I have covered my first couple of posts on this topic here (1, 2)
Coming to the fourth pillar of Strategic Alignment – Organizational flexibility is the most important to have and most difficult to ascertain. Whether a business or a group of individuals are ready to do something that they have never done before, is a lot of introspections. No offence meant, but not every leader is Captain Kirk, nor every business USS Enterprise. At the same time, isn’t flexibility at the heart of entrepreneurialism?
Nevertheless, what did I see in my experience? High inertia to change (But we have been doing it this way, and it works!), traditional ways of thinking (been there, done that!), skepticism (will it work?) and arrogance (what can this new kid on the block tell me that I don’t already know about running a business?)
Inertia and traditionalism are vices that cannot be sorted out in the short term. I always felt the need to know what I am up against. A little better. Even with a small firm, I liked figuring out where the funding is coming from. If the money guy wants you to generate returns yesterday, then you are in a big soup. Very recently, I heard about this new start up (a few guys running off from a fairly known name) where the Money guys have given them a 3 year window on returns. I have my reservations about the exact terms & conditions. But nevertheless, that’s a flexibility that you need to pull it off.
One of the biggest vice and virtue of youth is the need to break the rules. And those who play by the existing rules are not the rainmakers. What used to really bug me off was a reminder to stick to the old rules to set up a new business. My usual retort (in my head) used to be – Ok! So you know how it works! Why don’t you just send us a 10-step guide to building a 1bn dollar business? That will help me save time on thinking! BECAUSE THERE IS ANYWAYS NO GODDAMN POINT OF THINKING! ;)
I learnt to think politely later on! Waiting for crisis to drive a point home seemed to be the easiest way out! But then, business are not built on decisions taken during crisis!
Lesson: Look at who you’re going to work with, and under! Rule of thumb for start up – If you have too many guys who started off as the ground level guy and became Project Managers before becoming leaders, and have not taken a single weird decision in their life, are very unlikely to flexible. Almost every great leader CV has something zingoistic! Remedy for disaster – A “did my schooling from ABC (a known school” and “went to IIT and then IIM” and then worked for company A/B/C (all known brands) for x years (x>5). Whoops! You know that they have already lost their creativity!
Skepticism and Arrogance – Skepticism can be handled. Arrogance, cannot. Unless you are ready to fight fire with fire! Are you one of those people who, when pinned against the wall, can poke their nose into the poker’s eye before betting your life on why you think something is going to work! For skepticism, a thorough research is very important. That’s something that gets discounted when you are in a hurry. Young people like me always make the mistake of not having thought through all possible questions. We just find it too boring, and we ourselves are too arrogant. I know it. I can handle the questions. But vacuous answers increase the amount of skepticism.
Lessons learnt: Do your research well. And be ready to fight for it. Nothing comes easy. You have to be the bad guy at times!
Thursday, April 26, 2007
Tuesday, April 24, 2007
Analytics Start-Up Series - 2 of Many
I will continue with part 2 of the start up series and focus on the third part of the element wheel - New Product Design (Air)
New Product Design
What? By the time I had joined the team, we were still defining what we want to do, and what we don’t want to do. Analytics has come to connote not just data mining and predictive analytics, but even research analytics, product based analytics, dashboards, etc. We wanted to focus more on the marketing analytics, and that’s why we were MCoE.
However, the problem/uniqueness of our positioning was that we were focusing on a process driven analytics approach, while 90% of the listeners with different levels of analytics’ understanding had thought largely of product driven approach only. Even “SAS-skills” were “SAS” skills.
For whom? Moreover, we needed to decide which all verticals we will build our presence in. That’s tricky. Being small and new, you want to prove a point. You are ready for any project that comes your way. However, if you do your first project in healthcare with your key focus being FS, the next time you go to a client, you have a healthcare case study to talk about. If it’s an FS client, you neither want to own the case study, nor disown it. Boom!
Why? The bottomline for a sales guy remains – why would someone buy what you’re selling? Is there an identified need? Is it expressed? Would you need to educate the buyer? In the Indian market, for instance, Fractal Analytics, I think, has done a great job of educating the financial services sector about the need of and opportunities for analytics. There are similar examples elsewhere and in other industries too. Having said that, if we look at the analytics market today, the education is taken care of. The market does have an expressed need for analytics. If we take a closer look, the first industries to adopt analytics were financial services and telecom. And both these sectors loved keeping their data to themselves. They built strong in-house teams. However, things have changed in the last few years as firms have started engaging third party vendors (just as they adopted consulting/consultants as third party unbiased experts with a broader view) for analytics. But today, a lot of other sectors including Public Sector, Healthcare, etc. have emerged as buyers of analytics. Marketics, for instance, had more depth in FMCG than FS, given the ex-P&G background of its leadership team
Where? From a third party vendor point of view, almost everyone wants a piece of the US analytics market. The other markets have been slower to adopt analytics outsourcing. The other truth is the relatively crowded analytics vendor market in US. Net result, apart from some of the early movers like Fair Isaac, not a lot of vendors have been able to build a large scale. However, my MCoE stint taught me that there is a significant opportunity lying the Asian and European market as well, if you have the right connections, credibility and content.
