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.

1. Strategic Alignment With Overall Business

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!).
However, that being said, what our small and inexperienced team (with the exception of Gayatri) soon realized is that its one thing to say that we want to do “this”, and another to align it to the overall business.

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.

Lesson Learnt: If you’re an outsider roped in to run a new business initiative, make sure that you understand the powerplay and relative buy-in. Understand the weak and strong points of everyone you’re compulsorily going to deal with. Equally important is to understand the relative aspirations that help you share, transfer credit of the work done in a politically correct manner. Sales is a tricky issue that we will touch separately later

(…to be continued)

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4 responses to this post.

  1. Posted by Anonymous on April 23, 2007 at 4:14 pm

    Very well written post on your perspective on the issue. Apart from the regular issues which any new practice would face in a big services organization, analytics has a peculiar problem of definition. Almost everyone has his/her own definition of analytics. You may say only predictive stuff is analytics whereas others may say any piece of data analyzed over a few dimensions is analytics. So, you are right about revenue recognition part. I know a few folks who have done extensive SAS stuff for Pharma cos in Indian Serv companies without having a clue as to what is analytics.. Is it that when you do statistics or when you do software code or when you do software code which does statistics ? & At the end of the day, the revenues earned from an average analytics engagement is not big enough to make the senior management of service companies sit up & think about a solution for this confusion.As far as the outsourced part of Analytics is concerned, I am of the opinion that Data/Business Analytics is best sold along with consulting engagements.. as a niche.. Selling it standalone as a service or selling it with BPO is not even as good as trying to sell it as an add-on to BI/CRM IT Service. Whats your take on this?Its interesting to think how adoption of a thing (calling it so for lack of a better term) like analytics happens.. I think CRM, BI, ERP would have faced the same scepticisms in their early years but then got pushed by product companies. Who in this domain looks like emerging as a clear market leader. FI or SAS. Waiting for your next post as I am a guy who worked in one of those CRM/BI practices & now with a top-3 3rd party offshore based analytics provider. :)- amit

    Reply

  2. Posted by Amit on April 24, 2007 at 5:53 am

    Amit sir! 1. The definition bit is something that I touched on the next post. And yes, that to me is one of the biggest pain points of analytics service providers. They are not sure what they want to do! MR companies do reporting better than them, and consulting companies do strategy better than them. Even product companies have quick turnaround, standard reporting and enterprise wide application. Analytics, the way 3rd party vendors have treated it, has become that small piece of modeling/data management work that is not explicitly getting covered. In that small a nice, well, I am not sure if there is sustained revenue. For me, if there is any kind of data leading to any kind of knowledge/insight, thats analytics. That, for me, rules out parts of research because its focused on evaluation – qualitative judgment based on someone else’s qualitative judgment. 2. And I agree. As long as you keep selling standalone, it will remain a small share of the pie. But then, i dont agree that you cannot sell it with BPO. I still think a company like WNS can pull it off if they think through it. 3. FI or SAS? Difficult question. FI is the intelligent part. but without SAS it would be nowhere! My point is that someone’s comfort/installation of SAS usually tells you if they will ever ever engage an analytics vendor (FI or otherwise!) 😉

