Another Kind of Data Harvesting

I have written before about the data-driven revolution that’s taking place in agriculture today that will allow farms to radically increase their productivity and crop yields. Data collected from farm equipment and soil sensors allow farms to plant exactly the right seeds at exactly the right depth to maximize yields, all handled automatically by high tech farm equipment guided by GPS that can run itself autonomously. It’s an exciting future.

One of the key points of my earlier article is that a farmer’s data, by itself, isn’t that valuable. Knowledge comes from building a large enough sample of planting data from other similar farms in similar geographies in order to find benchmarks and best practices. Thus if you want data from your own farm to benefit your own farm, you need to pool your data.

But what if a farmer doesn’t want to make the needed investment to benefit from data-driven agriculture? Are there other markets for the data?

Well it turns out that there are. As an article in the Wall Street Journal makes clear, field level data doesn’t just benefit the farmer, there are others who will happily pay for it. For example, seed companies can get extremely detailed insights into what’s being planted and what’s growing best and where. They can use such data to inform both their R&D and their marketing and forecasting activities. There’s a Wall Street angle as well, with commodities traders looking for an edge by trying to get an early insight into what the forthcoming growing season will bring.

But even here, there’s a need for aggregation. The experience of one farm doesn’t help seed companies or traders very much. But the more farm data you can aggregate, the more valuable your dataset. The race is already on with companies such as Grower Information Services Cooperative, Farmobile and Granular Inc. are already duking it out to sign up the most farmers as quickly as possible.

The simple lesson here is that even though the same farm data can be monetized in multiple ways, there is a valid, indeed critical, role for an aggregator. We see also that first-mover advantage is critical in data plays like this. And as always, market neutrality is an important advantage: you’ll have a much harder time collecting this kind of data if you are a seed company as opposed to an independent information company.

Is Faster Better?

When it comes to information, is faster always better? As information users, we all want to have the freshest possible information possible on which to base our decisions. But, as many data publishers have learned the hard way, while everyone wants up-to-the-second accuracy and currency in their data, not everyone is willing to pay for it. Indeed, we’ve noted with concern the growing trend towards “good enough data,” where users are willing to sacrifice some amount of accuracy and currency in favor of a significantly reduced price. So, on a practical basis, a data publisher could be excused for concluding that the most accurate and current data shouldn’t be a top priority.

Things, however, are a bit more complicated than that. The speed of information updates does matter, a lot, in specific applications and markets and people in those markets will happily pay a stiff premium to get hold of such data. The obvious place to look for proof of this is the world of finance. If you have information that can move the price of a stock or the entire market, speed matters. Consider that Thomson Reuters used to charge a premium for those who wanted access to an important consumer sentiment survey just two seconds before everyone else.

There are more mundane examples of this in non-financial markets. Consider sales leads. While every second may not matter when it comes to sales leads, there is added value in delivering them quickly, particularly if based on a real-time assessment of a prospect’s online browsing pattern.

Given all this, it would seem that a new service called Now-Cast Data has a winner on its hands. That’s because the company, run by economists, is preparing to offer a real-time economic forecasting service. Real-time delivery is actually something of a breakthrough in the world of economic forecasting, which is used to monthly, quarterly and even annual reporting. Clearly, by accelerating forecasting, the financial types will gain an information advantage for which they will pay handsomely. Or so it would seem.

But as an article in the Wall Street Journal notes, Now-Cast Data has some convincing to do. The core issue is that while Now-Data is certainly accelerating forecasting, at the end of the day, it is still offering forecasts. It can’t be sure what will or won’t happen, or whether specific events (e.g., inflation) will persist. As an economist in the article notes, “When a big outside event disrupts the economy, those are hard things to forecast. By definition you can’t build them into your forecasting model because they haven’t happened yet.” In short, we’re guessing faster, but we’re still guessing.

So where do I come out on speed? Is faster data always better? At least for now, I don’t think it is. Right now, it’s only really valuable in a specific, limited set of applications. Keep in mind too that we’re already drowning most of our customers in data. Getting the fire hose to pump faster just makes things more unmanageable for them. And speed is a relative concept as well. If a company changes its address, that’s a valuable, time-sensitive piece of actionable information. But if you already pass that information to your customers the same day you learn about it – say 8 hours at most – accelerating that to 8 minutes won’t improve either customer sales results or your bottom line. As data publishers, we want to be continually looking for ways to obtain and move information faster, but speed is something that’s ultimately defined by your customers and your competitors.

