 this is Sonali. Thank you all for coming out some time for attending episode five of Meeks Academy, Business Excellence Mentoring and Coaching. Today's episode is on data intelligence for business excellence. To all the attendees out there, please type in any questions you might have in the Q&A section and we'll try to answer as many as possible at the end of the session. I would now like to welcome our speaker, Mr. Gaurav Mariah, Chairman and Founder of the Franchise India Group. A very warm welcome to you. Thank you Sonali and welcome friends and welcome to another edition with the Business Excellence Academy. This is an initiative by Business Excellence which is a part of Franchise India Group where every week on Saturday we talk about a particular subject part of our business excellence series and we talk about how you can implement those strategies in your businesses to grow your business or improve your business. Our endeavor at Franchise India and Business Access to help especially small businesses and startups to go to the next level. Business Access actually is an organization set up for three things. One, obviously we help companies to raise capital. Second, we work with them on developing their growth strategy and third, in some cases we would also do their exit planning if they're looking to exit the business. So we'll make it very interactive so it's about 30 minutes of series which I would discuss on today's data intelligence and I like to have many questions from you to use the Q&A box to ask any questions at the last five or seven minutes. I'll try to take as many questions you need to. So today's topic is actually about data intelligence and that's a very, very important aspect now for all businesses and especially if you look at small and early stage businesses they don't have any department called data analysis. This would really run into the founders themselves or owners themselves and they would have to really work on that and it's not on the priority list for them. So which means that they would continue to collect a lot of data which is part of anywhere our organizational cycles now because we are in a digital world so almost everything has a lot of touch points and a lot of touch points that get recorded but we don't really have any conscious effort done towards understanding the intelligence out of it and I know organization even the largest organizations are not putting that focus. Even look at what has happened in the current COVID period. We had a full cycle of one year for a COVID which was running in India and nobody, even the government of India, didn't put any kind of analytics to understand the second wave and how big it can be and so on and so forth. Now they're doing it, now everybody's understood the importance of data so almost all educational institutes of India are putting a lot of data, a lot of research organizations are putting a lot of data. So a lot of that is going on now. So we are bringing in predictability of the third wave and the fourth wave, the preparations would be required and so on and so forth. But other countries if you look at Singapore and other countries really have done this in the first wave itself. They started working on a lot of data points to really understand what is going to be the impact of what is coming up under this and if you cannot do this currently in your businesses it becomes even more difficult to sustain your businesses for future. So I would strongly insist that really put some kind of a conscious focus on understanding your data, understanding what the business is telling you, what is your organization telling you and so on and so forth. And so you're able to make your organization much more smarter to handle the issues and future challenges which it can really bring in. So what are we going to cover today? I'll cover five different topics. One, we will understand the need of data intelligence, why we need that today more than ever. Second, we'll understand the decision making process, how decision should be done in organization or how they are done and how this can really impact your decisions. Third, what is your data cycle, how the data should be collected and then we'll understand the larger business intelligence because end of the day there's so much of data which is available now, not everything is on use to me and you have to really bring in objectivity, what do you need to really hear from the data? What do you want from that answer from that? I think that's very, very important otherwise these are too much on these days and this whole data space has become very, very big and it's becoming even more confusing and you need to be very, very objective in terms of what kind of business intelligence you want from the data and five steps last point would be the five steps how to implement that. So let's get started, understand the need first. What is the need of having data intelligence in place? Any organization needs to take an effective and timely decision, that's very, very important now and if you're not effective or you're not on time you will either miss the opportunity or you will lose the customer. So it's very important at this stage to organizations for really to understand and forecast demand like for example current times if you look at this very, very challenging, how do you really forecast demand especially for manufacturing organizations? I'm seeing this a lot of big problems going on because they do not able to predict their demand cycles which is happening. A lot of look at auto companies they were slow, they stopped their production and then this thing started reviving, they had a good Q3 and Q3 was good and Q4, Q5 was looking very good and they start ramping up the production and again we come down to this situation. So a lot of companies are into this huge issue of how they can really bring in what I call demand forecast. What kind of demand we would see