Why we collect data . . what we need to do with it


Data is everywhere.

We collect data “for the record”, we collect data for use by predictive analytics algorithms and we collect data for use by humans and machines when making decisions.

Data, by itself, is highly important but not highly useful.

Contrary to popular opinion, unstructured data does not necessarily have to transition to structured data.

I will explain.

The usual flowgraph options for data go like this:

  1. Structured data -> data storage -> analysis/organization -> information -> knowledge -> decisions.
  2. Unstructured data \ structured data -> data storage -> analysis/organization -> information -> knowledge -> decisions.
  3. Unstructured data -> data storage -> free-form-searches -> information -> knowledge -> decisions.

All three work, providing the organization has methods, tools and platforms capable of managing the workflow. 

Except that many decision-makers short-circuit the process as follows:

Uninformed state of affairs               -> decisions

Data (structured or unstructured)   -> decisions

Information                                          -> decisions

Legacy knowledge                               -> decisions

My differentiating list for data, information and knowledge is as follows:

Data:                    Data, simply what it is – “. . all we want are the facts, ma’am”.

Information:       Processed, interpreted, or analyzed data.

Knowledge:        Increased level of confidence in Information that builds over
                              time (but can also decline over time).

Now for the explanation of how unstructured data can be as useful, at times, more
useful, than structured data.

Consider the following Strategic Planning platform (i.e. hosting multiple Entities, multiple hierarchies, thousands of data points), all accessible from one computer screen.


3D-Free-Form-Search Knowledgebase

Most corporations review/update their strategic plans at regular intervals (i.e. every 18 months, these days).  Absent ways and means for reviewing ongoing initiatives for their continuing contributions to strategy, the organization reverts to business-as-usual following publication of each strategic plan.

The problems are:

  1. Things change (e.g. changes to implementation priorities, changing customer needs, competitors leapfrogging “innovative” designs that are on the drawing board or in-progress).
  2. Information declines in value and needs periodic refreshing.
  3. Knowledge needs to be upgraded as a result of #2.

If you have experience with auditors or law enforcement investigators, you know that information virtually “leaps off the page” for some of these folks. They sense the need to drill down (e.g. when and where).

One way for non-auditors/non-LE investigators to make better use of information is to make use of 3D free-form-search Knowledgebases (3D-KBs) to launch “what-if” analyses and “connect-the-dots” exercises.

3D-KBs do not need to rely on structured data. Unlike searches across structured data, a free-form-search at a 3D-KB may be able find a phone number that was not properly entered into the “Phone Number” field at a relational database management table.

3D-KBs do not rely on invented “key words” – the search engines scan full text with the result that everything other than “the, and, and but, etc.” becomes a keyword.

Our experience with Strategic Planning Methods, Tools, Platforms

Civerex and its partners Global Initiatives and HNCT are in the business of evolving Infrastructure Protection plans for clients – our process starts with an inventory of all infrastructure/resources for each client.

From there, we assess risks/vulnerabilities, we remediate vulnerabilities, we evolve detection, avoidance, counteraction protocols. This takes each client to a state of “Readiness”.

Over time, we build on Readiness to bring a client to a state of “Resilience” (changes to Readiness as a result of daily scanning the horizon of incidents across the client industry area/geo-location, etc.).

When all of this fails, we move along to a set of protocols for “Recovery”.  The happy scenario is to train on Recovery profiles but never have to invoke them.

Moving Forward

If you want to improve decision-making at your organization, get on board with 3D-KBs. You will need a method, working tools and a platform.

Your options are to invent these out of your ‘garage’ or call us for mentoring.

Our approach to consulting engagements is arrive on site “loaded for bear” (i.e. we do our homework), and we start planning to leave from the time we arrive (i.e. our main deliverable to each client is the transfer of planning expertise and technology).

We do not push “buy-low-sell-high” and we won’t borrow your watch to tell you what time it is.


1 800 529 5355

About kwkeirstead@civerex.com

Management consultant and process control engineer (MSc EE) with a focus on bridging the gap between operations and strategy in the areas of critical infrastructure protection, major crimes case management, healthcare services delivery, and b2b/b2c/b2d transactions. (C) 2010-2021 Karl Walter Keirstead, P. Eng. All rights reserved. The opinions expressed here are those of the author, and are not connected with Jay-Kell Technologies Inc, Civerex Systems Inc. (Canada), Civerex Systems Inc. (USA) or CvX Productions Number of accessing countries 2010-2020 : 168
This entry was posted in #strategy, Corporate Infrastructure Protection, Database Technology, Decision Making, Resource Based View, Strategic Planning. Bookmark the permalink.

2 Responses to Why we collect data . . what we need to do with it

  1. Leon says:

    Walter this is a very comprehensive plan looks like we could do something with this if we could find the right customers.


  2. Thanks,

    Many moving parts, but they all fit together (data, knowledgebases, workflows, methods, tools, platforms).

    I find it fascinating that WordPress is able to interlink related topics, some written years ago – notice just below the “How we collect data . . .” article, that WordPress promotes “More” and wants the reader to look at “Big Data . . (2013) ” and “Theories of the Firm . . (2016).


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