Overcoming the Hurdles of Big Data Start-ups
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Overcoming the Hurdles of Big Data Start-ups

Cheryl Cheng, General Partner, BlueRun Ventures
Cheryl Cheng, General Partner, BlueRun Ventures

Cheryl Cheng, General Partner, BlueRun Ventures

The dawn of the digital era with the commencement of unprecedented technologies has resulted in a massive escalation in the amount of data that is generated and accumulated. Under the broad umbrella of “big data”, one must focus specially on useful data—data that is as close to real time as possible. Valuable real-time data must be segregated from huge pools of data that can help consumers and enterprises in their decision-making process. In enterprises, CIOs are often inundated with the data that is generated by their own systems, data bases, and third-party start-ups which make it extremely complicated for them to analyze and make crucial decisions that can significantly move the needle on their business. In order to identify trends and discern anomalies in data sets, the data must be ingested and normalized using potential software. Comprehending the method to identify anomalies in data patterns is mission-critical. Over time anomalies tend to become a norm and hence it is vital to detect them at an early stage to help your company save substantial amount of money.

Is AI a Buzzword or a Requisite for Data Analysis?

Jumping on the AI bandwagon, several start-ups are endeavoring to implement artificial intelligence in data pattern analysis by investing huge capital. Albeit, AI can help improve and expedite data-driven decisions, the important question here is “Is artificial intelligence the solution to your problems?” or is it just a fad that people are irrationally following? Instead of jumping to a rapid conclusion of leveraging AI to solve problems, enterprises as well start-ups must expend in advanced data base analysis which is not artificial intelligence. Also, it’s very important to ponder over the question that is inevitably going to rise in our minds—“Will machines run enterprises in future?” At its nascent stage, BlueRun is not equipped with a fully built out platform or the capital backup to invest an exorbitant amount in artificial intelligence. Maybe in the future when the company has enough capital turnover, implementing AI could be a viable solution to problems. Now or later, it is imperative to deliberate on the necessity of AI in building a solution and if it helps you to chase the expected amount that you are willing to sell your solution at. The next thing we thoroughly consider is whether our team is competent enough to develop winning systems in these areas. Our company is at its emerging stage and our team lacks the experience to build solutions by applying artificial intelligence that require years of expertise. Conquering the Challenges of the Start-up Landscape.

  Under the broad umbrella of “big data”, one must focus specially on useful data— data that is as close to real time as possible 

It is indispensable for a start-up to have a clear picture of the purchase cycle of a company and what is looks like to the CIO right now. There are other factors that are requisite to consider for a start-up to evolve into a full-fledged enterprise— deciding how mission critical the solution is to the company, how much money the company is leaving on the table by not adopting the solution. In terms of research and development, CIOs are myopic and do not allocate an innovation budget to explore and implement unprecedented technologies with start-ups. It is an inherent challenge that I am trying to help our companies overcome by building good relationships with CIOs, CMOs, and CTOs. It takes time as in a start-up world we move ahead rapidly whereas in the Fortune 500 world it’s a completely different bargain.

"The most valuable thing that forms the bedrock of my business is the trust that I build with entrepreneurs"

Emerging start-ups are always struggling to strike a balance between creating a solution that widely serves all kind of customers and picking a niche market that is concentrated enough to have a good wedge in an industry. Recognizing the potential of big data, many start-ups have begun to enter the big data field hoping to make a significant impact on industries that are evolving at a rapid pace. What makes it challenging for start-ups to secure their place in an industry, is the emergence of more companies in the B2B business domain which were previously not present. A start-up must strategize efficiently to gain a competitive edge in the market and thwart the risks of obsolescence.

Some Insights into our “Kabbage” Project

We are an early investor in the company ‘Kabbage” and Kabbage to me is a major disruption in the fund-lending and risk-analysis market. Established in 2009, Kabbage supported the emerging companies that were suffering the blow of a financial crisis. Banks were declining to lend money to small businesses and entrepreneurs had no access to capital to support their businesses. What aggravated the problem is that even if they did get access to money, the procedure for evaluating the risks of money lending were strictly based on scrutinizing the company’s financial background and fico scores instead of probing into the business. Deviating from the established model of risk analysis, Kabbage stepped into the market at a time of financial distress and operated on a completely different strategy. They would evaluate your UPA shipping data, ebay seller reviews, and other bits of information that are generated on different platforms and then assess credit card risks based on these factors and not just credit card fico scores. Kabbage started off by accumulating a ton of third party data which they ingested, analyzed and then created a solution. Over time, the company has gathered a substantial amount of primary data that they can use to tweak and refine their risk-analysis model. The company efficiently leveraged big data to provide an entire new service in the risk-analysis industry.

Our Invaluable Strategy

The most valuable thing that forms the bedrock of my business is the trust that I build with entrepreneurs. When you come into the pitch, it seems money is the most profitable thing you can gain from your investors. The most valuable thing you can get from me is my time; the time that I spend with entrepreneurs reflecting on your business and contemplating the hindrances that you might face in future. As lucrative as it might sound, building a successful business from the grass-root level is an extremely demanding job. Entrepreneurs pour in every dime, devote every waking hour, and put all their relationships in line to begin a start-up. I believe it is my responsibility to assist budding entrepreneurs in forging the path to their success by lending them capital, some through venture firms and some through the network that me and my partners build. Apart from these, I dedicate significant amount of time building trust with entrepreneurs discussing about a better outlook for the company or about manoeuvring the company to a newer direction.

I believe my industry is operating in two time zones simultaneously. While I am physically present in 2017, mentally I am in 2020. As investors, we lay special emphasis on timing, the right time to invest in a company. We always invest in prospective start-ups which are not at scale or mainstream at all, but will be three or four years from now. We constantly anticipate the future of aspiring businesses which have interesting platforms and a lot of possibilities but lack the infrastructure and hardware to move ahead with their business. Anchoring itself to mainstream market might take long for a company, might be 10 to 11 years. Proper timing of investment is the crux of our business, the building block of our success pathway.

See Also:

Top Big Data Solution Companies

Top Big Data Consulting Companies

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