Thought Leadership

Location matters! GIS: more than “just maps”

Uncovering relationships in your data and gaining insights

More than ever, geospatial knowledge is critical to get the insights you need from your data. Although maps are an important data source in GIS, and a way to visualize the results, GIS is about so much more. It is about understanding the dynamic relationships between big volumes of data. It is about being able to geographically track the process of your data measurements in the real world, and in real time. It is about algorithms, data, and models. It is about developing a new way of thinking – a “geospatial way of thinking”. In other words, GIS can help you understand why location matters for your specific business, ultimately helping you to manage your business more efficiently

Uncovering relationships in your data and gaining insights

Rooted in the science of geography, a Geographic Information System (GIS) integrates many types of data. By using maps and 3D scenes, a GIS analyzes spatial location and organizes layers of information into visualizations. A GIS can use any type of information that includes a location component, allowing its users to compare locations of different objects and discover underlaying relationships and connections. For example, by using a GIS, a single map could be created including, on the one hand, sites that are causing pollution (such as factories), and, on the other hand, sites that are sensitive to this pollution (such as lands and rivers). Such a map would be helpful in terms of determining the risk factor of water supplies.

In addition, GIS technology sometimes allows its users to access more detailed information about specific areas on a map. If so, users can get more information about a specific location by just pointing to a single spot on the digital map – the additional information stored in the GIS about that location will then be displayed. This allows, for example, GIS uses to discover how many residents are there in a particular area, what are the facilities available in the area like restaurants, shops, schools etc.

Finding new data sources

Although maps can be great way to output spatial data, they may not be the best input. One of the most common quality issues related to spatial data is the accuracy of locational georeferencing. This is because maps, which are an important data source, represent reality at specific scales – the smaller the scale, the less accurate the location information, and the fewer features that can be represented. To overcome this issue, and thus improve data accuracy, alternative data sources are increasingly being used as input data for GIS. GPS, for example, can provide more accurate geographic referencing, while digital imagery represents a more objective (less interpreted) view on reality. While it is clear that wireless services are going to contribute to location knowledge in many communities, the way in which these communities will use that information, and whether they are already using GIS, will vary.

Developing a “geospatial way of thinking”

Although maps are an important source of data, and a way to visualize results, they are not an organizing principle of geospatial work. Geographic principles need to be applied to algorithms, which can happen in different types of models – whether it concerns analyzing societal behavior or performing a risk analysis, geospatial knowledge is often critical to get a good and clear understanding of the problem. Our way of thinking in terms of data representation is changing, putting “geospatial thinking” at the forefront in our point of view. Algorithms, data, models, etc. should easily be added to any analysis, even without using a GIS-centric system

We used to think in terms of layers of information, stacked and integrated, to form a map. Now, our perspective has changed towards a more “modelling reality” point of view, meaning that we focus more on the relationships between data, which are interrelated and dynamic. With time, and in order to fully integrate GIS into mainstream business applications, we will need to move away from the “map paradigm” that has been the basis of GIS for many years – automating maps has been the primary way in which spatial data have been handled traditionally in GIS. However, new tools are allowing to gather data with more precise locations. In addition, wireless technologies, the Global Positioning System (GPS), and the ability to handle big volumes of data allow to geographically track the process of whatever data that is being measured, whether it concerns stream flows or issued building permits,  in the real world and in real time.

Discovering why location matters

Spatial data have been managed by companies for an awfully long time. Even long before GIS, spatial data where managed for intents and purposes like determining where to drill for oil or monitoring environmental change. It is crucial to understand that most things are spatially referenced – everything happens somewhere. Understanding how this “location component” matters in the conduct of your specific business will help you manage your business more efficiently.

As a leader in Spatial Intelligence, Avineon can assist you in that journey. We have been working with Esri for more than 20 years, offering a full suite of geospatial products and services to our clients in numerous industries, including electric, gas, water, and telecommunication utilities, as well as local, state, and federal government agencies. Our geospatial solutions, consist of data services (like data improvement and maintenance, data modelling, and database management), imagery services (like feature recognition, large-scale and satellite mapping, and land use land cover database production), 3D services (like 3D city modelling, photogrammetric services, photo interpretation, and Lidar classification), and a variety of technical specialties (like specification development, software development, project management, and training).

