 Welcome to the session called Lessons in Addressing Data Challenges while using OKRs for driving business outcomes and bringing customer centricity by our two speakers today, Ashish and Sujatha. Thank you. Welcome everyone. Again, very good evening, good afternoon and good morning for folks around the world. Like maybe introduce Ashish Mehdi Ratha and I have my colleague Sujatha Akrash here with me. We are part of V-Shell re-inageral practice and we are here to share some of our experiences in our journey of using OKRs. And this session is primarily focused more on the data side of the challenges that we have faced. Obviously you do have multiple challenges, but let's deep dive in into the data part in this session today. Again, a standard disclaimer from our organization. There's no financial projections in this session. This is just an experience report from our side. For those of you who may or may not be familiar with our organization, a quick sneak preview of our organization, the scale at which we operate, the customer base and the energy space that we are moving in. Moving on, I think just to begin, and before we deep dive into the data part of the challenges, just to set the context on why we are even talking about OKRs today. So I think today we are all seen in our organization. I'm sure all of you can relate. There are that we are at crossroads. We are at crossroads where we find many a times business moving in a certain direction and the IT teams moving in another direction. So there is always this dichotomy of how do you bring both the parties together and align them? How do you create that transparency, that focus, that clarity, so that business and IT are considered and work together as a single one team? And do not fall in the trap of us versus them rather are more focused and together focused on the customers really? And what outcomes we really want for those customers so that they can then do the job that they really want? So again, the context is that how do we get it all together? How do we bring the alignment together? How do we make sure that we are able to help them? Can I say help the business and the IT as a single unit and help them not just from a directional strategic execution perspective, but specifically in our case for this session, talk about the data informed data challenges that we see and how we can help them overcome those data challenges. I know this is a very short session, 20 minutes only, but we still wanted to introduce you quickly to the OKR concept itself for some of those who are not really familiar. So we talked about OKRs and OKRs stand for objective key to those. Nothing new here made popular by Google in 1999, obviously goes back to management by objectives by Peter Drucker in 1950s. But what you really are going after is whatever name we call it is really outcomes. But get to these outcomes. You really want to capture what are my objectives and that's where the word OKR comes from. So the objectives really are where you ask the question, what is the direction? Where do we really need to go? That question is the key question you ask when you start setting up objectives for the outcomes that you want to have. Next, for that objective, you really want to then have a set of key results and these key results help us to now understand how do I know that I'm getting there? And you already defined the objective, which is where do we need to go? But then the key results really help you to say, how do I know I'm getting there really? So those key results then help us to define the actual activities, the tasks, the initiatives. And that's where we find IT teams then come in play where they say, yeah, we now need to build a product with these features, with these feature sets which offers these benefits which lead to these outcomes at the end of the day. So that's a very quick summary, a quick example would be if you're a sales manager who wants to increase the sales of the product while increasing the revenue on the profit margins. That's a high level objective you would set up for your team. And now everybody in that team, whether it's our sales guy in the field or the IT team who's developing the product for that salesman, they're all completely aligned to that objective. And you could then have key results which could be, hey, I'm looking for increasing my signups from 2500 to 4000 in this quarter and every quarter thereafter. So that's a very actionable key result that you have. Another key result you could define is I want a conversion rate for anybody who comes to our landing page or our website. And actually trials our product. I want to increase that conversion rate, let's say from 15% to 30%. So again, that becomes a very actionable key result. And now the whole team is looking at that key result and is focused and aligned on that key result. That's a very short quick summary crash pose if you may call it on OKRs. Again, there are many success stories and challenges we have. But again, like I said, for this session, we want to focus on the data side of it. So I'll pass it on to my colleague Sujata to take it up from here. Thank you, Ashish. So could you please move on to the next slide? Yeah, so it might seem that OKR might be very easy to understand and align all the teams involved and you can really measure the key results easily. But when we started our journey, we encountered many challenges. Yeah, so the first and foremost challenge what we encountered was around the source of the data itself. The data that we wanted to collect was not really residing in a central repository. It was residing in multiple systems and in local repositories in some cases. So due to which the data authenticity was a great challenge. The second challenge was around the data accessibility. As I mentioned, as the data was residing in multiple systems and these multiple systems were managed by our business and some some of our partners, it wasn't easy for us to access this data seamlessly. The third challenge was around the lack of alignment itself, the alignment among all the teams or parties involved on various facets. So starting with the data requirement itself, their accountability or their roles and responsibilities and as well as the governance. The fourth challenge was around the interpretation, the way the OKRs were interpreted. So what we observed is the OKRs were being used by teams to measure the individual performances. And then they were just measured, but they were never measured nor tracked at defined intervals. So Ashish probably can move on to the next one. So let's go over some of the experiments we carried out to tackle these challenges in this slide. We tested with some of the options and they worked well, but of course not from day one. So after a few iterations, what we observed this, what the series of steps that I'm going to cover here as a first step, we held series of interactive workshops and awareness sessions with our business and all the suppliers involved and as well as our partners together to understand the various aspects of the key results measurement starting with the overall data requirements more holistically and the source of the data that is residing in more secure and reliable systems and the quality of the data itself. And then the second challenge, as I mentioned earlier, the data accessibility was a challenge. To tackle this, what we did is we formed a focus team and this focus team was provided with an adequate access such that they perform the analysis at required regular intervals. As a third step, we introduced lean governance which covered the ways of working and working agreements around various facets again, starting with the identification of the data parameters. When I say data parameters, they're nothing but as simple as monitoring the number of customer visits in a particular site or collating the number of incidents, etc. And once we define the parameters, the review or the verification of the data is very, very important and the completeness and correction validation is also equally important. The focus team that we had formed were expected to perform these