complexity comes from but that's where we were talking about vision earlier so important for leaders to take accountability of what that vision needs to look like listen to other people in the company try to buil