For more information on our product & services, contact us:

Location matters! GIS: more than “just maps”2020-11-18T06:26:09+00:00

Data Readiness Strategies for Utilities and Telecommunications

Realigning data lifecycle for sustainable value

Data readiness is a critical aspect of digital strategy. Especially within infrastructure-heavy industries, data associated with physical assets and networks in the field can play an important role in generating revenue, delivering customer satisfaction, and serving communities.

ArcFM Go Live Events

Utility and telecommunication companies managing electric, gas, cable, fiber, wireless, water, wastewater, and stormwater systems have, in many cases, successfully employed Geographic Information System (GIS) technology to build and manage their assets and networks. These GIS implementations typically support a wide variety of business and operational processes delivering significant value to the organization.

Need for Digital Models to Operate Flexible, Resilient, and Connected Networks

Shifts in technology, operating requirements, market conditions, regulations, and other factors provide opportunities for utility and telecommunication organizations to modernize and derive more value from the investments made in GIS.

As legacy infrastructure transitions towards smart ecosystems, the data feeds from assets, field workforces, and customer-owned equipment become vital for utilities and telecommunication companies to operate networks in a flexible, resilient, and connected manner systems.

These shifts are driving the need for modernized digital models in GIS that mitigate latency and integrate data efficiently to support business workflows. This need for robust digital models is also on the rise due to the decentralizing paradigm of resource networks across utility and telecommunication industries.

Objectives for Data Readiness

A key objective for many organizations is the expanded use of their GIS platforms by leveraging powerful new capabilities and delivering greater value and experience to their customers, workforce, and communities, as well as improvements in environmental conditions. Implementing such a robust GIS architecture requires accurate, complete, and current data.

The measurement, identification, collection, assessment, maintenance, and governance of spatial data for its highest and best use results in data readiness for the enterprise.

The benefits of data readiness include:

  • Predictability
  • Competitive Resilience
  • Ease of Integration
  • Expanded Use of Technology
  • Greater Return on Investments

The lack of data readiness can result in:

  • Regulatory Violations
  • Process Inefficiencies
  • Disgruntled Workforce
  • Increased Outages
  • Customer Dissatisfaction
  • Slower Growth

Data Readiness Mindset and Approach

Data readiness is a fundamental ingredient of your enterprise’s digital strategy and requires a holistic approach when examining and optimizing the data lifecycle. It can be achieved through the application of a methodology and tools that considers the complete system lifecycle. At Avineon, we subscribe to a methodology of:

  • Avineon’s design approach, supported by our proven tools and processes, enables your team to examine and assess the quality and completeness of current data holdings. It establishes a baseline of the qualitative and quantitative aspects of your data and the augmentation needed to modify the data life cycle towards realizing your digital vision.
  • Data readiness design readies your organization to implement the necessary data quality improvements, which may be carried out by internal staff and/or outside data specialists.
  • With the correct tools and processes in place, implementation prepares your organization to sustain high-quality data that is authoritative and dependable for improved business and operational results.

In light of this, utility and telecommunication companies preparing for any system upgrade or implementation of technology, such as the ArcGIS Utility Network Management extension, must ask themselves two questions with regard to data readiness:

  • Option 1: Should we limit our objective to running data integrity checks to confirm data set is ready to load into the newer version of the data/information model?
  • Option 2: Can we look beyond data integrity to optimize our target data/information model and data management life cycle to maintain continuous data readiness and deliver greater business value through software upgrades?

The tendency to assume data integrity checks (option1) are the only basis for readiness without fully considering the data lifecycle (option2) is a grave misstep in this journey.

The Data Readiness Role in Digital Strategy

There are many forces driving the need for better data. They come from many different stakeholders, users, and systems involved in the data life cycle. Identifying these drivers and opportunities should be a methodical process that results in a comprehensive spatial data strategy for your organization. This diligence may be the most important consideration in your journey to modernize data assets and maximize the value derived from your GIS.