in times to come and how the data can tell us that this is going to happen and this is very, very important. Second, which is always a trigger point where companies start looking at going into their data intelligence is when they have seen the consumer churn or a consumer iteration like with most of the telecom companies when they started getting from another thing earlier there were no policy of you can shift from one subscriber organization to another brand and as this guideline came in and people started seeing moving from the entire thing and companies got into action and they started putting a lot of understanding, sampling the customer, going out and reaching to the customer and say why are you shifting and things like that and that's very difficult at that time because your churn cycle has already begun and even if you go out and sample thousand people it not tell you what is happening largely in your subscriber base because your subscriber base of millions and millions and what kind of size can tell you why the people are so much shifting outside and that is actually not the best time you really should start your data understanding or data intelligence because you should do much before because when the churn cycle really starts it's very difficult at that time but most of the companies would really do it at a stage when they have a larger attrition happening of their customer they are losing customer faster than they know and that is the time they would start putting up that another area which is becoming more and more important is to understand what other value-added products or services you will be able to give to the same customer and customer is telling you a lot of things but we're not catching we're just trying to deliver but not hearing them out and these days if you look at what is going around us almost everything is delivered to our home and most of the time they come and just deliver but they don't really capture anything what you were looking at what else you were looking at and things like there is a company which was actually formed by reliance called rescue you know it came from the need of the customer base so reliance digital used to be the large umbrella brand and they used to be in consumer electronics and they used to go out and put appliances in people's home later they found that the inefficiencies because they used to sell the appliance I would say they sell a samsung tv and a samsung guy would come from there and go and fit the tv because this lag was big time because I made a decision to buy from reliance digital today and samsung came after three days so customer was not happy so reliance started taking that responsibility also additionally that they would go out and and fulfill this requirement and actually do the fulfillment on the behalf of the samsung which obviously brought the better efficiencies they were able to deliver much much faster and then they really went to when they went to homes and they actually started fitting it for the customer the customer started asking about other appliances they have in the house and average home have many different brands and different service points you know you have small appliances big appliances you have other gadgets and you need a different service provider for that and that's where reliance really saw an opportunity that average home would have maybe 50 different brands and it is impossible for them to really go out and take service from different OEMs if there can be a company which can come from a valuation of reliance digital called rescue which can go and address that need and that's how this was multi-brand service outfit which was created so it really came from what customer was telling you so sometimes a lot of value-added products or services really can come in also it is very useful when you're scaling up data intelligence very important before you scale because sale is a very very important and very crucial decision in companies when they really want to ramp up and go up they need to really put that emphasis you need to really engage a strong research team which can work with you at that stage before unless and until you are absolutely convinced on why you want to do that I'll give you an example I'm consulting a company which is actually a 100 year plus tea gardening company so they were one of the finest exporters of teas to the world and they found a particular gap that they had a product which they just launched is called the black tea product and they felt that Indians don't drink black tea because they feel that it's very bitter the normal tea which you get which is a ctc tea you get is very bitter and they launched a product which can be had without having a milk now this is very clearly an opportunity case they have found but it needed a lot of other research points and why would people shift what is the compelling reason why they would shift from the conventional tea which is now actually a habit to everybody people have grown up on that they don't even know that there is a other option which is relevant what is the compelling reason why they shift well we saw in very clearly in green tea when green tea was launched it was not the best taste people liked it but was purely a health quotient which triggered people to shift from there so all these are very important when you really want to really scale or get into the next level you need to really go about and see the the kind of preferences customer is telling you another thing which which is very important and when people look at using data intelligence is then when they are looking for a large part of their growth cycle and growth comes from three things you know only three things which I would understand in my consulting experience if you want to really grow your enterprise only three areas you need to focus one is new product new channel and new markets these are three things which are very important so