LinkedIn's New Corporate Directory

In my view, the future of LinkedIn depends on finding ways to get itself inside of business workflow – the essence of infocommerce – because the history of databases that remained standalone reference products is a sad one.

LinkedIn’s first big push to build ongoing user engagement was to add user-generated content, lots of it, creating a B2B Facebook if you will. This is certainly a valid approach, but with the Internet already groaning under the weight of endless content, much of it free, this is a tough road. I think workflow integration is a lot easier and ultimately much stickier. It is, fundamentally, the difference between logging into LinkedIn to “stay current” or perhaps find a useful morsel of information through sheer serendipity, and logging into LinkedIn because you need it to do your job.

Well, LinkedIn took a small but important move in the direction of workflow this week with the launch of LinkedIn Lookup. Very simply, this new app allows you to turn LinkedIn into an internal company directory.

As you can imagine, if you were to filter all LinkedIn profiles by current employer, you would essentially get an internal company directory. And it would be better than almost any company directory that exists given the depth of its profiles and the high level of data accuracy. But the new LinkedIn app does more than just filter listings, it also prioritizes fellow employee listings over your own connections so you’re really using it as an internal directory. Corporate email addresses are shown as well.

Overall, LinkedIn Lookup is a fairly weak version 1.0 app. But if LinkedIn sticks with it, it could take this product in some very interesting directions. Consider:

·        Setting up the product with a corporate administrator could help make listings more accurate (many people don’t update their employer information if they are not immediately going to a new job). In addition, LinkedIn could make this administrator the point person to maintain the company web page as well, helping to insure deeper and more accurate data

·        With listings now used for employment purposes, employees will be more diligent in maintaining their listings to the benefit of both the company and LinkedIn

·        By letting employees see all the connections of other employees, an extremely powerful networking tool along the lines of those offered by Reachable can be offered.

·        Non-public fields could be made available for corporate directory purposes such as reporting relationships, and this could in turn enable real-time organizational charts

·        The product could offer links to a company’s payroll system (as many internal company directories already do), to help insure even higher levels of accuracy

And that’s just a starting list. Indeed, an enormously powerful product platform exists for LinkedIn to exploit with only some additional programming effort. And this product, properly evolved, is certainly one LinkedIn could charge for. No company wants to maintain its own internal directory if it can avoid doing so, and LinkedIn would bring to the table features and functionality no company could duplicate on its own because of its connections data.

Best of all, as companies adopt LinkedIn as their internal directory platform, LinkedIn automatically becomes a stronger database as a result. Employees who haven’t yet built a profile will do so; and those with existing profiles will be motivated if not required to keep them current.

Sure, there are some data governance issues that will need to be addressed and doubtless some technological and structural bumps in the road will emerge; as the saying goes, “hierarchies are hell.” But these issues will come to the fore because LinkedIn is simultaneously becoming more important and the end result of that is a more comprehensive and accurate database for LinkedIn, that will give it the basis to chase even more data-driven workflow opportunities.

If LinkedIn wants to offer high quality user-maintained data that gets accessed frequently, there’s no better way than to help it enable daily business activities. LinkedIn Lookup can be an important first start in this direction.

How Do You Rate?

Morningstar, the financial information giant, today announced that it will be licensing a ratings system from Sustainalytics, a Dutch company that assesses and rates public companies along three dimensions: environmental and social responsibility and governance. Morningstar will adapt this methodology and apply it to mutual funds.

Why the rush by Morningstar to add still more ratings to its data platform? And why license a ratings system when Morningstar already has demonstrated expertise in this area? Indeed, Morningstar has been rating mutual funds on their stewardship (akin to governance) for a number of years now.

The answer, in a word, is that ratings systems are hot. While they don’t look like much on the surface, they offer to users what they most want today: fast answers. You could even go so far as to say that the other reason ratings system are so popular is that they do the research – if not the thinking – for you.

Most importantly of all from a data perspective, a ratings system provides a consistent, normalized and sortable data point. This is especially valuable in the investment world, which is in the business of finding needles in haystacks. Ratings systems and other filters significantly streamline this process.

