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In every industry, you can picture thousands of unfortunate analysts across dozens of companies all doing essentially the same work.  They’re all forecasting market growth, analyzing competitors, trying to understand customers, and so on.  And they read the same news, the same financial reports, and the same market research, for the most part.  The results of this work are closely guarded proprietary analyses, yet they’re all very similar.  There’s a huge amount of duplicated effort that doesn’t add much value.

Business Analysis as Software

Does this remind you of anything?  It’s what software development used to be like when every company developed its own custom applications in-house.  Every company had its own system for everything from payroll to accounting, either done in-house or by expensive consultants.  Eventually, software development activity was consolidated through a number of mechanisms:

• Commercial off-the-shelf software
• Process outsourcing (e.g., an external company handling your entire payroll process with their in-house software)
• Higher-level software languages and components
• Open source software

As a result, software development these days results in much less duplicated effort.

This dynamic has not occurred to the same extent with business analysis, to say the least!  Most big companies still have departments that do things like economic forecasting and competitive analysis.  Certainly, a part of this thought process is unique to each company and thus valuable for informing business decisions, but most firms can’t pinpoint where the commodity information ends and the differentiation begins.  It reminds me of the old John Wanamaker quote, “Half the money I spend on advertising is wasted; the trouble is I don’t know which half.”  The same is true of business analysis.

So Why Is This the Case?

I see a few causes for this waste.  First, there’s a game theory problem.  The first company to “open source” its analysis benefits its peers but doesn’t receive any benefit in return.  So there’s no incentive for individual firms to go first.  The current equilibrium results in little or no information sharing.

Second, external information sources are opaque.  Market research reports only include conclusions and estimates, not how those conclusions were reached.  As a result, consumers of those reports end up double-checking the work to make sure it’s applicable to their situations, or redoing the entire analysis because they need a slightly different focus.  Black box information sources can’t be easily repurposed.  In order to tweak an analysis by 10%, I have to reverse engineer the whole thing.  This isn’t an accident, either.  Research vendors want their clients to remain dependent on them, and revealing any of the inputs to their analysis reduces that dependence.  It makes sense for vendors to maximize their profits, but it doesn’t exactly maximize value for customers!

Third, internal analytical departments are motivated to maintain their headcount and budgets.  Advances in efficiency are often resisted because those affected want to avoid creating a reduced need for their work.  In reality, the importance of business analysis and research services will just continue to grow.  The difference is that they will be doing more highly-skilled, value-added intellectual work and less rote data gathering and number crunching.  But like any such revolution, it’s easier for people to see the negative first-order effects than to see the positive (and overall more impactful) second-order effects.  Those attitudes will take time to change.

Where Do We End Up?

Eventually, we’ll end up in a world where business information is more readily accessible, cheaper, and easier to remix and customize to specific needs.  The opportunity to disrupt the current high-cost approach to business analysis is just too appealing for new entrants, and the potential cost and efficiency savings will be too attractive for customers.  But the barriers to change described above won’t go away overnight.  Time and effort will be needed to get people used to the new paradigm of open source business analysis.

Let’s take a closer look at LinkedIn now that the company is moving towards an IPO.

LinkedIn’s Economics

LinkedIn users should be much more profitable than general social networking users because both those users and people who want to reach them are more willing to pay for features.  According to comScore, LinkedIn had 26 million unique visitors in December 2010, which works out to revenue per user of over $9.  According to recent reports, that’s more than twice the per-user performance of Facebook.

So then why is LinkedIn, at $3 billion, worth so much less than Facebook at $70 billion or so?  It really boils down to size and profitability.  Facebook apparently made about $500 million in profits in 2010 off of $2 billion in revenue, while LinkedIn only managed $15.4 million on $243 million in revenue.  That’s a 25% profit margin versus a 6% profit margin.  As it turns out, a rough PEG (price/earnings/growth) ratio for the two companies shows that LinkedIn is valued over twice as highly as Facebook based on 2010 profits and growth!  That Facebook valuation is starting to look better.

What’s unclear is how much LinkedIn is investing in future growth and to what extent it’s simply in a lower-margin business than Facebook.  While individual Facebook users are not necessarily that valuable, the business as a whole appears to be an incredible profit machine.