Data readiness strategies should focus on delivering enhanced value through an improved understanding of:

  • What software applications will the data be used with and what are their minimum requirements? Potential applications may include:
    • Editing and field use
    • Asset management
    • Capital improvement planning
    • Advanced system and outage modeling
    • Tracing for network isolations
    • Network modeling and analysis
    • Customer engagement
  • Will the data be used with Esri’s geometric network models, Utility Network models, or other industry models and software?
  • Are there regulatory and reporting requirements that the data must support?
  • Are there local and/or national standards that the data should follow?
  • Does the data need to address industry-specific needs such as:
    • Lead abatement in the water industry
    • Distribution energy resources in the electric industry
    • Smart grid functionality in the electric industry
    • Integrity management in the pipeline industry
    • Growing completion and 5G capabilities in the communications industry
    • Customer integration with smart appliances
    • Active system controls
    • Predictive maintenance
    • Rapid response for outage management
    • Sales and business development

Data Readiness Considerations

As these questions are answered, a natural outcome is a developing consensus on the benefits and ramifications of raising the quality of spatial data. This consensus becomes the foundation for establishing your data readiness initiatives. Potential benefits and ramifications include:

  • Better decision making for short and long term improvements to the systems.
  • Reducing data errors and duplicity, reconciling disparate data sources.
  • Generating new and better products and capabilities with the data and systems.
  • Enhancing access to authoritative data and ease of use.
  • Promoting the integration of standardized data among business systems.
  • Better compliance with required regulatory functions and deliverables.

Spatial Data Strategy

A well-facilitated data strategy that addresses these basic questions leads your organization to:

  • Craft enhanced data life cycle solutions in a collaborative fashion with all stakeholders.
  • Determine what data exists today and what changes are needed for improved operational and business efficiencies.

This strategic alignment guides and enables your data readiness journey towards applying innovative processes and tools during the design, implement, and sustain initiatives. This includes:

Rules-Based Assessment of Data

 A rules-based assessment of your data can reveal quality and integrity issues in many areas such as:

  • Attributes (empty/null, domains, subtypes, uniqueness, etc.)
  • Legacy fields and use
  • Features/Geometry (overlapping, duplicate, outside area, etc.)
  • Missing or broken relationships
  • Connectivity and topology problems

There are many tools available to assist in this process and to examine the source data for the selected content, quality, and structural characteristics. Some of the more prominent tools that Avineon has worked with and apply given the particular needs of the assessment are:

  • X-Ray for ArcCatalog
  • Esri’s Data Reviewer extension
  • Avineon’s Model Manager (available in the Esri Marketplace)
  • Avineon’s Metrics Extension to ArcGIS for Server (available in the Esri Marketplace)
  • Safe Software FME

Using such tools, the qualitative and quantitative aspects of data readiness can be shared with stakeholders through user-friendly dashboards. Summarizing results in this manner helps to develop consensus towards an optimal data life cycle for each enterprise asset that maintains data readiness throughout the course of normal daily operations.

Conditioning Strategies to Implement and Sustain Data Readiness

With the results of this in-depth data assessment, Avineon can help you design a strategy and tools to prepare the source data for migrating into the target framework. This is determined by the nature and state of the source data sets and improvements needed to fill in data gaps. We may employ tools and methods such as:

  • Digitization from analog sources
  • Field collection via mobile applications
  • Integration of real-time data feeds
  • Georeferencing of digital data for direct integration or for use as background reference
  • ArcGIS Pro analytics functionality and tools
  • Avineon’s Accelerator’s
    • Model Manager
    • Data Loader for Utility Network
    • Conflation Manager
    • Metrics Extension to ArcGIS for Server
  • ArcGIS Data Reviewer
  • Safe Software FME
  • Manual data clean up leveraging off-shore resources for reduced costs

We will then follow a methodical process to implement each data source for use in the target data model in a logical and pragmatic fashion. This will result in a documented and high-quality data life cycle that is carefully aligned with your business needs.

An example of this is an ArcGIS Data Review process that Avineon authored and has used in over 30 projects. Performing this process in an iterative fashion has produced highly accurate and complete data ready for integration in an extremely efficient and cost-effective manner.

Data Conflation, Data Trends, and Data Governance Tools

Following implementation, data statistics and trending tools such as Avineon’s Metrics Extension will baseline and monitor data refinement efforts to sustain your investment over time.  

Taking a Holistic Approach to Data Readiness

Avineon’s holistic approach to data readiness and wealth of experience, skills, and tools can help your organization successfully navigate the complexities in designing, implementing, and sustaining data readiness. For more information, please contact Avineon directly or through your Esri Account Manager.

