Data And Analytics Strategies: What Investors Think
Whether raising a round of funding or creating shareholder wealth, companies increasingly need a well-articulated and demonstrable data and analytics strategy. Here are some things that can sway an investor's opinion, for good or bad.
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Data and analytics strategies are no longer merely nice-to-have. They're becoming mandatory because data and analytics are changing the competitive landscape in every industry. Some Wall Street analysts and venture capitalists are keenly tuned into the top-line and bottom-line differences the use of data can make. If you're presenting to one of these firms in hopes of getting funded or maximizing shareholder wealth, you'd better be prepared to answer some very smart questions, and be able to back up what you say.
Institutional Investor recently published a report, sponsored by KPMG, based on a survey of 260 investors and sell-side analysts. Twenty-four percent of the respondents said they changed one or more of their investment opinions based on a company's data and analytics strategy, and 45% expect that to be the case in the next two years.
"The [companies] that have been using analytics for years are farther along, but one by one they're getting it, and I'll call it the competitive advantage or competitive disadvantage," said Brad Fisher, national data and analytics leader at KPMG. "You're either playing offense or defense."
The report indicates that data and analytics strategies are affecting organizations across industries. While the data-driven maturity of companies varies from industry to industry and business to business, momentum is building. Failing to have a data and analytics strategy, or executing one poorly, can negatively impact a company's ability to compete -- and therefore its value.
"Data strategies are here to stay across a number of different areas [where] we're going to continue to invest, and it will be a bigger part of our investing thesis as far as where we put our time and energy in the portfolio," said Ron Heinz, managing director at venture capital firm Signal Peak Ventures.
Data and analytics strategies need three key elements to succeed: The technology, the ability to execute, and a culture that embraces data-driven decision-making. How all that is evaluated is interesting indeed. Here are six examples of what investors look for before they decide to pump capital into an organization.
A company's ability to compete has always affected its valuation. Already, 82% of the investors and equity analysts responding to the Institutional Investor study expect data and analytics (D&A) to disrupt the sectors they cover in the next year.
"By industry and by company, people are at different stages with their D&A strategies," said Brad Fisher, national data & analytics leader at KPMG, which sponsored the report. "Some have had advanced analytics for years, and others are probably [behind]. Maybe it's the fact that their industry model hasn't been under such duress, so they're still disbelievers."
Even startup companies need a data strategy to win attention from investors. The ability to leverage data affects a company's ability to compete and, although there are lots of things to measure, understanding customers and their behavior is critical. Without that, an early-stage company will be unable to achieve the momentum and critical mass it needs.
"The expectations have gone up considerably for how entrepreneurs understand their business, and how they measure their business," said Brian Ascher, a partner at venture capital firm Venrock . "Do they understand the total cost of customer acquisition, the lifetime value that customers have [based on] engagement and usage metrics? If you fumble on understanding your internal data, it's very unlikely you'll do a deal."
On the other hand, Ascher said, if a startup can convince an investor that it's leveraging data to understand the nuts and bolts of its business, that's a huge plus. "Would it influence our investment decision? Yes. Would it influence the amount of capital? No. The amount of capital depends on capital needs and the risk versus milestones met, but the initial decision is very influenced by this," said Ascher.
Wall Street has always monitored the performance of companies, and venture capitalists have always linked milestones with funding. According to the Institutional Investor report, buy-side and sell-side analysts think data and analytics' biggest potential is in improving the operating performance of their investment targets in the short term, followed by various forms of business and product expansion and risk management.
For a company to execute a data and analytics strategy, it needs technology, access to the right data, the ability to execute, and a culture that thrives on data. Technology alone cannot deliver the intended level of business impact.
Talking about a data and analytics (D&A) strategy is one thing, demonstrating the impact of it may be another. According to the Institutional Investor report, "expectations and standard metrics for D&A success are not well established."
In a few cases, Venrock has asked for raw data from the companies in which it invests. "We had a very specific way in which we wanted to look at retention, because you want to do it on a cohort basis, and there are [different] ways to come up with an answer, some of which may be more lenient than others. So we said, 'Look this is exactly the data we want in this spreadsheet, please fill it in and we're going to do our own calculation of churn," said Venrock partner Brian Ascher. "You really learn a lot by asking questions and seeing if the answer exists in quantitative form. Sometimes [the answer is] 'yes,' you turn to the slide. Sometimes 'no, but I have it and here's an estimate.' Sometimes you get a blank stare, and the blank stare is not great."
Another way to show that a data and analytics strategy isn't merely smoke and mirrors is to demonstrate actual results.
"If you pitched me in February and told me something would happen by April [show me] that it actually happened by April," said Mercury Fund partner Aziz Gilani. "The real proof for us comes when we use our internal contacts to talk to potential target customers or current customers and hear what those customers tell us directly. What we like to hear the most is 'this company came up with a product that solved a problem, but then it solved an even bigger problem I didn't even know I had.' That's super impressive because it means the company took the time to understand its customer base and is responding to what customers are not necessarily [saying] overtly, but through their behaviors."
Data and analytics can help public companies minimize some of the quarterly surprises they had in the past. By monitoring operations, customers, and customer interactions, executives can take corrective action faster. While it's wise to learn what data and analytics strategies can do in specific situations inside and outside your own industry, it is also wise to keep your own unique business in perspective.
Early-stage companies aren't saddled with the legacies of more mature companies, so they have an opportunity to leverage data and analytics out of the gate. The problem with shiny new toys is the belief that a company can do something that is not practical, not consistent with its business model, or both. If you think "monetizing data" means you're going to sell data and you're pitching Venrock, you'll either be right, or wishing you'd thought more about what "monetizing data" means in context.
"It's usually a telltale sign to me when I hear 'we're going to charge for our software. We're going to do this and sell our data because it's really valuable.' I'm usually pretty skeptical of that because you're either in a business where you sell data or you're not. It's going to be a core focus or you're going to get value, but you're not going to sell it," said Venrock partner Brian Ascher.
He added: "Another thing I would be skeptical of is someone who says it's all about my math. I don't think fundamentally it's about new math or proprietary math, it's usually about asking the right questions and getting access to the right data and then you have to be smart about it. It's about trying to understand if they have a realistic sense of what it's going to take to build toward the vision that they're trying to sell me on."
Data and analytics can help public companies minimize some of the quarterly surprises they had in the past. By monitoring operations, customers, and customer interactions, executives can take corrective action faster. While it's wise to learn what data and analytics strategies can do in specific situations inside and outside your own industry, it is also wise to keep your own unique business in perspective.
Early-stage companies aren't saddled with the legacies of more mature companies, so they have an opportunity to leverage data and analytics out of the gate. The problem with shiny new toys is the belief that a company can do something that is not practical, not consistent with its business model, or both. If you think "monetizing data" means you're going to sell data and you're pitching Venrock, you'll either be right, or wishing you'd thought more about what "monetizing data" means in context.
"It's usually a telltale sign to me when I hear 'we're going to charge for our software. We're going to do this and sell our data because it's really valuable.' I'm usually pretty skeptical of that because you're either in a business where you sell data or you're not. It's going to be a core focus or you're going to get value, but you're not going to sell it," said Venrock partner Brian Ascher.
He added: "Another thing I would be skeptical of is someone who says it's all about my math. I don't think fundamentally it's about new math or proprietary math, it's usually about asking the right questions and getting access to the right data and then you have to be smart about it. It's about trying to understand if they have a realistic sense of what it's going to take to build toward the vision that they're trying to sell me on."
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