Sales and Marketing Costs

What’s even more intriguing is LinkedIn’s Q1 2011 numbers.  Sales and marketing expenses went from 23% of revenue to 31%, and net income dropped from 6.3% in 2010 to just 1.4% in Q1 2011.  At first I was surprised at the big jump in expenses, but on further reflection, I don’t think this is necessarily a bad sign.  LinkedIn is in a large and relatively open market.  In fact, I can’t believe no serious competitors have cropped up.  That’s a story in itself.  Anyway, the firm is in land-grab mode.  Spending heavily on sales and marketing now to build greater barriers to entry (in the form of more registered users, data, and corporate customers for recruiting and marketing) makes sense.

Of course, that position assumes that there is no permanent shift towards a much higher cost to acquire and retain customers.  That is a potential concern.  LinkedIn’s channel mix is slowly shifting from online to field sales (up from 47% to 56% in the last two years), which according to the company’s disclosure is associated with a longer sales cycles and higher sales costs.  It does also result in higher average selling prices, so it doesn’t appear to be a significant concern yet.

However, it does illustrate the limits of LinkedIn’s virality.  Facebook has built a huge viral engine on photo tagging, newsfeeds, and social games, and the draw of professional connections is certainly weaker for the average person.  As an aside, there are of course limits to Facebook’s growth curve as well, with some claiming that Facebook penetration tops out at around 50% of the population in most countries.

Revenue Breakdown

The revenue breakdown by product also reveals a lot about LinkedIn’s future direction.  There are three product categories, hiring solutions, marketing solutions, and premium subscriptions.  Hiring solutions revenue grew 182% from 2009 to 2010 and now makes up 42% of the company’s revenue.  In contrast, premium subscriptions grew 35% on 64% growth in registered users.  Advertising growth fell in the middle at 107%.  Clearly, the average user doesn’t see much need for a premium subscription, while recruiters can’t get enough of LinkedIn’s services.  Companies tend to follow their most profitable customers, so I expect LinkedIn to start offering much more sophisticated recruiting solutions over time.  I’m curious to see how they fare against other up-and-coming recruiting companies like TheLadders, Indeed, and Simply Hired.

So Is It a Good Deal?

If LinkedIn didn’t exist, someone would have to create it.  The online resume and professional network are basic features of modern life, and LinkedIn has hitched itself to a new consumer behavior that will only continue to grow.  As an individual, I wish LinkedIn would provide more useful features, but as a hypothetical investor, I see an ongoing growth story in this company.  The question, as always, is how much one is willing to pay for that growth, and that’s one I have a hard time answering.  LinkedIn’s venture capital investors, Sequoia Capital, Greylock Partners, and Bessemer Ventures, made up of infinitely better investors than me, are sitting on their shares and not participating in the IPO.  That suggests they expect the value of the company to continue climbing sharply.

The situation is even worse for hospitals in particular.  They’re overwhelmingly complex organizations, and as a result they’re difficult to manage.  They also have high fixed costs, and there is often over-capacity in specific geographical markets, leading to intense competition.  From a Porter’s Five Forces perspective, most of the puzzle pieces look pretty bad.

Most importantly, overall healthcare costs cannot continue climbing at their current rate indefinitely.  And like the old quote says, if something can’t continue indefinitely, it won’t.  Much more significant waves of reimbursement cuts are inevitably on the way, although no one knows when they will hit.

Considering all of these factors, it seems probable that the industry will undergo painful change and consolidation over the next couple of decades.

So what kinds of providers will survive ongoing changes in the field?  Here are the likely candidates:

• Unique, mission-driven organizations like the Mayo Clinic
• Disruptive providers like specialty hospitals that can offer more standardized care with a lower cost structure
• Large organizations that can develop superior processes and leverage high-quality management talent to outperform smaller competitors (i.e., the big hospital chains)

Unfortunately, the last of the three is probably the least likely.  I assume many hospital chains will attempt to go down this road but will fail nevertheless.  Why?

