Today, more often than ever, utilities rely on digital tools to help them
make operational decisions, meet regulatory requirements, plan capital
spending, and respond to incidents. The key to all of these applications is
accurate, complete, and timely data. The introduction of new systems, such
as AMI/ MDM, distribution SCADA, and field data collection automation, plus
the availability of public data, including weather, public imagery,
demographics, and population change projections, has resulted in an
explosion of the quantity of data used by utilities.
While many of these tools can help utilities make better operational
decisions; inaccurate, incomplete, and outdated information can lead to
false conclusions, incompatible decisions, and costly errors.
Data silos often lead to discrepant data values being used for the same
piece of data throughout the organization. A lack of data standards and
unified processes will typically lead to misunderstanding and
miscommunication between different groups. Most often, these groups won’t
see the disconnect and proceed as if everything is mutually understood. This
leads to costly mistakes that could result in regulatory non-compliance,
business inefficiencies, or threaten safety. At a minimum, these mistakes
will cost time and manpower, which translates to money in terms of direct
cost and lost opportunity. One of the most effective solutions to resolve
these data problems is Data Governance.
Data Governance is the process of effectively managing, utilizing, and
securing data. It establishes internal policies and processes to protect the
integrity, availability, and usability of data within the organization. This
type of system generally includes a governing body, a defined set of
standards, and a plan to implement and maintain the new data procedures
throughout the organization.
With well-executed data governance, organizations can avoid the headaches
that go along with inconsistent data, because it standardizes definitions
and increases accuracy across diverse platforms and teams. More importantly,
a well-organized data governance system will increase security and ensure
compliance with internal and external data regulations while providing
decision-makers with reliable information.
Utilities have vast amounts of data, and, with new technologies, the volume
of data coming in will continue to increase. From data collection in the
field to entry through a GIS and running network analysis, often utility
data is used and created by multiple teams with different data standards due
to an emphasis on each team’s interests. This can result in poor data
quality that affects the overall understanding of the utility network and
assets. Accurate, good-quality data is essential for data analysis, and
proper governance paired with a well architected data system strategy helps
organizations keep data organized, secure, and usable.
Knowing data governance is crucial, why is it so hard for utilities to
implement it effectively? There are many common issues organizations
encounter when implementing a data governance system. They range from the
culture of the organization to data security, efficiency, and cost. Below
are some of the problems utilities may face when employing a data governance
system.
Changing protocols and technology can be stressful for end-users in an
organization. If the employees collecting, utilizing, and analyzing the data
do not see the value of data management, they may be less likely to create
good quality data. It is essential that all stakeholders within the
organization understand the importance of quality data governance in order
to gain their support in data governance initiatives.
Lack of agreement or understanding who is responsible for what data can lead
to gaps or overlaps of data ownership. This inevitably leads to data having
different values in different groups within the organization. Good data
governance defines a system of record and designates an owner for each
category of data. It also establishes the process for disseminating data
throughout the organization so that everyone is working with accurate and
current data.
Without data governance, there are inconsistent workflow practices between
the various groups, teams, and projects that generate, maintain, and use
data. There are often many different data sources, including corporate
acquisitions, which bring historical data of varying quality, and other
departments and regions with different processes and values. All of these
factors lead to inconsistent data quality. Data governance is the solution
to creating data and workflow standards for all teams and projects, ensuring
that data quality is consistent throughout the organization and over time
Implementing data governance may have short-term costs in both personnel and
expenditures. Time is taken to hold meetings to gain agreement on standards
and implementation processes. Consultants and technology may be employed to
ensure a high-quality end result, but the ROI is well worth it in the
long-term, as new data standards and practices increase organizational
efficiency and the accuracy and currency of the data.
IT security is a critical issue for all organizations today. Security is
necessary to prevent attacks on the corporate data structure and leaks of
sensitive information. Good data governance will help enhance corporate data
security by putting controls in place that specify where data comes from and
where it is allowed to go while maintaining visibility to support business
needs. Data governance is not a replacement for IT security, but it will
make security easier to manage and control.
EN Data Solutions offers a wide range of services to support our clients in
all stages of a data governance implementation or review. During the early
stages of a data governance project, EN Data Solutions can facilitate the
collaboration of all relevant stakeholders. Our teams have extensive
experience drafting policies to ensure that the requirements and concerns of
all stakeholders are considered in setting a data governance policy. We can
also coordinate workshops to ensure that critical stakeholders are not
overlooked and that each group has the opportunity to contribute to evolving
standards.
At its core, ENTRUST Solutions Group is an engineering company that not only
brings experience in data governance to our clients’ projects but we also
bring operational expertise relevant to utility companies. We utilize
industry best practices developed from our experience with utilities across
the country, and we also understand utility operations and where exceptions
need to be allowed for reasons of expediency. Our specialists make sure that
processes are put in place that allow exceptions without sacrificing
quality.
Some data governance standards require that the utility adopt changes to
long-standing practices. We can help create, review, and test new workflows
within the utility as part of this process. EN Data Solutions can ease you
through this process to help smooth the transition to new procedures and
standards for all stakeholders.
EN Data Solutions can assess our clients’ current data state and identify
ongoing and potential problems that data governance can address. This
service involves quantifying the value of data governance to their
organization and includes a cost/benefit analysis. Our team works with
clients to identify both immediate and long-term benefits of data governance
that will deliver measurable value to their organization
EN Data Solutions will work with clients to identify all stakeholders in a
data governance initiative and facilitate workshops to ensure that the needs
and concerns of all affected parties are considered when developing an
effective data governance program, including policies and procedures.
Stakeholders include groups who create, manage, and use the data under
consideration.
EN Data Solutions will recommend data governance policies and processes that
incorporate industry best practices and are specific to each client. A data
governance program should not just be an implementation of a textbook recipe
for data governance. The particular circumstances of each client will direct
what policies and procedures will be successful. Our experience with a wide
variety of clients in the same industry and working with various
circumstances helps us understand what will be effective for individual
clients.
Our specialists at EN Data Solutions have extensive experience drafting
standards, procedures, and documentation for our clients. We can also assist
in drafting the policies you need to support the implementation of a data
governance program.
A new data governance program will necessitate implementing some new
processes and changing some
existing processes. These workflows will need to be tested for bottlenecks
and unforeseen consequences. EN Data Solutions helps our clients set up a
testing program to evaluate the proposed process changes and resolve any
identified problems.
After a new data governance program has been developed, documented, and
tested, the program needs to be implemented to achieve the desired results.
EN Data Solutions can assist in this process, drawing on our experience with
other clients to help you avoid costly mistakes during the implementation.
We help ensure that the implementation is expedient and effective, so
benefits are received as quickly and completely as possible.
For any new program to be successful, change has to be managed effectively.
Changes need to be communicated to all relevant stakeholders as it is
critical that everyone involved understands and values the new processes and
standards. EN Data Solutions can help you achieve this. We understand who
needs to be included in change management and what messages will
successfully gain their buy-in.
Once a new data governance program has been successfully implemented, it is
essential to assess the program’s results to ensure that the desired
benefits have been achieved. If the program isn’t delivering the planned
value, the program must be reassessed to determine what changes need to be
made to bring the desired results. EN Data Solutions’ extensive experience
in this area is crucial in order to improve underperforming programs quickly
and efficiently