Topic #3 - Information Architecture

The State of Information Architecture

In Walker (2015), he surveys a group of around 40 enterprises from all different industries, sizes, maturity levels and geographies about the state of their information architecture. The results are interesting and even spot on in terms of my organization.

The first question deals with the level of impact Enterprise Information Architecture (EIA) has delivering business driven outcomes. The chart below from the article shows that while 90% think it is "ideal" or "significant".



I would agree that we have this same kind of thought in our organization. However, I think we also have trouble understanding the impact that good information architecture would have on our organization. We have completed assessment from Gartner & Hackett and both a reviled that we need to have better data management.

The second question asked about the current state of the enterprises' EIA practice. In the article, it states that "only 16% felt that EIA as a practice had been fully implemented or mostly implemented.



Again I would agree with this from our company prospective. We have not implemented an EIA program. I will be working with our organization to start looking at how we implement an EIA. We have tried to do some governance activities in the past around data management and they have been less than successful. I think if we had a larger of view of EIA then the governance program would be easier to tie directly back to why we are trying to implement such controls.

Walker (2015), goes on to ask what level of impact does EIA have on major efforts like Big Data and traditional MDM and 96% of respondents answered "ideal" or "significant". Again after reviewing other notes around EIA, I also feel that a good EIA program could have significant impact on those efforts. It seems to give everyone a path to walk towards a common goal and highlights the importance of good information management.

The final question was centered on trying to agree on a good definition for EAI. According to the article, "60% of respondents they felt that this definition represented enterprise information architecture:

Information Architecture is an aspect of enterprise architecture that enables an information strategy or business solution through the definition of the company’s business information assets, their sources, structure, classification and associations that will prescribe the required application architecture and technical capabilities."

I feel that that is an adequate definition for EIA.

It is clear that EIA is important and we need to be focusing on how to develop EIA in our organizations. Walker (2014), finishes the article with an important summary:

"However what this data does tell us is that while EIA is important (or maybe even critical) we still don’t have:

• A collection of proven practices 
• The right structures and framing for the EIA space 
• Proven methods that result in predicable and predictable outcomes 
• A clear organizational and competency structure for EIAs" 

Reference
Walker, Mike (2014). The State of Enterprise Information Architecture. Retrieved September 23rd, 2016 from http://blogs.gartner.com/mike-walker/2014/07/23/the-state-of-enterprise-information-architecture/

Data is NOT Information
In the article from Aitken (2015), he attempts to clarify why data is not information. I really like his example of how data without context has no value. The example is this, "take a column of floating point values in a database table – while a developer might be able to discern something about the meaning of the values by physically inspecting the database table and column names – the values are meaningless to the naive user until they are presented on a computer’s screen in a field labelled 'Cholesterol level (mg/dL):'"

I believe we have the issue that data loses its context shortly after it leaves the source system. While the data may be extracted with column names like indicated above it doesn’t take much for someone to manipulate those column names and give the data new meaning in a new context. We have a classic example with the "number of customers" question. Being a utility company, I would say the number of customers would be the number of service points that we currently maintain. Those service points might be active or inactive so not all service points would be related to an active customer. Another point of confusion is that if you don't spell out that one customer can be responsible for multiple service points you can end up with too many or too few customers. So for this example the context should be "customers as number of service points", however many times the number gets labeled just as customer losing the full context of the data.

I like the idea of information asset as spelled out by Aitken (2015). He states that like other assets information assets have value and a life-cycle. I think it is important to label the value of information in terms of data otherwise we end up just storing everything because "storage is cheap." The idea that information has a life-cycle is an interesting concept and I would like to explore that further in our organization. I think the idea certainly is valid as we have data like customer that expires after a certain period in time. Once we have a customer they might not always be a customer so at some point that information would expire.

I'm going to be spending time with my team to help build up the idea of EIA and how we improve our understanding of information within our enterprise.

Reference
Aitken, Chris (2015). Data is NOT Information. Retrieved September 23rd, 2016 from http://enterprisearchitects.com/data-is-not-information/

Why EIA Matters
I have read a couple blog articles from Seth Earley and like the content he provides. In Earley (2013), he talks about getting back to the basics and talks about taxonomy. He continues to talk about two core artifacts needed to improve EIA. Those two artifacts being a good enterprise taxonomy framework and a domain model. After reading a few of his articles on taxonomies those two artifacts started to make more sense.

In our organization we have a good understanding of what we do in various area, however we lack an overall model of what high-level interactions are needed to run the business. I feel we have maybe approach our data governance from a slightly wrong angle. I think we need to address the overall view of the business and build out our enterprise taxonomy and establish a domain model that represents our enterprise. I think doing this will help move our data governance efforts ahead in a way we haven't seen before.

In Earley (2015), Earley tries to reestablish the definition of a taxonomy. I agree with his statement as an IT professional it is way too easy to get into the weeds of the data of an application or system instead of trying to address the higher level abstract perspective needed to build an enterprise taxonomy. This article help me understand how to look at an enterprise taxonomy and how to potentially use it at my organization.

Reference
Earley, Seth (2013), Why Enterprise Information Architecture Matters. Retrieved September 23rd, 2016 from http://www.earley.com/blog/why-enterprise-information-architecture-matters

Earley, Seth (2015), Why Information Taxonomy Must Represent the Landscape of the Business. Retrieved September 25th, 2016 from http://www.earley.com/blog/why-information-taxonomy-must-represent-landscape-business