• Organizational chaos – Mergers bring scale but also dysfunction.  Many hospital chains will be unable to deal with the disruption and clashing priorities that mergers introduce.
• Apathy – Big, impersonal organizations exacerbate the tendency among the rank and file to say, “That’s not my job.”  Large hospitals have a much harder time holding people accountable.  Processes have to substitute for individual initiative, but they often can’t fill the gap completely.
• Complexity – Economies of scale are only good if you can really achieve them.  Because hospitals are individually so complex, just having more locations within the same company doesn’t necessarily achieve a lot of efficiencies.  Administrative tasks like billing likely become somewhat more efficient, but I doubt large hospital chains manage their physical resources any better.

As the largest hospital chain in the country, HCA would seem to be the flag bearer for the scale strategy in the hospital industry.  The recent IPO was successful, but I’m less convinced that they will actually be able to generate the operating advantages they’re looking for.  Operating margins look like they’re in the general ballpark of public healthcare providers at about 7% – not exactly a ringing endorsement of the strategy.

The wrong way

Probably 95% of investor relations departments don’t have this kind of mandate. To pick on a recent example, let’s consider Strabag, one of Europe’s leading construction companies. The firm recently shut down its communications Twitter account because no one was tweeting them. Of course, the company didn’t use the account for anything except for relaying analyst ratings and the status of its order backlog – not exactly captivating.

Strabag made a variety of mistakes. All marketing, but especially social marketing, is a content-driven activity. If you don’t have interesting things to say, no one will listen. You don’t have to be in a sexy business to come up with meaningful content (look at Zappo’s in shoe retailing), but you do have to think about what your audience wants to hear. Strabag could have engaged in a dialog with analysts, better understanding their information needs and perceptions of the company. A primer for investors unfamiliar with the construction market would have been even better. I won’t belabor all the usual social media points beyond that.

Tactically, Twitter is an awful channel for arbitrary data points (output is up 6%!) lacking context. Even order backlog is probably interesting to investors and equity analysts, but it should at least link back to a chart and spreadsheet showing the trend over time, comparisons with competitors, and implications. There’s no reason for online communications to mimic the dry facts of a stock ticker. Help people draw conclusions!

The right way

In contrast, I was blown away by the exchange between Reed Hastings from Netflix and a hedge fund short seller on Seeking Alpha (brilliant site, by the way). The hedge fund manager lays out his concerns about Netflix’s valuation, new competition, the costs and quality of licensed streaming content, and a few other reasons for his short position. Hastings addresses them all openly and dismantles most of them. Finally, the short seller posts again to say that he’s covered his position and why. For a business geek like me, their dueling analyses are such fun to read, and they do an excellent job of illuminating the company’s strategy, the industry landscape, and possible risks and upsides. I probably could have read Netflix’s entire 10-K filing and come away with much less understanding of their business than after reading those posts. It’s also brilliant investor relations, and Hastings and his team eliminated a potential stock performance issue, thus allowing them to stay focused on the core business. Now, this kind of response requires that your company actually have a very well thought-out strategy and evidence to back it up. Most firms probably couldn’t hack it, but it is something to aspire to.

Expand your mandate

Various corporate functions have been transformed from rote work to strategic assets over the last few decades. Human resources used to be about job postings and benefits management. Now, ideally, it’s about selecting, recruiting, and retaining the best possible talent. Traditionally, purchasing was probably one of the dullest jobs imaginable (no offense). However, in the context of strategic sourcing, the job is more about partnering with suppliers, understanding their impact on product quality and strategy, and forecasting the evolution of your industry value chain than just about issuing purchase orders.

The same thing needs to happen with investor relations. Investors are critical stakeholders in public companies, and we’ve seen various examples of firms crippled by short sellers over the last few years. Investor relations should be a strategic communication channel to cultivate a supportive investor base and to funnel market information back to management. It’s time to go beyond conference calls and financial filings.

