An undeserved focus on data-making, not sense-making

The incredible amounts of data being produced by global consumers is accountable to two trends, one more obvious than the other. The first trend is the natural growth of populations, more specifically populations who seek to consume apps, services, and luxuries in developed countries. The second trend is the cross-industry obsession with data, and using it to make more calculating and algorithmic business insights. Simply put, more people means more unique data producers. But pursuing an obsession in “big data” means the further quantification of actions and behavior, perhaps to a point where data sources overlap, rendering large amounts of data collection unnecessary, irrelevant and costly.

This trend of over-quantification was personified in the July issue of Fast Company concerning General Electric’s crusade to outfit legacy technology such as locomotives and turbines with digital sensors:

But now that it is also a rolling electronic laboratory, a [GE] locomotive’s insides contain 6.7 miles of wiring and 250 sensors that put out 9 million data points an hour.

Few people or companies find themselves in the position where sticking a hundred sensors on everything that moves is a viable solution. And while having more datapoints to observe is always a good thing in terms of experiments (statistically, the more observations n renders a more normalized distribution!), the reality is we are usually only given the opportunity to grab a limited amount of data due to constraints in time, resources, or access. How can we make this grab count, so we get away with the jewels and not just the cash from the register?

Think about source

A key to overcoming information overload is know exactly where to look when faced with a challenge. This requires a practiced method of sourcing data and resources; thinking about where things come from, collecting them in a sensible manner, and maintaining a personal frame of thought to maintain these sources. While “sourcing” may mean more about one thing to a supply chain expert than it does to an organic restauranteur, many key components make up a similar thought process. This approach—essentially a virtual database, in your mind!— has been productive tool in my management of projects personal or team-based.

Mental metadata

Think of all the qualities we describe to a product: brand, color, manufacturer, where it belongs in the home… The possibilities are endless! Jony Ive elegantly describes the process of ascribing these features to an object in the 2010 film Objectified:

When you see an object, you make so many assumptions about that object in seconds: what it does, how well it’s going to do it, how heavy it is, how much you think it should cost. The object testifies to the people that conceived it, thought about it, developed it, manufactured it. Ranging from issues of form to material, to its architecture, to how it connects to you, how you touch it, how you hold it. Every object, intentional or not, speaks to who put it there.

With an object like a book, a book should mean much more to you than its contents: it should also bring notions of genre, writing style, author, cover design, and perhaps even more personal connections made during your time reading it. The idea here is to perceive objects for more than their implicit function, and to maintain additional qualities in our perception of the object. Keeping our thoughts organized in this fashion will help develop a mental filesystem. Our perceptions can be tagged like a file for better, faster referencing in the future.

Specify questions with scope

Try strengthening your search for information by determining a more specific scope of what you’re asking. In a team, this is as easy as the difference between asking “What was added to the team notes last night?” and asking “Were the summaries of the case dockets added to the team notes last night?” The first way of asking may solicit a more nebulous response, which can produce less descriptive answers in the overall conversation. The other way of asking is more direct and has a better possibility to stem into more detailed questions and render a productive conversation.

Asking questions with a specific scope applies to how we ask questions online as well. Take Google for example: there is so much data out there that simple Google searches render less and less useful info for our needs, or all the useful info is left on a distant page in the thousands of results returned by the Google search. Google is basically asking “What are you looking for?” and by giving it a query with a well-defined scope, it will fetch better results. For instance, say that you know you want a PDF file of a report on climate change in California. You don’t know what the best result will be exactly or specifically, but you know that the best one will be from a verified team of researchers and their research is subject to academic oversight. In Google, you will want to type in:

filetype:pdf “climate change” “california” report .edu

This will return PDF files that are referred to as reports and that are pertinent to the phrases “climate change,” “California,” with references to .edu domains. While this is a technique very specific to Google, it is a very good example of the methodology behind defining the scope of a question. The idea here is that the scope of your question can render better results from people and machines, and will help you ask questions in a framework of blocks. Ask what is answerable, then ask what is next-to-answerable, in a series that not only shows project growth but provides tangible benchmarks on your train of thought and problem-solving process.

Be relational

Working in a newsroom, you’ll find that many journalists follow a beat, actively pursuing leads pertaining to a certain topic such as public safety or local politics. Beat journalists are experts in knowing the more nuanced aspects of their field, such as police radio codes or local election laws. This structure of specilizing is a structure found in most teams, and we find that our interests take our careers in certain specializations. A neat approach when sourcing material can be fashioned by thinking like a beat journalist, or rather, by keeping an eye out for facts that may only be obvious to those experts in touch with the subtle attractions of the field. For instance, it may not be obvious, but unsurprising, to you that the UN, US Government, and many other administrations publish all sorts of government data online. It makes sense now that you know, but do you know where it can be found? A lot of economists who seek government data know that adding “data.” to the beginning of a website URL will render a special page where that organization publishes its public datasets (data.ca.gov accessed from ca.gov or data.worldbank.org accessed from worldbank.org). Sourcing techniques like this are very effective and direct to the original publisher of the source, but would probably only be known to wonks and experts who maintain a close interest in these nuances.

Use your mental database to be relational in these matters; the search for these subtle techniques can be done manually, but by mentally relating new information to like information you already posses we can figure out these techniques on our own. Let’s take the “data.” example. Initiatives in adding “data.” pages are a function of our society: we live in a society where industries are obsessed with data procurement, and thus industry professionals expect companies and institutions to publish public data to fulfill that obsession. We also live in a society where there is a culture with web development and programming, and those industry professionals expect relevant companies to provide documentation and kits in using their products. So, just like how adding “data.” to the beginning of a website URL can render a page of datasets from that website, adding “developer.” to the beginning of a website URL can provide a page dedicated with web developer documentation for that same site (developer.google.com, developer.facebook.com). The idea here is to apply what may be true in one branch of your working knowledge to a completely different branch. At the simplest level, we do this very commonly with analogies. But at this higher level, making relational connections can be an awesome way to obtain a new perspective, and approach problems with a new frame of mind.

Open your mind!

Shortly said, this is all just a practice in being aware, detail-oriented, and relational. This can help us overcome very modern challenges such as information overload and an abundance of irrelevant data. My biggest fear going forward is that our society will become to focused on the consumption of things—be it datapoints, the Kardashians, or CNN talking points— rather than the unique points of view and perspectives. To fight this, we should all wonder: where do things come from? We should not blindly accept anonymous origins but rather investigate for holistic understandings. The manner in which we obtain things can define how we will come to use them. In that respect, it is important to have a tangible process when it comes sourcing materials. Not only will it build your own mental capacity (mind database!), it will provide a clear communicable train of thought for teammates to understand and those to follow in the future.