how do you really use your data intelligence to define new products which you have what is a new channel you can use you're delivering customer to through this channel can you go it from this channel also is your data telling you you can add to certain more convenience to the customer like a lot of things are now becoming direct to home direct to consumer businesses and third is what are the new markets which you have not explored you can do that so this is what the need part of it and I also also have to define you know there are three cycles to me in the in the whole data intelligence one is the data itself where it is coming from second is the information it is giving you and third what can be knowledge draw you can do out of that what kind of knowledge you can really get out of that information which is important actually you process the knowledge the data and information are just about really cyclic in order in doing it now a lot of you know companies have really created many many ideas out of that I'll give you example there is a company I was advising and I met the founder of Swiggy Swiggy is a very household name for home deliveries and they really started a dark kitchen the dark FMCG business in in Gurgaon and started testing it why because then they were doing deliveries in Gurgaon and these were late night deliveries people started asking a lot of FMCG products for them a lot of young people and a lot of other people asking for cigarettes and other things in the late night and there's nothing which is available at that time so they realized that an order especially in the late year when the supermarkets and your grocery stores or convenience stores are shut at that time people also needed a lot of FMCG to be delivered and they had the platform because they were doing late night deliveries for food and they started thinking that can we do this piece also now they started that pilot pilot was not so successful they didn't go forward on that because the the sample size or the ask was not big enough which means that they were there was a demand but demand was so small that it cannot be implemented across board I remember that when this first saw this as an opportunity they thought that they would probably go and put up these 2000 dark FMCG stores where they would do the fulfillment of basic staples and basic things and and then later they dropped the idea because it was not sizable it might be an indicative of one particular market telling you some indications but it cannot be generalized overall as an opportunity and then say they dropped it so they did a pilot they opened up a couple of stores of that nature but they didn't scale it up after seeing this early results were not very encouraging for them to do that now let's get into the second part of my discussion is what is the decision making process at what levels different decisions are taken on the data what data tells you and how you do that first is very operational decisions which are normally done at the point of a sales cycle right which is the almost front-ending teams would take that decision which means discounting it can be many other things which really comes from your data what customer is looking at and also maybe comparing with your competition you took this operational decision these are normally short term decisions taken by very very operational hands-on teams while obviously it will come strategic from the the top management but it's normally those decisions taken second are more tactical decisions which are which are designed for your promotion cycles you have a three-month cycle or a six-month cycles what you want to do or a new product launch cycles these are very clearly decisions on that and then the third decision which are more strategic which are long-term decisions are normally done when you have even a complete innovation of a product to be done or an absolute change of strategy or you want to shift from a you know offline to an online space or vice versa and things of that these are decisions which should be very very compelling and come from a very long-term viewpoint on that now let's get into the third part which to me is a data cycle you know what is a data cycle and how you really get this data historically there are two ways which we would really read the data one is through expert viewpoint expert viewpoint means that you have every single thing which happens in your organization there is a process lead so your sales head would tell you what is happening in sales and what he's hearing from a market and things of that so the or you can have even an expert from outside a consulting firm or a research firm and they would give you some kind of a opinion on which is very expert opinion somebody who belongs to that domain would give you that opinion second is actually what is your organizational knowledge base which means that at every point of your organization it can be different departments you capturing a lot of sense and you combine all that which through a data mining and get that expertise so one is a very data centric capability and second is very expert viewpoint on that and both has advantages and disadvantages when you are working purely on data then that's advantages that you're not really depending on somebody's viewpoint you are actually reading the data a lot of times actually business owners take decision on the expert side they don't really read the data and data might be telling you something else and the expert has his own viewpoint to tell you what he feels would be there so but if you look at only data and you don't look at expert the data can be purely historical it cannot predict sometimes the future it is very historical in nature so you need to really understand that it might give you what is being done in the business so far but it not tell you what is there but with expert you obviously can also find out what is going to be the future because