Data Readiness Strategies for Utilities and Telecommunications2019-08-08T12:44:17+00:00

Esri’s ArcGIS Utility Network Management Extension

Avineon’s Unique Expertise backed by Esri Technology

Avineon’s offering around Esri’s ArcGIS Utility Network extension is a comprehensive approach to help clients plan the journey to the UN with the Head Start program, incorporate the UN into operations during the Implementation process and continue to drive value from the extension through the Sustainment program.

Avineon’s Head Start Program For Esri’s Utility Network

Gain a Head Start in Delivering Value Using the ArcGIS Utility Network Management Extension Key Benefits | Beginning Your Journey The ArcGIS Utility Network Management Extension is a groundbreaking transformation of enterprise GIS technology with a modernized data model, desktop, and web applications. [...]

A High-Level Overview on the Value of Esri’s Utility Network

Utilities, ranging from electric, gas, pipeline, telecommunications and water companies, have always been a complex mix of constantly changing network data, representing an array of interconnected assets across a region. Learn how Esri’s Utility Network can help companies improve business processes, empower their [...]

Esri’s ArcGIS Utility Network Management Extension2019-10-23T10:06:11+00:00

Small Data Improvements Can Lead to Big Savings

Limiting Truck Rolls When Providing Service

Even the smallest improvement in establishing service for a new customer can lead to substantial savings, especially in an organization that is servicing millions of customers across a region. In the process of serviceability (establishing new customers) for a utility or telecom, sending a truck out to check for service availability to a specific location (aka “rolling a truck”) can not only delay service and revenue to an organization but also become costly. Though it is sometimes necessary to roll trucks, inconclusive outcomes from these initial truck rolls can lead to repeat truck rolls further adding costs. On the other hand, focusing on a specific area of data improvement, locational accuracy of streets, and facilities can help reduce the number of truck rolls per day, returning large dollar savings to a company’s operational bottom line.

limiting truck rolls service


In a perfect world, any utility or telecom cable customer service representative would field a request for new service, verify the location of the request, and quickly register the requester for new service without a delay. In practice, this involves the coordination of a multitude of business units and/or systems including geographic information systems (GIS), service agents, construction groups, accounts management, regional operators, surveying groups, etc. The process and interdependencies of a new service request can be complex and daunting to change in any utility or telecom despite potential cost savings. But can there be any value to focusing on one aspect of the process for signing up new service? Just by improving aspects of location data accuracy, a utility or telecom can reap sizable savings simply by updating features in their GIS data.

A good example of this is street and facilities maps. The locational relationship between streets and facilities is one of the primary factors for serviceability. In this day and age of expanding operational regions, company consolidations, and simple organic growth, improving the locational accuracy of a utility’s or telecom’s GIS data can fall to the back burner. On the ground, discrepancies between street and facility maps can creep in on a weekly or monthly basis further antiquating the data that these companies use as the basis of their operations. In regions experiencing growth, entire subdivisions may be included in the street’s GIS database but not in the facility GIS database or vice-versa. These deviations can hinder the customer service representative’s efforts to extend service to a new customer. This all can lead to an incomplete picture of the service territory, driving up the cost of acquiring new customers and putting the utility at a competitive disadvantage.

Truck Roll Map Overlay

Blue Line (Previous Street Map) vs. Green Line (Updated Street Map)

Truck Roll Map Before

Before Asset Map

Truck Roll Map after

After Asset Map

Imagine Cable Company X provides utility or telecom service for a region of three million subscribers. On a daily basis, Cable Company X receives 2,500 calls for new service within its operating region. Conservatively, Cable Company X can accurately locate the site of needed new service 95% of the time. Meaning, Cable Company X can instantly check on the address of the particular request and know that service can be provided without issue. As a result, Cable Company X is unsure if new service can be provided to 5% of customer inquiries (250 calls per day).

