Data and Analytics · Data analysis

Looking for recommendations on data analytics business

Weihong Zhang Co-founder at Brilent, Inc.

July 9th, 2013

Data analysis and analytics has been increasingly playing a more important role in business process recommendation and decision making. Given the growing demands of data analytics, there should be more business opportunities of data related analyses and software developments from the market. However, this hypothesis does not translate into reality in a straightforward manner. One reason is that the business owners or senior executives may overlook the importance of business data analysis. Another reason is data privacy/security - a business is reluctant to disclose its data to outside firms. Do you have recommendations on how to strategically approach the small- to median-size companies that have data analysis needs for example in the healthcare, retail, or financial industries?

 

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Tim Kilroy Analytics - LTV - Boosting Profits - Digital Marketing

July 11th, 2013

Hey - I think the issue is not that companies aren't willing to share their data (many, many retailers are). The issues are:
1. They don't really know what they have and what they don't.
2. They are very unsure about what they will get out of parsing all this data. If you look at a retailers purchase data and find that customers are more likely to buy on Thursdays in June, what does this mean? There is the insight to action gap that keeps many on the sideline.
3. Without a desired end state and a roadmap to get there, many companies will not "explore" to discover new opportunities. They are more likely to want to know what others have done and do that. It isn't a failure of vision, but a failure of staff, resources and time on the client end that keeps exploration on the sideline.

This, honestly, sounds like a business & sales problem. If you have skills to discover insight - wonderful. But how do you package that insight into actionable improvements for your clients. If you can sell to the opportunity, that is much better than selling on the process.

Jason DeMorrow Senior Software Engineer at iSpot.tv, Inc.

July 10th, 2013

The data analytics space as it exists today seems dominated by "hand us your data and we'll tell you stuff" type companies. They fall at varying points along the product <> service spectrum, but they all seem to serve the same segment: huge companies with mountains of data. These are the only customers who'll spend large sums of money on "discovery" projects because a) they have the money to burn and b) they have enough data to make it worthwhile. I think if you want to woo the small-to-mid market with an analytics solution, it would have to solve a specific business problem of theirs, and be able to do so with a relatively small data set. I agree with the comment about SaaS; smaller companies are going to want a plug-n-play solution with a specific, known outcome. And it has to be (relatively) cheap.

Michael Brill Technology startup exec focused on AI-driven products

July 9th, 2013

I'm not sure if they're going to delete your question again, but I think it would be useful to describe your offering, target market and competitors. The issues you raise don't resonate with me for large enterprises who are spending a ton of money on BI/big data/analytics.

Mitchell Portnoy Healthcare Information Executive

July 10th, 2013

There are a few methods that have proven effective in the past.  I'd be happy to talk to you sometime over the phone if you like.  Google one of my former creations:  Symmetry Health Data Systems or Episode Treatment Groups for examples.

Weihong Zhang Co-founder at Brilent, Inc.

July 12th, 2013

Vijay MD Founder Chefalytics, Co-owner Bite Catering Couture, Independent consultant (ex-McKinsey)

July 9th, 2013

From what I've seen there are 2 ways to get in:
1) Sell a package tied to software/ reporting (e.g., X certified vendor) ...execs want to buy the reports not the analysis
2) Do backend stuff for special project teams (e.g., internal consulting, data interface for external consultants)

Most small/ median size companies are the wrong targets because they're not used to outsourcing everything and often don't have the capabilities to do it.  Also, they'll generally want to pay for an established product (e.g., SaaS) over professional services at any type of onshore billable rate.  Professional services firms may be an exception as they could resell your services at a higher billable/ use your capabilities to go after more parts of a project as part of a project proposal.

Gaurav Garg

July 9th, 2013

i have created BI solutions for healthcare providers and HIEs in he past. Happy to talk about BI, Analytics in the healthcare industry. It is a, rather complex discussion, best done in person or phone. Gaurav

Michael Brill Technology startup exec focused on AI-driven products

July 12th, 2013

I still don't know who you're targeting, what problems they have, what your solution does and who your competitors are. My underlying concern is that maybe you are selling at a level of abstraction that isn't going to be well-received by someone with specific problems to be solved. [Of course I only have 2 short posts from you from which to make this broad assertion!]

One suggestion is that you focus on ONE business problem where you can clearly identify the companies who have this problem, how your solution is well-suited to solve this problem, what their alternatives are, and why they'll select you. I think if you bring that back to the group, people can give you a lot more valuable feedback about how to move forward.

Weihong Zhang Co-founder at Brilent, Inc.

July 12th, 2013

Thanks to all for your insights from this supportive community. Most of the responses have been in the areas of big data, business analytics, and business intelligence. As Michael, Jason and Tim pointed out, the targeted markets should be more on the large enterprises: large enterprises have enough resources to sponsor the analytical projects, the discovered insights are more worthwhile in improving their business operations, and they are more robust in digesting project up-and-downs on the road. Vijay proposed two ways to approach an analytical business, the second of which is “do backend stuff for special project teams (e.g., internal consulting, data interface for external consultants)”. Did you mean to be a subcontractor of a project team by contributing to the data analytics part of it? I look forward to listening to Gaurav and Mitchell’s successful experiences in the healthcare industry using data analytics.

 

I like to discuss a little more on data analysis and data analytics. As the industrial trends stand and move forward, the notion of data analytics has been dedicated to the technologies around big data, business intelligence, data mining, machine learning, hadoop/mapreduce, NoSQL, AWS, etc. Although in general “data analytics” is larger-scaled and/or more distributed part of “data analysis”, I would use “data analysis” to mean more traditional data processing, say the data samples of disease symptoms versus nutrition intakes, a clinical study on the efficacy of a drug in certain populations, predicting the output of a solar panel given the time series data of outputs over several years, the customers’ shopping behaviors analysis for a median-size retailer, and so on. These data analyses are generally in smaller scale, say in less than gigabyte scale. A small data analytical business organization specializes in and more replies on commercially available software (like SAS, MatLab) and existing open source software (like Weka), other than substantial development and integration services. I think that such data analytical businesses may target at the data analysis projects in the market.