they can have some kind of a trends which they can really capture so I would always try to mix these two I will try to mix these two options hear the experts what they're telling pocket there don't make opinions on that and also hear from the data what is telling and then try to make a combination of that and that would give you a little bit of what I call business intelligence which is my next point how do you really build a business intelligence from there what do you want to know from this data and what is the information you are seeking the first information to me would be your product preferences how the consumer is making the product or a service preferences with you it can be price it can be overall product relevance and these are very important points you know every boardroom has a brilliant idea that oh let's reduce the price by this and there would be a larger audience to take that sometimes it is not true in my company in a service business we were offering one one of our services at X price and I asked my senior team and say what should we do and they said let's drop the price because of this whatever the covid is going on let's drop the price and we'll get customers and and and I asked them is this only a decision for people not to take it because they cannot have affordability issue or we have only overall shrunk the market is the market itself is shrunk and because it shrunk we are giving the reason that we should grow the price down but actually it might be lesser customer which are willing to pay the same or more price for what needs to be done so you have to be really intelligent why you want to take that decision sometimes the overall market has shrunk but the demand of your loyal customers or people have that thing they are paying they are actually happy to pay you more because they want to really get that service done so it will not be like for restaurants when they open partially in the covid period almost every restaurant was trying to sell cheap to encourage people to do that actually it was wrong strategy and I actually did a webinar and and educated people that is a wrong strategy because everybody who's stepping out in the risk to come into your restaurant and eat is willing to pay you the best price and and he also appreciates that you are also underperforming and would not mind that you are while you cannot overcharge but you can charge the right price there is no way you should at that stage discount and create an excitement for people to just come out and risk to have a cheaper burger or something like that so one has to really see how do you really what are you trying to understand from what your data is telling second is your customer acquisition life cycle how your customer is acquired and and how the fulfillment is done so all that piece is and needs to be understood how you can build a better efficiencies consumer demographics like for example I was talking to one of our clients is actually based out of Middle East and they have operations in South India it's a children fashion company and they have stores only in certain part of South India which is largely Kerala they have stores and their online is telling a very different strategy is telling that the maximum demand is coming from markets like East and up North and so forth so when I asked the chairman of the company and said look what is your strategy for growth from an operational viewpoint he was very comfortable in doing South India but the indications of what people are making preferences on especially for online is coming from other markets not coming so much from the market he was operational now so this is can be a different strategy you might have an online a different strategy and for your offline business a different strategy because they both are different operational design sets and you can probably go and market yourself more online in the eastern and the northern markets where you're getting more demand and better conversion cycles are happening your your conversion ratios are better and maybe continue to have your retail brick and mortar strategy more concentrated on the south then a lot of things other than that we should really ask from data is how do you build better supply chain efficiency how do we save cost and time how do you boost productivity productivity is very very important and especially businesses which are non technology defining productivity is is a big challenge what do you really expect from from your workforce what kind of productivity they can do and especially in these times where a lot of them are working from home and things of that nature productivity becomes a very important aspect also understanding different needs a consumer would have and it might be shifting and significantly you might not know because you're you don't have any kind of sales dip you feel that the sales is still growing and robust that doesn't mean that consumer is continuing to enjoy the same kind of offering which you have it might have already have shifted but because there was no alternative available they are sticking with you so one has to be very conscious a lot of times with these we see sales numbers as an indicative to the consumer preferences answer is no customer might have shifted already but he's not really seen moving out of your sales function because there is no alternative at this being presented so as the alternative would be presented there will be complete shift off so therefore has happened to a lot of businesses which suddenly go out of business because they didn't understand that the customer was already not there it was waiting for an alternative to be driven and how do you really also build a transparency and relationship deeper relationship with your customer base how do you bring predictability to read the future as I said how do you are ready for future collaborations you might product might need something else tomorrow which you