Get Out of Your Data Silo Mindset

For decades many businesses, especially the larger, have operated in silos. No more so when it came to the information they created; finance, operations, sales, marketing. Each department head knew that information is power. It can help them retain their job, increase office political clout and ensure budget approvals. The very thought of sharing corporate information to other industries was heresy. Some might be shared down the supply chain, but only to drive costs lower or improve efficiencies. Enterprise platforms like SAP have helped break some of these barriers down, but not enough for todays world. And such siloing of information may be more dangerous than ever before. Why?
Sharing is Caring. And Profitable.
It’s an adage that many a parent teaches their children. In the business sense, sharing is caring can mean more profit and greater office political clout. As our world has become more interconnected not just through the internet and communications technologies, but through trade agreements and multinational supply chains. Industries are generating more data than ever before and that is only growing. As a result, more information needs to be shared across value chains.
Beyond Internal and External Silos
It is a shift in corporate culture to think of sharing more data between departments. It’s one of the major things I deal with in regards to infonomics consulting. It is entirely another proposition for a company to consider sharing information, or even selling it (licensing) to another company in another industry.
For companies that leverage Big Data as part of their analytics, they know that it is a variety of data that is a key component to a successful analytics project. A tension arises when the company doing the analytics wants data from another company and pursues getting it, yet thinks of its own data as special and proprietary to them.
It’s All About the Derivative
The reason another department may want data internally or another company in another industry wants your data is not for your data. They want the resulting derivative that comes from integrating your data. That is a derivative that will help them. If it helps them, it will most likely help you.
Siloing information in today’s increasingly analytics driven world is no longer the power play it once was. Internally, externally, through the supply chain; sharing data can be more beneficial.
How do you think about data sharing in your company or with another company?

What “Data is the New Oil” Means

Just over a year ago Wired magazine proclaimed data is the new oil. Just a few weeks ago The Economist magazine reinforced this statement. It’s true. But few understand what this actually means. So let’s unpack what is meant by data as the new oil, where we are and where we need to go.
Old School Data Brokerage
When most people think of buying and selling data, they tend to think of email lists or financial data such as consumer spending habits. These types of data have been traded for decades and it’s a multi-billion dollar industry. But that’s the tip of the iceberg and it’s the old school of data brokering.
All The Other Data
As most readers will know, just about anything and everything is collecting data these days. From drones and satellites to sensors in home thermostats, cars and manufacturing equipment. Anything in the Internet-of-Things (IoT) and Industrial-Internet-of-Things (IIoT) world collects some type of data. For the most part, the creator of the device collects the data for themselves. To improve their product or provide the data in a cleaned format for the user of the product.
Why Different Types of Data Are Valuable
A business intelligence analyst will ingest a variety of data sources to arrive at insights that can help their company find a competitive edge or new opportunity, as one example. For Big Data projects, it is the variety of data that makes the most value to gain insights. As analytics tools advance and more companies adopt Big Data analytics, more and more types of data will be needed. For instance, we recently in-licensed HVAC data for an elevator manufacturer running a Big Data project. They used all kinds of data including HVAC, weather and traffic signal data.
Setting a Value on Data | Infonomics
Right now, there really isn’t a standard methodology for placing a value on different types of data. For email marketing lists, this is fairly easy because there is a history. But what about SCADA data from a robot on a plant floor that makes brakes for cars?
This nascent area of data valuation or placing economic value to data is called “infonomics.” There are many variables that come into play. The primary being that you can’t “buy” or “sell” data sets. You can only in or out license them. Some data expires quickly, some increases in value. The value of the data is relevant to time, place, volume and need. The in-licensor (buyer) of data also doesn’t really care about the data they care about the derivative.
Why Data is the New Oil
As more and more companies need varieties of data to run analytics on for insights, they will look for ways to get that data. This may be through data for data trades, short and long term licensing (such as subscription) or even buying a company for the data it produces; this is why Microsoft bought LinkedIn and IBM bought the Weather Network. They want the data. Microsoft bought LinkedIn for $26 Billion on revenues of $3.2 Billion.
Data is the new oil because it drives product development, competitive insights, mergers and acquisitions, product development and more. It’s why we started DataTradr and it’s an exciting time.
What do you think?

Sorry, But Your Data Isn’t That Special

Ask any company and most all of them will say that information is their biggest asset. Yet there really isn’t a way to put information assets on the balance sheet other than “goodwill” and that’s a very malleable number at best. The other issue is that companies feel that all their data is proprietary and needs to stay strictly in-house. This is known as “dark data” or the data that you have to keep, but think you can’t do anything with, or won’t because it’s top secret, super special.
No One Really Cares About Your Data
Certainly some of your information is proprietary and highly confidential, but based on our experience, that’s only about 15% of your overall information you collect. That other 85% or so? It’s either data exhaust (data that is collected but meaningless to your business) or tertiary data that really isn’t part of your secret sauce.