Cable Company X would now need to roll a truck to that location to see if and how service can be established. With inaccurate or incomplete street or facility GIS data, rolling a truck can sometimes lead to inconclusive findings. The field operator may not be able to find the correct address or may not be able to locate the assets needed to connect a house for new service with pin point accuracy. This becomes a wasted truck roll, and wasted money, as it leads to no conclusions of serviceability due to inaccuracies in location data. The truck would have to come back, raise an exception flag, and at some point, another truck will have to roll for the same service request.

truck roll

$6 Million Lost Annually to Inaccurate Data

If this occurs in 10% of Cable Company X’s truck rolls a day and each truck roll costs $1,000 (industry average) that amounts to $25,000 a day and over $6 million a year is lost to the bottom line all due to inaccurate locational data for streets and facilities. Simply by calibrating and auditing its GIS data, Cable Company X can reduce wasted truck rolls and enable customer service representatives to accurately determine viability of more new service requests, saving millions on its overall operations annually.

So how can utility or telecoms get better locational data?

With options ranging from automated GIS data re-alignment to comprehensive GPS-based field surveying, Avineon can tailor a solution to ensure a greater return on your investment in GIS. Just like limiting truck rolls, sometimes small actions can lead to surprising results.

Small Data Improvements Can Lead to Big Savings2017-10-28T06:08:28+00:00

A New View of Aging Assets

“Smart” Plans to Audit and Maintain Legacy Assets

3D modeling continues to add value to different industries and customers, as companies try to catalog assets or the environment around them, recreate or replace antiquated drawings, and/or develop interactive models that help drive more efficient maintenance and operation. The use of smart 3D models in the energy and utility industry has created an innovative way to manage aging plants by providing updated smart views of assets with accuracy down to the millimeter (mm) level. These smart plans can be the basis for plant operations and provide another level of guidance for maintenance, ordering parts, or updating assets within the plant.

In the past, creating immersive smart 3D models of legacy plants required exhaustive manual surveying and then converting the information to achieve a truly impactful, usable model. Today, with the advancement of surveying technology, such as laser scans using point cloud data, and an engineering model services provider like Avineon, creating Smart 3D Models has become really easy.

Antiquated Plant Plans

Antiquated Plant Plans

Updated Smart 3D Model

Updated “Smart” 3D Model

With Smart 3D Models, plant owners enhance overall plant operations in two significant ways. With millimeter (mm) level precision, Smart 3D Models provide a more efficient planning tool for modifications and operational changes across a power plant. In addition, accessibility of Smart 3D Models is not limited to those with access to paper plans or antiquated software. This allows models to be accessible even on workstations across the plant workforce.

In order to capture data using the laser scanned point cloud technique, benchmarks are first created on the local coordinate system of the plant. These benchmarks then become the landmarks of the plan as they are usually fixed, accessible, and viewable. Next, the plant is broken into parts with specific High Definition Survey (HDS) targets that require detailed surveying (i.e. turbine, reactor, cooling tower). Based on the specific measurements taken from the HDS target and the identified benchmarks, a laser scan creates a point cloud reflection of the HDS target.

Point Cloud Data after a laser scan

Point Cloud Data after a Laser Scan

360-degree panoramic photographs are also taken of the HDS target, which is linked to the smart plot plan. Rather than additional manual measuring and surveying as needed with more expensive and archaic surveying techniques, the laser scan and subsequent point cloud data diagrams are thoroughly analyzed digitally for accuracy.

In the post scan analysis, a registration process is implemented once the HDS target point cloud data is received. The registration process is a method of aligning various point cloud data plans into one cohesive coordinate system. An expert partner like Avineon helps you in converting the point cloud plans with HDS software into geometric models. Measurements are made directly into the 360-degree panoramic views with software like TruView. Integrating the appropriate intelligence in 3D CAD Plant Design Applications with data from piping and instrumentation diagrams (P&IDs), a complete Smart 3D Model of the plant is generated.

Primitive R3D Model

Primitive R3D Model

Lastly, with 3D reviews and clash detection, a final “Smart” 3D model is rendered, which incorporates all aspects of the asset or assets of the plant in one immersive system.  This process can also be tailored with a specific 3D model software of preference.

Final Smart 3D Plan

Final “Smart” 3D Plan

Many global utility companies have benefitted from the laser scanned point cloud data and our 3D modeling experience. With immersive dimensional views and millimeter level accuracy, plant owners can proactively audit and manage aging assets.  Overall, as a cost effective solution, Smart 3D Models can improve safety with better accessibility and more informed plans, improve maintenance across the plant and reduce the complexity and cost of extensions or modifications to plants in the future.

A New View of Aging Assets2020-11-17T12:48:00+00:00