Lessons learnt – Identify a market that you understand well, and where you have the credibility to sell. Sell only a bit, and understand it in depth, and avoid trying to be everything to everyone.
New Product Design
What? By the time I had joined the team, we were still defining what we want to do, and what we don’t want to do. Analytics has come to connote not just data mining and predictive analytics, but even research analytics, product based analytics, dashboards, etc. We wanted to focus more on the marketing analytics, and that’s why we were MCoE.
However, the problem/uniqueness of our positioning was that we were focusing on a process driven analytics approach, while 90% of the listeners with different levels of analytics’ understanding had thought largely of product driven approach only. Even “SAS-skills” were “SAS” skills.
For whom? Moreover, we needed to decide which all verticals we will build our presence in. That’s tricky. Being small and new, you want to prove a point. You are ready for any project that comes your way. However, if you do your first project in healthcare with your key focus being FS, the next time you go to a client, you have a healthcare case study to talk about. If it’s an FS client, you neither want to own the case study, nor disown it. Boom!
Why? The bottomline for a sales guy remains – why would someone buy what you’re selling? Is there an identified need? Is it expressed? Would you need to educate the buyer? In the Indian market, for instance, Fractal Analytics, I think, has done a great job of educating the financial services sector about the need of and opportunities for analytics. There are similar examples elsewhere and in other industries too. Having said that, if we look at the analytics market today, the education is taken care of. The market does have an expressed need for analytics. If we take a closer look, the first industries to adopt analytics were financial services and telecom. And both these sectors loved keeping their data to themselves. They built strong in-house teams. However, things have changed in the last few years as firms have started engaging third party vendors (just as they adopted consulting/consultants as third party unbiased experts with a broader view) for analytics. But today, a lot of other sectors including Public Sector, Healthcare, etc. have emerged as buyers of analytics. Marketics, for instance, had more depth in FMCG than FS, given the ex-P&G background of its leadership team
Where? From a third party vendor point of view, almost everyone wants a piece of the US analytics market. The other markets have been slower to adopt analytics outsourcing. The other truth is the relatively crowded analytics vendor market in US. Net result, apart from some of the early movers like Fair Isaac, not a lot of vendors have been able to build a large scale. However, my MCoE stint taught me that there is a significant opportunity lying the Asian and European market as well, if you have the right connections, credibility and content.
Lessons learnt – Identify a market that you understand well, and where you have the credibility to sell. Sell only a bit, and understand it in depth, and avoid trying to be everything to everyone.
Tuesday, April 17, 2007
Analytics Start-Up Series - 1 of Many
Yesterday, I was talking to one of my friends who wanted to get my perspective on what did I learn or not learn about starting an analytics company (having been a part of multiple start-up environments). That’s when I thought tt might be a good idea to pen down my thoughts on this.
Disclaimer: This applies to my understanding of a company which is doing offshore analytics.
I always looked at my learning along four dimensions
This post is going to be the first in a series of posts where I will write about my experiences.
A. Existing product portfolio
Context : The company already had a BI practice, a CRM practice, and a lot of analytics was already being done in different relationship pockets. To put it bluntly, every time a relationship needed someone with “SAS skills”, they hired one and put him/her on the relationship. No need to aggregate the “SAS skills”, (which is what analytics job postings have reduced the required analytics skill-sets to!). Additionally, tools like SAP and Oracle have their own analytically intelligent layers, and SAP and Oracle are separate practices within the organization. Imagine your plight when you’re talking to a client about analytics and she says – “Well! But that’s pretty similar to what you’re BI team talked about. They probably had a higher product focus, though!” And you start looking at the account manager, who has probably introduced every practice to the client (to grow the account). It was not our fault that we were the new baby on the block. Interestingly, the leadership had never thought of aggregating the knowledge lying here and there in the firm to have a solid ground from the beginning.
Lesson Learnt: If you’re going to cannibalize your existing product line, you need to be sure on what you are offering, why you are offering, and how will you work with the existing product lines.
B. Stakeholder Alignment
Context: In the organizational power play – strategic positioning can mean that you are the weakest (fresh out of the closet) player, or the strongest player (the whole company is looking at you). Usually, you are not stuck in the middle. If you are the strongest, the performance becomes extremely short term oriented. Stakeholders want to see quick wins, proof of concepts and a latent potential (as visible through a practice bursting at the seams!)
a) “Who’s with you?” - We realized pretty soon that very few important players have been sold the concept and its importance to the overall soon. The attitude towards the new practice ranged from “This is neat!” to “Oh! So we are wasting money on analytics this time”. To an extent, the varying levels of cynicism is expected in large organizations. The problem we faced where cynicism in the mind of decision makers/policy makers.
b) “Who gets the credit?” - Driving from my other experiences, analytics team can potentially be at direct conflict/synergy with another practice. For example, an offshore analytics center (analytics outsourcing) model can be a potential threat as well as support to analytics consulting. Analytics (platform independent) can be a threat to product driven analytics, but can be used to augment the nature of analytics as well.
c) “Who gets the money?” – Given that analytics is a horizontal solution and not specific to industry, revenue recognition is always a challenge. All the verticals stake claim to the analytics revenue, while analytics unit may have a separate revenue target. For instance, a 100MM target for Financial Services vertical will be achieved through products, services, analytics, implementation, etc. However, the 20MM analytics target will be achieved through a combination of work done across verticals- such as Financial Services, healthcare. Every dollar generated by analytics team will be claimed by the respective vertical. However, the effort devoted to sell analytics will be lower, because there is no specific FS-Analytics revenue target.
