Is Data an Asset? The importance of the metaphors we use for data


The metaphors we choose to describe our data are important, for they can either open up the potential for understanding and insight, or they can limit our ability to effectively extract all the value our data may hold.  Consisting as it does of nothing but electric potentials, or variations in voltages and frequencies, when speaking about data we are forced out of necessity to speak in metaphor.  Even our cherished 1’s and 0’s are metaphors for the underlying electromagnetic reality, and in going from bits to bytes we’re already stacking metaphors on top of metaphors.

Let’s start with a metaphor I must see at least once a week in articles, blogs, white papers and webinars: data as an asset.  As a starting point, I’m okay with this, it seems an apt and accurate metaphor for data.  But let’s nail this “asset” terminology down a bit more.  If data is an asset, what sort of asset might that be?

big_data_linkedin3Is it a fixed asset like plant, property and equipment?  Meaning, is it like the other productive operational assets that can be leveraged as tools?  I suppose one could see it that way, but I find that particular metaphor hard to work with.

Moving higher up the balance sheet – is data like inventory?  As with inventory, we most certainly warehouse data, in, what else, data warehouses and data marts.  I’m even willing to take this inventory analogy one step further and say that we can subdivide our data-inventory into ‘raw material’, ‘work-in-process’ (WIP), and ‘finished goods’ data, adding value at each step as we integrate our data silos, sort, score and store it, or extract, transform, and load (ETL) the data into ever more accessible and valuable formats.  Yes, I think inventory might be a good one.

But why leave out the King of Assets – Cash; can data be like cash, like a currency?  Can data share a common definition with money – as a medium of exchange?  In many cases, this would appear to be the perfect analogy.  The 1’s and 0’s traveling down the wire or through the ether have no specific value on their own (how much would you pay for a billion "1's"?), but instead represents a transfer of value from one server/client/device/sensor to another.  Unlike inventory, which has direct value even if it’s just sitting there, cash is more a store of relative value, itself unproductive but capable of being exchanged for or between productive assets and processes.  Oooh, I like that metaphor too – data as a medium of exchange.

But just as oranges are not the only fruit, business is not the only source of good metaphors.  Biology presents us with another set of metaphorical options, from glucose to hormones to hemoglobin.  Is data a source of energy with which to run our business, and in the process converting the relatively large sugar molecule glucose (C6H12O6,) into the many smaller sugar molecules which our cells can actually consume, extracting valuable energy and information along the way?  Has data become the oxygen of your business processes, without which it begins to suffer brain damage after 90 seconds of deprivation?  Or is data like the hundreds of hormones that course through our bloodstream, a refined and elegant balance of feedback and control, triggering site/organ/cell specific reactions when they reach their destination?

Those are all good, but when it comes to biology you can’t leave without considering the granddaddy of all data metaphors – the nervous system.  Is your data network a nervous system for your organization, as Brian Arthur postulated in “The Second Economy”, the underlying central nervous system that controls the physical systems of bone / muscle / sinew (i.e. inventory / production / logistics)?  As Arthur emphasizes in his classic paper, the two become so entwined and interdependent that to talk about the physical system separate from its data-based nervous system is to talk nonsense.  There are processes like airline ticketing that without the supporting data simply cannot be said to independently exist.

Lastly, we get to those businesses that are nothing but data.  Google.  Facebook.  Netflix.  With physical checks largely gone from the process, all that remains for the financial services industry to move completely into the ether is the day when cash and coins are replaced with electric potentials on personal smart devices / cards.  The related metaphor for these All-data, All-the-time businesses might be the Holographic Universe, where the physical universe is depicted as nothing but the data it takes to represent it.

To reiterate the point I made at the start, the value you can extract from your data depends on how you see it, and how you see it could be a limiting factor in how you use it.  If data is like inventory in a warehouse, don’t leave out those analytic processes, such as data mining, visualization and exploration, and text analytics that can add value to that data as it moves from source to warehouse to user (i.e. raw material to WIP to finished goods).  And more than just its static value, consider also its dynamic value in motion with the application of event stream processing and decision management.  Is customer segmentation data the oxygen and glucose that power your sales engine?  And lastly, if your business is your data is your business, its security and protection could be a matter of life and death.

I know I’m going to hate myself in the morning for reusing this already overused cliché, but if all you have is a data warehouse, then every data problem looks like inventory.  Instead, bring vitality to your business by bringing your data metaphors to life.


About Author

Leo Sadovy

Marketing Director

Leo Sadovy currently manages the Analytics Thought Leadership Program at SAS, enabling SAS’ thought leaders in being a catalyst for conversation and in sharing a vision and opinions that matter via excellence in storytelling that address our clients’ business issues. Previously at SAS Leo handled marketing for Analytic Business Solutions such as performance management, manufacturing and supply chain. Before joining SAS, he spent seven years as Vice-President of Finance for a North American division of Fujitsu, managing a team focused on commercial operations, alliance partnerships, and strategic planning. Prior to Fujitsu, Leo was with Digital Equipment Corporation for eight years in financial management and sales. He started his management career in laser optics fabrication for Spectra-Physics and later moved into a finance position at the General Dynamics F-16 fighter plant in Fort Worth, Texas. He has a Masters in Analytics, an MBA in Finance, a Bachelor’s in Marketing, and is a SAS Certified Data Scientist and Certified AI and Machine Learning Professional. He and his wife Ellen live in North Carolina with their engineering graduate children, and among his unique life experiences he can count a singing performance at Carnegie Hall.

1 Comment

  1. Martin Hartken on

    Great article containing an interesting remarks regarding the question "is data an asset", proved with well-chosen metaphors.

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