]]> http://www.brekiri.com/blog/477/the-new-paradigm-of-investor-relations/feed/ 5 http://www.brekiri.com/blog/461/why-is-good-business-information-so-scarce/ http://www.brekiri.com/blog/461/why-is-good-business-information-so-scarce/#comments Wed, 02 Mar 2011 14:35:16 +0000 Greg http://www.brekiri.com/blog/?p=461 I recently came across this O’Reilly post about CrunchBase, the open database of information on startup companies, asking whether CrunchBase will remain free in the long term.  While the post itself is interesting, the part that puzzles me is why there is so little business-oriented information freely available out there.  Data as a service has been [...]]]>

I recently came across this O’Reilly post about CrunchBase, the open database of information on startup companies, asking whether CrunchBase will remain free in the long term.  While the post itself is interesting, the part that puzzles me is why there is so little business-oriented information freely available out there.  Data as a service has been generating a lot of excitement recently, and I think it’s well warranted.  However, the only prominent sources of open business information are the SEC’s Edgar database, LinkedIn, and CrunchBase.  After that, the field gets very thin.  Considering how much effort companies put into business intelligence and competitive intelligence, it seems like there should be a great profit motive for someone to provide a deeper business information layer.  So I don’t really understand why we’re in this situation, but it does seem like a big opportunity.

These days, most companies are still creating expensive in-house data sets for purposes like market analysis and competitive intelligence. Data providers like Thomson Reuters and CapitalIQ do the same thing and charge through the nose for it.  As a result, big companies end up paying a lot for often not very impressive information. Meanwhile, the rest of the market makes do with sources like Google that just aren’t intended for business research.

The open source analogy

The current landscape reminds me of the days when every big company did custom development for its own IT applications, even though each company’s payroll or data processing system did basically the same thing. That’s good for consultants and developers, but it makes process improvement very expensive for corporations. Similar walled gardens still dominate the business information market.  We need to move to a mindset closer to the open source world. In the last ten years, open source software has become a very competitive option compared to commercial software.  While the core movement is still based on developers writing code based on their personal interests, an important catalyst for the movement has been the rise of companies that add a layer of support and commercialization on top of the core technology. Open source is now a lively market, not just a movement. What’s interesting is that users of open source, from Google and Facebook to NASA, probably contribute more to it now than the companies that sprung up to commercialize it, like Red Hat.  The crowd is contributing to tools that would often be prohibitively time-consuming to build internally or too expensive to license from a vendor.  All the users benefit as a result.

The Wikipedia of business?

Wikipedia and other crowdsourced sites like Wikinvest (a wiki for public company information for investors) are a bit analogous to the open source movement. People make contributions for fun or or to burnish their reputations, not for monetary incentives. The results have been amazing – the English language Wikipedia alone has over 3 million articles. But there are also limits to the phenomenon. Growth in articles is estimated to have peaked in 2006, and you can tell that sometimes articles of marginal interest to the community languish or are even deleted. And as the base of articles becomes more static, it will be interesting to see whether the relatively mundane task of updating all those articles still motivates people.

Wikinvest is another amazing tool, but also one with limits. Interesting companies are updated frequently, but articles on, say, pulp and paper companies tend to be out of date. (As an aside, I get the impression that contributors to Wikinvest are overwhelmingly undergraduate business majors. I wonder what the incentive is. Do corporate recruiters look at the site?)

So there are limits to the open source model for data, particularly commercial data like company information. Somehow writing up a stock analysis doesn’t have the same craft appeal as working on a piece of software.

The commercial data layer

But I do think there’s potential for a real commercial data layer, crowdsourced but with profit and cost savings motives as a driver. There are myriads of players who need information on topics like companies and industries (or who want to sell it), and right now they’re all creating expensive, in-house data sets.  Moreover, much of the data is inaccurate or rapidly goes out of date because maintaining that volume of information requires massive scale. It’s a lot like the software world before first off the shelf and then open source became prevalent.  There are huge economies of scale to be realized with a more consolidated data layer.

Facebook owns the social graph. FourSquare or Yelp will likely do the same with local business information (although Groupon could be well positioned to horn in on it). Right now, no one has claimed pole position in creating this data layer for commercial purposes. There are also lots of aspirants to that position: Thomson Reuters, Capital IQ, Bloomberg, and on and on. I just don’t think any of them are taking the right approach. We need a platform, not a silo.

Once commodity information on companies becomes more widely available, it will be interesting to see what kinds of applications people can build on that information.  Tools like Google Finance, which is quite amazing for a free service, are just the tip of the iceberg. Imagine if you never had to do another bubble chart yourself again! Freeing people from basic research will make it much easier to do deep, thoughtful business analysis instead of spending your time trolling for information online. Basic business information needs to become an open commodity.

