Follow Datanami:
April 5, 2012

VC Sheds Light on Data-Driven Future

Datanami Staff

Norwest Venture Partners currently manages somewhere in the neighborhood of $1.2 billion in capital.

Over the course of its 50 year history, it’s kicked funds to over 500 companies. The firm currently carries 75 companies, almost all of which are focused on data-driven technologies for IT management and select verticals, including energy and healthcare.

For those who follow big data news, Norwest might strike a familiar chord because of some of the companies it has its paws on. Among notable investments in big data technologies are 1010data, Hadapt, Avere, and Apigee.

According to Sergio Monsalve, a partner with Norwest, these are the first in a new string of startups that could help manage the next generation of big data tools.

Monslave says their focus on new investments revolves around four themes, which are all related to data. He says that of all the markets, financial services seems to have the most traction and captures the kind of market share he says he needs to see to consider funding.

In terms of eCommerce, the Norwest Venture partner says that he is most interested in how the proliferation of data can create a “better consumer”  by leveraging data so customers can actually make better decisions about consuming products.

In something of a surprising statement, Monsalve said that another focus is on the education market as it relates to big data. As he stated,  “there is a lot of data proliferation around how you learn and to garner that, make use of it and process it in the proper way so that people can learn faster and more efficiently. It’s actually a very interesting theme.”

One of the central questions Monsalve said he often considers is how this” consumerization of technology” can actually be applied to the small and medium-sized businesses. “Not just the enterprise, we focus on that as well at Norwest, but my specific area of focus is on small and medium-sized business technologies via the consumerization of technologies.”

The concept of consumerization of IT is one that’s been talked about to death, yet still remains rather general, at least when young companies are finding ways to differentiate. According to Monslave though, sometimes the solution a team is providing isn’t as important as the team itself…

He states that “we tend to focus a lot on team and market size. The solution is also important, but many companies we’ve seen with great teams, can meander and pivot into the right solution. …In the later stages, growth equity, absolutely we need to spend a lot of time on the financials and the operating leverage of the company. Can it be profitable? If it’s not today, can it be in the future? How has the growth been? The quality of revenue, is it good revenue, bad revenue? All of that, we spend a lot of time on the growth equity side. However, in the early stages, there’s not much to go by, but team and focus around the market is pretty important.”

Perhaps then instead of going after the next big data solution and pitching only a technology as a standalone key to success, young big data startups should consider putting more time and effort into their selection of an all-star team to drive the leadership factor and increase appeal?

For many big data startups, especially those offering new solutions like Hadapt which are built are on still-evolving technologies like Hadoop, MapReduce and so on, it can be a bit of a challenge to draw from a shallow pool of true expertise. Nonetheless, the VC firm says there are other considerations.

In terms of what his team looks for as they consider new data-driven investments, Monsalve says:

“I think we tend to, especially in the early stages; fund teams– high quality teams. I think a lot of people should focus on their qualifications as a founding team, but also the passion, the ability to articulate a very clear strategy and vision that’s very important.

Market size is also as important in that there are many ways to articulate that in a pitch. The way I prefer to do it is both from a bottom up perspective.  Can you actually multiply all the units, price and get to a market size that will make sense from a bottoms up perspective, but also from a tops down perspective…. It’s more a matter of, “Do you understand the global nature of the industry and how it segments down to where you could address it?.”

Related Stories

Startup Wrangles Machine Learning for Retailers

Latest Hadoop, Analytics Partnership Unfolds

Is Boston the Next Bastion for Big Data?