currently don't have capability you might have to collaborate with somebody else so all these things help you to make much better and faster decision making in the business now let's go to the last part of my today's presentation how do you put the five steps of putting data intelligence into your business first step is integrate your data understand the source understand the size you have got the simple size you've got and what kind of substance you get we call the triple s so i source size and substance how do you get what kind of insights you are getting out of that what is the kind of innovation is expected in whatever you want to change and can be small innovation which you want to really implement and how would you integrate within your organization that's very very important aspect this is before even you have started making any kind of this is just about integrating your data and understanding your data then this data gets into the actionable intelligence how do you really put this into action i call the four fits which are very important for any decision of your business which you want to take put this four fits into place all four fits are very important to run through strategic fit financial fit operational fit and marketing fit you want to make this action because you read this piece is it going to be a financially viable for you to take that is it a right call at this moment for you to make that additional investment to maybe produce a new product or change the strategy or change your channel whatever you want to do which data is telling you is it a right financial decision is it a right operational decision because it might burden your current operational structure you operationally you cannot manage that decision which you want to really bring in is it something which can come from the same marketing bandwidth or approach you have or the consumer would see from the same perspective coming from you and is it strategic for the organization to take that call sometimes the study call is so big that you have to take some major financial calls also because it is very strategic for you to that so first is understand data integration second is how do you build what i call actionable intelligence and then third goes into a little bit of a competitive and intelligence you need to also understand your competition and competition today is direct and indirect competition how do you really build your competitive intelligence on that how do you understand from the mistakes of your competition what they have done you don't want to do how do you create a differentiator then the your competition or understanding your core core value system what you need to do and sometime your competition is large enough you know and there is no way you can compete on all points then you need to really find your core competence and say i would do this best and stick to that part of entirely and leave aside everything i like the company called ISB ISB was a consumer electronic company still very strong as an organization and and they also had temptation like a lot of other companies like BPL and and video con and other companies to become a full-blown appliance company and get into all appliances and and and most of these companies on Eda and everybody else was actually trying to get into almost everything and now you look at it almost everybody is out of business they all are out of business and i have to be still strong because they were very clearly driven from their core competence and they were they were very very strong on that similarly voltas voltas were very strong on their core competence and they still as a strong company on that and a lot of other companies which were came in in this place got lost and they lost their competence they were actually doing everything but they didn't have a leadership in any of the of the pieces which is which is there so understand your competition the fourth point is understand real time visibility and insights don't lose even if you have that continue to check what the signals are coming in i call the test and measure anytime you really implement any decision which comes from your data understanding or your business intelligence if you if you put that decision go and test and measure because if you test and measure you will be able to manage things better you cannot manage what you cannot measure that's very very important and that's would be your very important aspect and the fifth point is once you have made a some kind of a strong decision or you know any kind of innovation which is implemented do a incremental improvement continuously keep reading the data what is it telling you if it giving good science keep doing your incremental improvement incremental improvement would would put the whole flow chart in a structure that you will continue to grow as an organization and improve your efficiencies and and your you know delivery to better deliver to customers so data and business analytics is the real muscle of delivering what i call operational and business excellence so this was a topic for today i hope that these points which you've got i have covered about five different points which is the overall need uh decision making process overall data cycle uh business intelligence what you want from the data and fifth is how do you really implement uh this so what do you sonali for any questions if you have i will be happy to take that thank you so much for another wonderful and insightful session for all our attendees uh we do have quite a few questions lined up with us and i would like to take up the first one so the first question is what kind of data points should i be looking at for leveraging my data i come from a retail business background you know so if you are in retail retail tells you a lot of data points uh again go back to the same thing data information and knowledge uh data points would be what is selling how much which