It’s All About The Derivative
A company that may in-licence (buy) your exhaust or tertiary data actually doesn’t even care about your data in the context that you do. If they are licensing your data, it is likely for a Big Data or advanced analytics project, where the variety of data is key. They are also likely to be buying or licensing all kinds of other data. What’s important to them is the information derivative of the data.
Changing How You Think About Dark Data
The field of “infonomics” or assigning economic value to data, is still nascent. We’ve already set precedent by helping agricultural, manufacturing and automotive companies in/out license their data. It takes a bit of a mind shift on how you see your data as a revenue source beyond just your current business model. But doing so can help lower or zero out the costs of your data costs.

It’s 3AM, Do You Know Where Your Data Is?

There’s a good chance that if you’re reading this article, you’re reading it on a smartphone or tablet. It’s also likely that you have a number of apps on these devices. Maybe you have some health apps that tie into a FitBit or similar device. You know you’re sending data to those app developers and to Apple or Google or whoever. Maybe you have a Nest thermostat at home as well. A new car with built-in Carplay or GPS as well? You, are a data collection machine. So are hundreds of millions of others. But that’s alright, the government has privacy laws. The EU government probably now has the toughest privacy legislations in place in the world. While that’s good, it may be difficult to enforce, let alone prosecute.
The Global Data Privacy Conundrum
We are collecting such massive amounts of data today. More than in the history of mankind. And it’s entirely borderless. It is reasonable to argue that every big tech company from Apple to Google, Microsoft, IBM, Samsung and so on, are all in violation of privacy laws in many countries. Not intentionally. That’s the way it is in a hyperconnected world.
Toss in the Internet of Things
As we integrate sensors into more and more devices and appliances, ever more data is collected. This is the Internet of Things and there are estimates that already nearly 7 Billion devices are connected and Cisco predicts 1 trillion devices will be connected by 2025 when we include the industrial Internet of Things.
Then There’s The Hackers
We can’t forget all that data that has been and will be stolen. Most of the time it’s personal data that is stolen and sold that contains access to your financial information. In time, that may change to household information to hold your connected house hostage for ransom or health data for nefarious purposes.
The Challenge for Governments and Companies
All of this collecting and sharing of data will pose huge problems for both industry and government. While the likes of Apple and Google may be able to set terms on the use of data from their devices to app developers, it can become difficult when aggregate data is resold by an app developer. Or a company buys a lot of data from various sources for Big Data projects. Fortunately there are advances in ways that data can be transferred with secure tokens so it remains anonymous and can be extremely difficult to unravel unless you have the key.
For governments, the challenge will be to track where the data goes and who’s sending it around. At what point of the flow of data is a company responsible? How do governments enforce privacy laws when outside their jurisdiction? The EU views privacy differently from Canada and America. Multinational corporations move data around constantly; so how does this impact operations?
From Here
There are no clear or easy answers. All we can say is that more data will be generated and it will move all over the world. Tracing its flow will be ever more complex and difficult. As part of privacy laws we may likely see ways that governments will enshrine human rights on personal data. That will work in democracies, but may be difficult in less than democratic nations and those with poor human rights records.
Do you know where your data is?

Considerations for Selling Industrial Data

Selling exhaust data or data that you generate for purpose can be re-sold. Many times over and sometimes to a most unexpected buyer. Selling data can help to offset the costs of operating your data warehousing as well. We look at some steps you can take when considering if you can or should sell your data.

  1. What Data to Sell: This can be exhaust data or specific data formats, say perhaps, from line robots on the floor. Or perhaps HVAC data from facility operations. The first step is deciding what data you might sell.
  2. Privacy: If you deal in data that can identify people, you will need to ensure the data is anonymized (we don’t deal with human identifiable data such as marketing lists or health.) When selling these types of data, you’ll need to ensure the buyer isn’t using it in a way that can identify people. So ensure you have an indemnification clause in any sales contract.
  3. Who Not to Sell To: You may not want your data to be used by a competitor, so take steps to ensure whoever is brokering your data or whom you sell it to, is not a competitor.
  4. Price: This is a moving target. Based on our experience most industrial data has to sell in terms of volume. We’ve seen prices around $800 for 3Gb of SCADA data and as high as $7,500 for 1Tb of an operating line of data. Which brings us to the next step;
  5. Preparing the Data: Once you’ve identified the types of data you could sell, it’s good to partition that data away from your primary storage and management. Put it in a container. Leave it. We don’t recommend cleaning as you can never be sure of who will want the data and in what degree of structure. You can clean it when there’s buyer, if they want.
  6. Contracts: You can prepare your own contracts, but a good data broker will have contracts established. They should also ensure your data is sold to a reputable buyer and protect you to some degree.
  7. Regulatory: Make sure you’re in compliance with the legal right to sell your data or that it won’t cause any concerns with governance and the law.


There are a few more things to consider, but these can get you started down the road to considering the sale of your data. We often work with companies to help them assess what data they can sell and put a plan in place to prepare it. Ideally you want to keep costs at a minimum for preparing the data for sale.