As is usual with private equity deals, HCA has been fairly heavily loaded with debt.  The IPO won’t give it too much additional financial flexibility since proceeds are expected to go primarily to the current private equity owners.  So pursuing large-scale consolidation, which was Columbia/HCA’s original claim to fame, seems unlikely.  Instead, HCA plans to selectively extend its services in major markets.  The company also just reorganized to offer its shared services, like revenue cycle management and supply chain management, to other healthcare providers.

It’s not clear yet how interested investors are in the IPO, but HCA reduced the fundraising target for its IPO from $4.6 billion initially to the current price.  This suggests less than unbridled demand for shares.  One area of concern may be the impact that healthcare reform will have on HCA’s business.  The government has been making more efforts to contain the growth of Medicare and Medicaid spending, which makes up about 40% of HCA’s revenue.  Overall, it seems unlikely that shaving part of a percentage point off government healthcare reimbursements will make a big difference to HCA, but maybe investors are easily spooked these days.

HCA’s results for the fourth quarter of 2010 included a 31% jump in net income, although most of that appears due to miscellaneous accounting adjustments.  Surely just a coincidence with an upcoming IPO, right?  From a top-line revenue perspective, growth slowed down considerably in 2010.  The reason is unlikely to be the economy considering that revenue did grow well in 2008 and 2009.

In many ways, HCA is a pretty straightforward company.  I’m going to spend some time digging into HCA’s latest 10-K and their IPO prospectus and see if I can find out anything interesting about the company, or perhaps even about the healthcare industry these days.

• U.S. tries open-source model for health data systems
  • The government and a variety of big companies are working to quickly develop a standard for sharing healthcare information among different providers.  The early version basically appears to be encrypted email.  It sounds ridiculously simple, but maybe getting a basic standard in place and seeing what healthcare users need to help them do their jobs is a better approach than spending years in standard-setting only to realize the specification doesn’t really meet people’s needs.

• A new challenge looks for a smarter algorithm to improve healthcare
  • The Heritage Provider Network, a big primary care network in Southern California, is offering a Netflix-style prize of $3 million to whoever can best predict which patients will end up in the hospital based on anonymous medical data.  The idea is that statistical analysis might catch risk trends that physicians miss, allowing riskier patients to receive better care and thus mitigating the chance of costly hospitalization.
• Can we lower medical costs by giving the neediest patients better care?
  • In New Jersey, Boston, and Atlantic City, a few doctors are taking a much more intensive approach to the sickest patients, trying to minimize extremely expensive chronic hospitalizations.  Even more interestingly, the article mentions companies like Verisk that are attempting to use data analysis to minimize healthcare costs in much more sophisticated ways than usual.
• Massive Health uses big data, mobile phones to fight chronic disease
  • Details are a bit slim, but Massive Health recently got a couple of million in funding from top-tier venture investors like Andreessen Horowitz to help patients manage their chronic diseases with the help of mobile phone data.  The idea is that real-time feedback on their behavior will encourage them to change it, the same way real-time mileage information changes driving patterns.

Of course, these initiatives are all different.  And there are very legitimate reasons to be skeptical of whether they can all be successful, or more importantly whether initial, localized success can be extended to the overall healthcare landscape.

But these initiatives already seem more likely to have an impact than efforts like Google Health and Microsoft Health Vault, both of which seem like platforms looking for a problem to solve.  Most patients simply aren’t that interested in the abstract idea of online health records.  To make inroads with health data, companies need to either focus on helping healthcare providers or create consumer applications that focus on self-improvement rather than healthcare per se.   The paradox, as always, is that the patients who need to be the most vigilant about health issues are usually the hardest to motivate.  That challenge won’t simply wash away in a wave of new technology.  Innovation in medical business models and practices will also be necessary, and progress will probably be slow.

From a technology perspective, we can only hope that the insoluble problems of healthcare decision-making become more tractable over time.  Speech recognition, computer vision, and the tricorder all once seemed like pie in the sky but are now either a reality or just around the corner.  Now that healthcare information is finally becoming digital, perhaps similar advances will finally be possible with the treatment of chronic disease.