SKU is selling what needs to be done the in the information you will draw on that is what is customer basket looks like how much they are paying to buy uh what is the average buying cycle who's buying what age group they are coming you know so the whole average basket size average price side how it is improving growing not growing all these are what i call uh this and knowledge you would draw on that is uh is more important to me you know which would be really about understanding uh you know what was the conversion ratio which you were getting and how you can improve that conversion ratio which means that footfall to conversion what is happening uh then average conversion to improving or ticket value what ticket value is a benchmark from from a market say the other competition is doing 600 rupees and you're doing 400 but where are you not doing that it's because you don't have required SKU or the offering or the uh you know any kind of a structure so all these are are this business uh this would create a knowledge base this would create what i call action actionable intelligence uh information would you would draw from the data and data is just about you know what has sold in the in the place and when it was sold who made a purchase decision to buy what they want to buy that right uh the next question is is it smart to invest in a data intelligence team at this time we are trying to sustain our employees but are struggling with uh with the same because of the second wave of covid i'm very interested in investing in a data or a business analytics team but not sure if that should be a priority at this stage it should be a priority rather it should be very big priority today i mean i know i'm not sure that you want to hire somebody from outside i would say it is a priority for you to invest your time into this it's not necessarily that you have to hire somebody uh to do that but and especially for small businesses you don't really need to hire you need to prioritize you need to prioritize it should be one of the top uh agendas for you to really have that and also put systems to really get the right logical data otherwise uh you get opinions you know and that's not something which again go back to what i was trying to explain you get expert viewpoints quite a bit uh everybody has a viewpoint on things which is good because they have some understanding below they're in market uh but it is backed by data so unless and until i would mix these two things together decisions should not be taken sure uh the next question i have is what is the future of real estate data analytics who all are the buyers of such analytics a lot of them i mean real estate so obviously it is a huge huge work going on and with all the major uh real estate advisory firms uh uh have a lot of uh you know investment good ones are obviously the jls and cdres and likes of them they do some i also personally because i have a real estate investment company for remax but i actually go out and read them more because i feel that they've they've done some some really good work in in terms of their forecasts and uh and you know their market behaviors and so almost every month they would create a lot of these reports for the for the industry and a lot of other companies are also there and i think mature developers today are investing a lot on doing it even to create their offering what they want to do because it's now becoming very very difficult uh different products are available in the market uh a particular site would you choose it for doing value home or you want to do a premium housing you want to do luxury uh in these are very important decisions and it's not really about the what would be just required because the project has to run for next four five years and you need to really see that the project would have continuous demand for next four five years and things would change in three to four years so it's actually analytic of uh strong data is actually a it's a very important need and it's a large investment projects uh it would need a much in uh depth of uh understanding and a lot of people have done mistakes and if you really see the lot of developers who've gone wrong is not because they don't have ability to sell or they were not aggressive or whatever it was the wrong choice of project at the timing was wrong and they were not able to sustain it look at a group called JP in Noida which invested so much in in creating those kind of possibilities invested into creating even a formula track which was 2000 crore uh in the predictability that it would create a lot of demand around it and that didn't happen so that money was not even recovered so it's a it's a wrong decision sometimes you put it back to buy uh understanding is able to create that kind of a demand it would create a an opportunity for a or a or a place where people would really buy homes because they want to be in a sports city like that and I mean he thought very Dubai centric approach Dubai has done this many times and because it's attracts tourists and people from all over the world which Noida is not attracting so it using a strategy of Dubai to Noida is is wrong and Noida is a end consumer market and he wants to be close to where he works and lives not for living for leisure versus in Dubai you can really have a second home or a third home in Dubai and you will take a leisure decision then taking a decision so so so a lot of things can go wrong with people when they don't really hear what what the market is telling them sure sir the next question is not specific to our topic of the day but I would still like to take it up the question is my son is 17 years old and he wants to do bbn wants to become an entrepreneur in the future can he attend any sessions held by you sure sure please anytime and this is the best time for them to attend that rather uh they should encourage them to be doing their you know entrepreneur journey as