    Reply

  3. Posted by Anonymous on May 2, 2007 at 2:44 pm

    so let me try & explain why I think a cross/up sell to existing BPO relationship is not a natural fit for Analytics. (disclaimer: coming from a guy who hasnt closed even a single $ of sale in his life, so take it with oodles of salt :P). Lets look at it from Customer (actual user of Analytics) viewpoint. Lets take an example of a customer focused organization (like a credit card company, what else). Processes like marketing campaign (outbound calling) or service calls (inbound calls) or claims processing (Txn processing) are easily outsourceable since – (1) processes have been standardised – everyone in an org knows who is responsible for sales targets or service levels or file transactions, etc & demand is regular & aggregated so one can think of a 3rd party provider (2) cost savings is important (3) Processes are clearly back office or front office – output doesnt affect your strategy directly – exec mgmt can afford some latency for these processes.If you evaluate a piece of analytics work (whether predictive modeling or other data analysis work) – (1) processes are very immature in nature & demand is sporadic & accountability unclear – who is actually responsible for a metric like Retention Rate of Customers – Product Manager or VP Marketing or Director Analytics? A Campaign Management executive might run multiple campaigns for multiple products throughout the year – but is he/she going to have enough bandwidth to – create enough pipeline of work for a vendor team; ensure that latency between vendor/customer doesnt impact the strategy/implementation level work; transfer some bit of business knowledge to the team ?? So on & so forth – similar arguements for a Pricing executive in an insurance company or supply chain planner in a retail company.(2) cost savings are important clearly(3) most “Knowledge Service” work/processess are kind of middle office or VP/MD/CEO’s office projects. Exec mgmt cant be comfortable outsourcing/offshoring such a process completely as it would take away a lot of fliexibility in adhoc analysis or quick turnaround projects.Lets look at it from Vendor viewpoint. Acc to me, there are 3 things important to a vendor – (1) Having an existing relationship (& consequently a Master Services Agreement sort of thing – which would facilitate the process of targeting right people within customer & take care of data compliance, etc)(2) Getting right data – being a BPO rather than a Systems Integrator doesnt make it any easier for me since all data resides in systems which are managed by another party(3) Size – BPO is about selling capacity. # of seats. Extremely competitive, commoditised & undifferentiated market. Analytics is exactly opposite. 1 analyst’s work – acted upon at the right time can produce wonderful returns for the customer. But you cant put that in a service contract.so my thinking says that delivery model is far from perfect for all such so-called knowledge based services (incl analytics). maybe the market needs a big bang success story or an institute like SEI (whose CMM model helped IT offshoring phenomena) which can layout the process in a standardised, templatised manner.I also tried to validate my thinking by looking around & seeing what vendors are selling analytics. Apparently, as a service offering, its only the independent analytics providers, pure play BPOs or BPO arms of IT firms. I could think of 2 reasons for that – 1) Analytics is sold to a line exec – someone like a CMO or CFO or VP – Risk. BPOs sell to these folks, not IT companies. Hence, from a selling standpoint, its logical to club the new offering under the BPO umbrella (without thinking much about strategic sense)2) BPO/KPO industry has more people from consulting background than IT. Selling analytics would come easier to them I guess :PA captive center is one environment which doesnt suffer from all of these problems. Hence, I would place my bets on captives to be the places where Knowledge based work would thrive in the long run rather than a 3rd party. 3rd party players (under the usual utilization % pressures) have cut rates for analytical assignments to such levels that the revenue numbers (# of seats * $/FTE/Annum) dont look inspiring enough for even themselves. & Anyways, challenging part of most assignments is – data preparation stage & model implementation. Since, these jobs are laborious & monotonous – service providers package these as main offering (at low prices obviously). But, this part of value chain should also soon disappear since there is some consolidation due in the products/tools serving analytical tasks space. Apart from the fact that its a private company, doesnt SAS make a good acquisition target for Oracle? & Perhaps, tools like SAS E-miner, Oracle ODM or Teradata Miner would make the data prep rigmorale in an analytics project redundant in next few versions of their’s.What say?- Amit

    Reply

  4. Posted by Amit on June 4, 2007 at 9:41 am

    Amit.. long delay in responding to your comment! While I agree with your evaluation of structural difficulties for BPOs in pulling it off, there are a few things that we should not forget -1. Analytics, like consulting, is extremely knowledge intensive. The problem right now is that most analytics service providers are trying to commoditize parts of analytics and consultatively sell the other parts. Under the same umbrella, its difficult. A Mckinsey, for instance, may not be charging a differential rate for PMO work as compared to run mof the mill market entry strategy. An IT company would have a much lower PMO rate than Mck.. but thats a different debate altogether. My point is – you are confusing the buyer by selling analytics that is cheap/inexpensive, and selling analytics that is expensive at the same time. 2. Captives – They have the problem of work variety/ career progression. Unlike a BPO where people evolve and hit their aspirational level of being a manager, handling 2-5-10-50 people in/across teams, in a captive, the extent of that evolution is much lower. Even managers and VPs are doing the same thing.Who will win? No-one. Right now, the buyer is winning with rates under pressure. Over a period of time, the 3rd party resources (at least someof them) move on to the buyer side. Alternatively, its quite possible that smart large organizations centralize their BI/Analytics requirements. One such 50 people deal can make or break a small KPO. But then.. there are too many ifs here, right now! 🙂

    Reply

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