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)