young as possible and that's what is very important and I feel that the young people from age of 14 15 to about 20 they are the best time to really conceive their startup ideas they're the best time to really nurture entrepreneurship because absolutely best time to do that and that's what become even more younger and and I was actually in oxford in you for a visit and and they told showed me a bmw has set up a lab there which is innovation lab in there and and this was kids are 13 14 were working on that because they said the next level of startup ideas innovations would come from this age group and bmw actually sponsored that piece for them for looking at the next level of creativity in mobility and that was the whole project and and and that's what is happening if you really see the the kind of ideas people are discovering these days are coming from absolutely you know fresh thinking and and fresh possibilities and and problem solving which sometimes in a later age like at my age it becomes very orthodox thinking you know well we can do all these talks and share our good viewpoints and and our numbers but really speaking in our businesses sometimes at my age I am a roadblock for for a fresh thinking the young people have much better thinking capability. Another question on similar lines is to get into a career in data analytics is it really required to have a technical or IT knowledge and skills according to you? You obviously IT knowledge I would not use the word I would say IT tools tools are very important because data is becoming bigger and bigger in in any form you cannot manage that but there are many tools available there are many many tools available to churn your data understand your data you need to choose very carefully which stage of business you are in and there are lots tools for small businesses which are available which are very good tools for you to really understand and draw a little insight but before you even start drawing and using the tool and then what is your ask is very important and that should be simple you know what you are really trying to ask is very important and stay very focused on that rest is easy rest is easy you know you know what you need to do that and that's what to me is very important so how do you really what is your ask is more important and the last question I would like to take up is how data intelligence works to sustain business excellence for long periods of time that is pretty much the gist of the whole session but anything you would like to add up to that sorry I missed your point question how data intelligence works to sustain business excellence for long periods of time yeah so this is what the whole session as I said is completely on that I mean how do really uh but essentially to make your future ready that's something which I would say is is the need of uh data analysis if it if can tell you that what is going to be future lies for you and how you can be adaptable to that future nimble to be that future and change it accordingly and stay honest to what you are like reliance has changed their strategy of energy because they feel the energy itself would change you know what would be a traditional fuel which would be a play important or the new energy would play a role so the transition would be easy now because they've clearly understood the next 20 years is is is transformation and and they would go out and look at almost all possibilities of next energy cycles it can be biofuels and it can be solar it can be any other thing possibly which needs to be done electric is any way with future for for going in different general energy so all these energies you will see these companies would would quickly adapt to and and that's what they are doing Adani just made a big investment in acquiring Bharti's assets in in renewable energy and clearly the transformation you can see how how companies are thinking and they're moving towards that so you also have to be really future ready and and and today good part is that you can really secure their data earlier days to get the data was impossible you know how do you really get to understand what your customer is trying to tell you today is simple while you have to cut a lot of noise also because a lot of noise is it's not true and and that's where you need to be really connected with your customer to understand what they're telling you sure sir so with this I would just like to wrap up our Q&A session thank you so much Gaurab sir for once again answering all the questions very patiently anything you would like to say in the end no thank you very much thanks for joining another session of mine it is your valuable time you take out so I thank you for for coming over and keep sharing your thought process anything you want from us to really bring in next time while we have a calendar to bring in a different topic every time on business excellence this is second series I'm doing I did one more series earlier which is invest scale exit and value your business that's also on on our Business X Facebook channel so if you want to refer anytime anything on that is all available it's all on the internet so thank you very much thanks for coming in and if you are looking to scale your business or raising capital or looking for a exit planning please reach out to Sonali and her business looks after that part of the business so if you any need you have please reach out to her and she and her team would be able to find right answers for you thank you very much thank you so much sir and thank you to all our attendees we really hope you were able to add some value to your lives through the session we'll see you next Saturday at 11 a.m. with another session in our BX Academy series and if you have any questions any concerns or if you want the recording of any of our previous sessions or this session please feel free to reach out to me and I'll be very happy to help you thank you so much