Introduction

Organizations are driven to “perform well” over long periods of time. High levels of performance produce the results needed to satisfy its many different stakeholders. Leadership teams are accountable for achieving those results. However, what does it actually mean to “perform well”? What are the categories of performance that are relevant to managers and other decision makers? How can measurable goals be identified that drive the right behaviors needed to achieve those goals? Consider the plight of executives at a pipeline company when their new president asks the following questions. 

•  “How good are we at identifying and managing leaks?”
•  “How capable are we at managing asset integrity?”
• “How well do we manage capacity utilization?”
• “How good are we at managing operational risk?”
• “How capable are we at managing our environmental impact?” 

How can they answer these questions in a meaningful manner? If they do attempt to answer them, how can they answer these follow up questions?

• What are you basing your answer on?
• What evidence do you have that supports your answer?
• Are you satisfied with how good we are?
• How can we improve or sustain our levels of performance?
• How should we allocate our capital and resources to improve targeted areas?

 To create answers useful for process improvement, it is essential that the questions are framed in a more specific manner that can lead to plans, actions and results. 

Consider a measurement framework based on four categories of performance. The first category is Effectiveness.  An effective process produces the desired results based on its design, purpose and objectives. The second category is Efficiency. An efficient process produces higher levels of output value than the required input cost to produce it. The third category is Quality.  A quality process is described in terms of consistency, availability, reliability, security and scalability. The fourth category is Compliance.  A compliant process operates within all of the constraints and obligations imposed on it by regulations, policies, standards and best practices. 

Companies need to measure what matters and turn those measurements into meaningful insights. Managers can make their resource allocation decisions across all the processes to optimize business performance levels.

The Rise of Analytics 

Pop culture and the news media have recently been producing movies, books and articles on the topic of “Analytics”. Articles describe how data and analytics are transforming our personal and corporate lives. Newspapers, magazines and web sites tell us how retailers are using analytics to customize and target theirservices to meet individual customer preferences. Books describe how analytics is used by political strategists to selectively target and persuade undecided voters to achieve political objectives. Reports about the “Smart Grid” describe how electric utilities are using analytics to manage power demand,maintain system reliability and optimize customer service. The recent movie “Moneyball” describes analytics has changed the approach that professional sports teams use to measure, evaluate, select and reward individual athletes from the perspective of optimizing team performance. 

The term “Big Data” has moved from hype to reality. The concept has been legitimized by articles published in the Harvard Business Review and The Economist. The articles describe how our digital society is generating rapidly increasing amounts of data from many new data sources such as social media, other web sites, sensors, GPS devices, multi-media, images and text. This flood of data is creating new opportunities for companies to implement analytics techniques to help generate useful business insights from the growing digital content that is readily available.

What Exactly is Analytics?

Although the mainstream media continues to publish articles about analytics, it isn’t always clear what the term actually means. Confusion about its meaning is common. The term analytics describes a process that is made up many different components. It creates capabilities for people to learn, explain, predict and understand. When correctly applied, analytics can yield significant advantages to anyone engaged in personal, athletic or business activities.

The actual process is centered within the minds of people. It is enabled by combining data, mathematical models, computing technology and thinking skills with relevant expertise of key people. It helps us discover insights and learn how things work in whatever fields of interest we care about. It is used to discover new relationships in our data that tell us how we can better influence the behavior of processes we are trying to manage. Analytics is used to help us frame and solve problems to eliminate root causes. It can also guide us in our decision making activities as we pursue our goals.

The Analytics Process depends on the following components working together.

1. Defined Domain of Interest
2. Measurements and Data
3. Mathematical Models
4. Software and Computing
5. Visualization Techniques
6. People with Communications and Story Telling Skills
7. People with Domain Expertise and Background Knowledge
8. People with Thinking and Problem Solving Skills

These items must work together in a coherent manner to generate actionable information and insights in areas that are relevant to the decision maker. 

The process enables people with the necessary domain knowledge to use mathematical models, business metrics and other forms of data to answer difficult and important business questions in areas they care about.

What Can Analytics Achieve? 

Analytics helps people to measure what matters in their areas of interest. It helps them to interpret those measurements and drive actions that improve key performance variables in meaningful ways.

When useful measurements are available, analytics techniques helps us to do the following:

• Identify the key variables that drove historical performance levels
• Identify the variables to be used as proxies for difficult or unavailable measurements
• Recommend the values of key decision variables needed to optimize performance metrics
• Provide predictions and expectations of future performance metric values

Analytics provides us with the capability to measure, monitor, explain, optimize and predict values of critical performance metrics that matter to us.

Opportunities for Pipeline Companies

What does all this mean for pipeline companies and their management teams? 

Analytics helps pipeline companies improve their business performance in targeted areas. It is important that the selected opportunities are framed and prioritised in a manner that all company professionals clearly understand. 

The term “Analytics” by itself is a general term. When combined to an area of interest, such as Marketing Analytics, Sports Analytics or Predictive Analytics, it takes on an applied meaning with purpose. 

Pipeline Analytics is the application of the core analytics building blocks to critical areas that Pipeline Companies depend on. This definition means that measurements, mathematical models, human experts and technology are working together to improve the performance of key aspects of a pipeline company’s operations.

The following are some of the critical areas that influence overall business performance of pipeline companies.

• Leak Detection Capability
• Asset Integrity and Reliability
• Capacity Utilization
• Linepack and Inventory Management
• Environmental Impact
• Operational Risk Management