(...to be continued)
Disclaimer: This applies to my understanding of a company which is doing offshore analytics.
I always looked at my learning along four dimensions
This post is going to be the first in a series of posts where I will write about my experiences.
I am drawing largely from my first company experience here, which was with a very large Indian IT firm thinking of setting up an analytics practice. When I joined the team, Gayatri Balaji was leading the initiative, and she had Dhiraj Narang helping her. Me and Shivani Sohal joined her as part of our third training stint. Apart from Gayatri, the three of us were raw with no analytics background/experience.
Analytics, or Marketing Center of Excellence (MCoE) was a prized initiative of the company at that point. It was an attempt to move up the value chain by doing “intelligent” work (in the Business Intelligence way, not that the company was not doing any intelligent work!).
There are four set of challenges that we discovered –
A. Existing product portfolio
Context : The company already had a BI practice, a CRM practice, and a lot of analytics was already being done in different relationship pockets. To put it bluntly, every time a relationship needed someone with “SAS skills”, they hired one and put him/her on the relationship. No need to aggregate the “SAS skills”, (which is what analytics job postings have reduced the required analytics skill-sets to!). Additionally, tools like SAP and Oracle have their own analytically intelligent layers, and SAP and Oracle are separate practices within the organization. Imagine your plight when you’re talking to a client about analytics and she says – “Well! But that’s pretty similar to what you’re BI team talked about. They probably had a higher product focus, though!” And you start looking at the account manager, who has probably introduced every practice to the client (to grow the account). It was not our fault that we were the new baby on the block. Interestingly, the leadership had never thought of aggregating the knowledge lying here and there in the firm to have a solid ground from the beginning.
Lesson Learnt: If you’re going to cannibalize your existing product line, you need to be sure on what you are offering, why you are offering, and how will you work with the existing product lines.
B. Stakeholder Alignment
Context: In the organizational power play – strategic positioning can mean that you are the weakest (fresh out of the closet) player, or the strongest player (the whole company is looking at you). Usually, you are not stuck in the middle. If you are the strongest, the performance becomes extremely short term oriented. Stakeholders want to see quick wins, proof of concepts and a latent potential (as visible through a practice bursting at the seams!)
a) “Who’s with you?” - We realized pretty soon that very few important players have been sold the concept and its importance to the overall soon. The attitude towards the new practice ranged from “This is neat!” to “Oh! So we are wasting money on analytics this time”. To an extent, the varying levels of cynicism is expected in large organizations. The problem we faced where cynicism in the mind of decision makers/policy makers.
b) “Who gets the credit?” - Driving from my other experiences, analytics team can potentially be at direct conflict/synergy with another practice. For example, an offshore analytics center (analytics outsourcing) model can be a potential threat as well as support to analytics consulting. Analytics (platform independent) can be a threat to product driven analytics, but can be used to augment the nature of analytics as well.
c) “Who gets the money?” – Given that analytics is a horizontal solution and not specific to industry, revenue recognition is always a challenge. All the verticals stake claim to the analytics revenue, while analytics unit may have a separate revenue target. For instance, a 100MM target for Financial Services vertical will be achieved through products, services, analytics, implementation, etc. However, the 20MM analytics target will be achieved through a combination of work done across verticals- such as Financial Services, healthcare. Every dollar generated by analytics team will be claimed by the respective vertical. However, the effort devoted to sell analytics will be lower, because there is no specific FS-Analytics revenue target.
(...to be continued)
Friday, April 13, 2007
A weekend thought on analytics
I have often thought about what is the kind of analytics I want to do and tried to correlate it with the kind of analytics that companies are thinking of doing.
- I want to think of analytics as a key to strategy. Organizations want strategy to define the analytics required for the business.
- I want to do analytics to optimize social benefits. After all, what is policy but a goal programming issue! Policy makers are driven by soft objectives and non-economic intentions more than economic incentivization. They ignore data for convenience.
- Analytics can, potentially, be used for wealth allocation. Just as Activity Based Costing helps organizations decided the key contributors and key unproductive consumers of resources, good analytics in the social context can help us define how the resources should be reallocated.
- I want to do analytics on product development. I can see that organizations validate product ideas using analytics more often than analytics for coming up with ideas. Aren't there creative people who can think of random surveys already done by equally random agencies and come up with new product ideas?
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