Building a strong foundation for the future

Building a strong foundation for the future

Mirko C. Obendorfer¹ & David F. Ridderikhoff²
¹Toronto Hydro-Electric System Ltd.
500 Commissioners Street, Toronto, Ontario, M4M 3N7

²IPID Services Inc.
PMB 242, 1389 US 127S, Suite C, Frankfort, Kentucky, 40601-4385

Many papers and articles have been written, and will be written, on the subject of the power of geospatial technology and it’s positive impact on the overall corporate decision making. Given the fact that 80%, or more, of data relates to location and, the ever increasing functional and inter-operable capabilities of geospatial solutions, we should not be surprised that what used to be predominantly an “island of automation” is rapidly becoming a major component of the “enterprise” solution.

This paper however, attempts to address some common and basic issues which, if considered, would increase your chances of creating a strong foundation for the future automation initiatives within your enterprise. The focal point of our discussions will concentrate on the project organization, processes, data and decision making relative to or plant assets; the examples will be from an electrical distribution utility environment, but may apply to other utilities and organizations.

Project Organization
A lot has been said that technology alone can not, and does not ensure success. Considering the functionality, “openness & integratebility” of current geospatial technology offerings, most key strategic automation initiatives have a large degree of dependencies, which require corporate coordination and prioritization. Also, since most of automation initiatives are in fact “business transformation” initiatives, it would seem logical that a senior executive sponsor for all automation initiatives be, for example, a VP Business Transformation, reporting to the President or a Senior VP of a given business unit. Similarly, since most of the key automation projects require support and participation by the same SME’s (i.e. Subject Matter Experts), the effective project organization may look as shown in Figure 1.

Figure 1: Organization for corporation Business Transformation Initiatives

In the opinion of the author(s), the “type” of competencies of key people, and their origin within the organization has a great deal of impact on the overall acceptance and success of these projects.

Business transformation processes
Most business transformations processes cross traditional departmental mandates. Therefore, in order to avoid “islands of automation” of the past, “process-centric” approach to automation initiatives is recommended. Furthermore, there is a logical process when developing/deploying automated solutions (i.e. “one has to crawl before one can walk, run or fly”).

Figure 2 describes “common sense” building blocks required when developing an “automated/integrated working environment”.

Figure 2: Building blocks for an “automated working environment”

The Figure 2 above shows the activities that have to be addressed/resolved (i.e. landbase, network model, data migration/conversion) in a logical order, before or in parallel with process automation phase (i.e. “core” applications), followed by the development/deployment of “analytical” applications.

Data requirements
The methodology and issues related to data architecture has been, is being and will be discussed in many other papers and articles for example:

From tiles & layers to seamless spatial databases
From spatial features-centered to object-centered
From procedural programming to object-orientation
From proprietary spatial formats to RDBMS
Etc. etc.

In this paper, the authors wish to emphasize the importance of the following:

Data integrity (i.e. obtain/capture data from a source that is mandated and competent to provide specific data)
Data timelines (i.e. ensure as close to immediate access to all data for all
Avoid duplication of effort)
Ensure only critical data is captured

Since your Geospatially Enabled Asset Registry is in fact the “home” for all your plant (and related) data, it is recommended to create, and subsequently to maintain, an “Data Inventory Matrix”. This matrix would be a “living document” showing all your data in your corporate Asset Registry, including graphic symbology and attributes, for all data classifications (i.e. from Landbase to Administrative, Structures, Electrical, Streetlighting, Fiber-optics, etc.) This document would help you when prioritizing the development of your “analytical” applications since it is obvious that the application can not run without data. Similarly, it would readily show you which data elements are available and which new ones have to be captured before any given application could be functional.

Conclusion
Just a few logical, common sense issues have been covered in this paper. They should help you in the creation of a stronger foundation for your automated working environment, using geospatial and related technology. We should all attempt to reverse some of the findings by industry observers and analysts, for example:

42% of corporate information technology projects were abandoned before completion
75% of re-engineering projects fail to deliver the results they promise.
Etc. etc.

By defining business objective(s), realistic project planning, internal project coordination, participation by the right type of people, application of some old fashioned logic and common sense, we should be able to reverse some of the above stated statistics.