Imagine if someone asked to you identify the ten best restaurants in Dallas. Without Yelp and Zagat and the other existing restaurant rating services, this would be a nearly impossible task, particularly if you were looking for a comprehensive and objective answer. But these services in effect conduct mass-scale surveys, asking people to condense their opinions of restaurants into a predefined ratings scale. This user-generated approach to ratings has all sorts of imperfections, but most people believe that with enough people participating, the truth will present itself.

A step up from these open surveys are the professionally administered ratings systems. These distinguish themselves by identifying and rating companies against a fixed set of criteria. The goal of the exercise is to be objective as possible. That’s why data are used in place of opinions whenever possible. The more rigorous the system, the more valuable it tends to be. That’s because in addition to being normalized and consistent, these ratings systems allow you to make dependable comparisons. Companies rated “A,” for example, are all rated that way because they met a certain specified set of criteria. That means you can place more trust in the ratings system.

Interestingly, most ratings systems happily publish their underlying criteria and ratings methodologies. While this might seem to be their highly proprietary “secret sauce,” the reality is that nobody wants to undertake the same laborious ratings work if somebody else has done it, and publicizing the underlying methodology builds credibility and trust. In fact, the underlying methodology of most professional rating systems is central to their marketing efforts.

Rating systems reflect the fundamental shift we are seeing from data publishers selling vast piles of raw data to high value, more analytical datasets. The next opportunity is to actually do the analysis for them.

You can learn more about how publishers are using their data to produce a wide range of high value products at this year's Business Information and Media Summit. Hope to see you there!

Taking on LinkedIn

I read a fascinating blog post yesterday by  venture capitalist Hunter Walk musing how (or indeed if) there might be some way to compete with LinkedIn. In addition to Walk’s insights, the post attracted a number of comments from other venture capitalists and entrepreneurs. Apparently, taking on LinkedIn is a growing topic of discussion, at least in Silicon Valley.

The post discusses a number of different approaches:

·        Vertical Markets – could one create a better version of LinkedIn for specific vertical markets? The post doesn’t dismiss this as a potentially viable approach, but does correctly note that simply imitating LinkedIn isn’t likely to work.

·        Project Focus – LinkedIn is designed around the traditional resume and with that comes the expectation of fixed employment at specific companies for fixed periods of time. There are some who are speculating that the growing “gig economy” is creating a need for individuals to showcase what they’ve worked on as opposed to where they have worked. I would argue that Houzz, the wildly successful site for architects and designers to display their projects, is in effect a vertical and project-focused version of LinkedIn, optimized for a specific market and its way of doing business.

·        Data Verification – All the information on LinkedIn is user generated. That used to be considered a feature; now some are suggesting it’s a bug. My question here is how many people want/need verified data badly enough to justify ripping up the existing LinkedIn model?

·        Public and Private Data Control. There are some who suggest that there is room for a LinkedIn competitor that gives users more control over who sees their personal details, presumably at a fairly granular level. This is an interesting concept, but how much more personal information would people put online if they had more control? This new service would quickly start to bleed into Twitter and Facebook. That might sound like a big opportunity, but to me it sounds like a big mess, raising issues about separation of one’s business and personal life that I don’t think anyone has figured out yet.

·        Transactional. I’m a huge fan of B2B marketplaces, but the notion of essentially putting a “buy” button on people’s resumes strikes me as a limited opportunity. There are a very limited number of jobs where the work is project-based and people are hired strictly based on their skillsets. In addition, I think if you opt for this model, you necessarily have to fold in the data verification model as well because trust becomes paramount.

These are all interesting concepts, but they all come with issues. The biggest opportunity (and exposure) for LinkedIn is that it exists outside of workflow. If your job doesn’t involve hiring people, you likely don’t interact with LinkedIn too frequently. But what I’ve realized over time is that LinkedIn has become my Rolodex. If this is true for lots of other people (and I suspect it is), then LinkedIn needs to focus on better email integration and even more importantly, a light contact management capability. Why should I use a separate CRM system (which more likely than not is sucking limited data in from LinkedIn already), when I could keep all my contact notes in one central place in the cloud? This, by the way, is something that LinkedIn could sell as a subscription service.

Right now, all of this is just talk and conjecture, but it’s useful to note that in many respects, LinkedIn is no different from most other commercial data products.