review and validation of the data that has been collected. And last but not the least is to really track them at regular intervals because some of the key results can be measured on a monthly basis and some are on a quarterly basis. So that is something which we wanted to agree upon. The fourth step is to really agree on the joint reflection because teams reflecting in silos will not really help. So coming together and reflecting and understanding the key results that we have defined are really making any sense. Is there any improvement that we need to do and come out with a common action plan? So that is something which we introduced. And last but not the least is to publish all that you have measured and socialize these in the business sharing committee such that you can seek the decisions accordingly. And as you see, this is a cycle and it continues. And overall experience led us to reiterate the key lessons we learned in this is to start small. As I mentioned, since many multiple teams are involved and the data is residing in multiple systems, it is very, very important for you to define a simple objective to start with. Not really ending up defining too many objectives and key results that we encountered in our journey. But start with a simple objective. In our case, we defined a very simple objective as increase customer base by 5%. And the corresponding key results we identified were monitor the number of customer visits in that site and number of incidents collated on a periodic basis. So with that, we could test and learn. So it's always good to start small is what I would like to reiterate. And secondly, how a clear cut alignment among all the teams involved, be it the way you understand the data, the data that you would like to review and validate could be the publicizing these key results, the joint reflection. So all these practices are crucial for you to succeed to achieve the desired outcomes. As you see, this is a journey and it's an ongoing one. And of course, we have been able to share very, very few very specific reflections over here and happy to share more and more learnings as we go on. Yeah. So Debbie, how much time are we left with I think we have come to the end and if anybody is interested to know more about our experience you can always find us on these contacts. Yeah. It's about five minutes to run. And I noticed we have a question that's just come up for both of you. What will be the stretch target for KR, could it be in percentage? Okay, what from our experience, we have been able to start with only 5%. Yeah. And yeah, that is what we have been able to define now and we have been able to, we have been assessing the results as of today. But I would recommend don't really set the stringent target to start with, start small, but we started with 5% and which is something ongoing one. So that's what I would like to recommend. Ashish, would you like to add anything? Yeah, absolutely. I think if you're asking in general for an OKR, how much of a stretch in an OKR. So we do say that the objective has to be ambitious. And again, for a fresh start, we don't recommend a stretch target which you really know you cannot achieve and that would just be wishful thinking. So if you say, I'm going to triple my sales or I'm going to triple my customer base in this whatever one quarter or one year as your OKR, then you are set up for failure itself. So what we recommend is for a fresh start when you are starting this journey, don't have very high stretch targets, but definitely the objective is where you're looking at setting up a goal and that goal has to be ambitious. So that when you are reviewing those OKRs, you are able to then refresh it and say, hey, this is either impossible for us to achieve or we may achieve 60% of it by the end of the let's say the calendar year. And that itself may be what is a good outcome leading to the good outcome at the end of the day for your business. Again, just like in any other new introduction, it is OKR is also a lot of change management built into it. So you really want to introduce this slowly because it includes a lot of activity in terms of getting people to structure the right OKRs. It's very easy, the simple, hey, I can write three bullet points and I'm done, but believe us that it is very important to structure the right OKRs. Otherwise, you will either have too many, too complex or impossible to meet, right. So you may want to add some more. Absolutely. Absolutely. And the practice that I recommended starts small because every experience is going to be unique. There is no hard and fast rule that you have to start with certain target. So we strongly recommend understand what object you would like to achieve the purpose behind that and what are the key results. It could be as simple as monitoring your customer transactions or could be it's as simple as number of incidents in that particular flight. Like I was mentioning in one of the experiment that we carried out, right. So start small. So that is what I would like to recommend and reflect on a quarterly basis. Don't really wait until the end of the year or so and end up having too many key results also. So the thumb rule is one objective, three to five key results only, not more than that. So that also we took a very smallest step to have only two key results for only simple objective like I was mentioning. Lots more questions coming up for our speakers. What I'll do for both of you is take one more question and then take the rest of the questions with you across onto the Hangout Area where you can spend 15, 20 minutes answering people's questions. So the next question we have is which tools do you use or prefer for OKR management and tracking. Okay, as we had started our journey, we made use of the program management office, a team which is available and we also started publishing the business line specific dashboards so which was built in-house. So there is no industry-wide recognized tool as such, which I am aware of, but that was one of the approach that we carried out. So wherein we had come out with a mechanism to really communicate which were those key results which are coming directly from the R-Wide tools which can be populated and automated and already made available in the program management dashboard. So that was an approach taken, but happy to share details around that. How did we approach? How are we communicating with our PMO team who are publishing internally on a fortnightly basis. So that's something happy to share that experience. Fabulous. So I think we've got time for one more. Any other examples of OKRs and what has been, what has been duration it has been used? So the duration we picked up was six months only to pilot it because in one of the example we piloted was not at a team level but more of a strategy initiative that was held up at a senior leadership team in which we wanted to track the revenue tracking at various markets in a specific region. So in which what we were tracking is the overall number of the increment in the loyalty customer. How can we improve the customer satisfaction was the objective across the specific region that we had identified. So in which the corresponding key results were the number of loyal customers. In a specified duration so the measurement was done on a quarterly basis and the reflection happened upon completion of two quarters. So that was one classic example I would like to call out. The reason I'm calling out this example is the OKR implementation started not at the bottom up approach but top down approach in our experience because once the leaders are recognizing the significance of OKRs the implementation will also I would say it's more easier than really starting starting at the bottom level or a ground level. So we were fortunate to experience that and that was one example I would like to call out. There are several other examples which we can share but might not be covering all the aspects of people are looking for. As I mentioned we have just begun this journey and if they fit relevant happy to share more. Thank you so much for joining us today. It's our pleasure.