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How are business intelligence (BI) trends playing out in the energy industry? That’s the question I posed in last month’s article. Let’s continue examining some other BI trends and their impact the energy sector today.
Trend #6: Enterprise data transparency
Enterprise data transparency enables an organisation to track any piece of data back to its source, and understand how the data has been transformed and manipulated along its path through the
organisation. The ability to trace the lineage of data from a historical perspective ensures that the data being aggregated and reported on is correct. Not only that, but also it must be comparable
to, and rationalised across, all business areas. Metadata management is an evolving technology that will support data transparency initiatives of the future, particularly within ETL (extract,
transform and load) applications. Ultimately, business users should be able to access metadata tools more easily to define and apply business rules and understand data lineage for themselves.
For energy companies, regulatory requirements make enterprise data transparency particularly significant. Health, safety and environmental regulations demand that energy companies quickly and accurately report on safety inspections, fuel component quality, facilities maintenance, and emissions, which will be difficult to do without achieving some level of enterprise data transparency. These regulatory requirements are very high on the list of priorities for energy companies and call for heightened enterprise data transparency.
Trend #7: Actionable Business Intelligence
Improving capabilities around corporate performance management continues to gain importance as a strategic objective for many
organisations. The challenges in achieving this goal are numerous.
First, a paradigm shift is necessary; many organisations cannot comprehend that business intelligence is used for anything more than historical reporting, trend analysis and strategic insight. These organisations need to broaden their thinking about business intelligence to include serving the needs of near real-time operational or tactical metrics, as well as key performance indicators (KPIs) that have clearly defined responsibilities and actions associated with the results.
Second, many organisations struggle to develop a manageable and clearly defined set of KPIs. Establishing a repeatable process for adding KPIs also proves to be difficult.
A third challenge lies in determining how to align the operational metrics to the corporate performance management and measurement systems that are currently in place or are being implemented.
A major push for actionable business intelligence can be seen across the energy industry, especially in the upstream oil and gas sector. In order to optimise production, upstream oil companies are using business intelligence for predictive analytics, optimising capital investment in well workovers and proactively scheduling maintenance on equipment. In addition, energy companies are largely transforming their culture into a performance-driven environment, defining performance indicators, measuring them and then comparing the results to predefined targets. Energy companies also are looking to define a clear process to follow when a KPI generated in a dashboard or report is either above or below the target by a variance outside of a tolerable range.
Trend #8: Service-oriented architecture – Drawing the connections to business intelligence
A service-oriented architecture (SOA) is a business-driven approach to
systems architecture that simplifies the integration of applications and business processes as linked, repeatable business “services.” These services are self-contained, reusable
software modules that are independent of applications and computing platforms. A significant benefit of an SOA is that rapidly changing business needs can be supported easily, quickly and
economically due to the loosely coupled and interoperable nature of the services, which are based on well-defined and formal interface definitions.
According to the Aberdeen Group’s recent “Service-Oriented Architecture Benchmark Report,” the next five years will bring more rapid development and adoption of service-oriented architecture in supply chain operations. Of 300 executives interviewed by Aberdeen, 75% said that their current supply chain software limits the services they can offer customers and does not support their strategies for profitable growth very well. The solution, according to Aberdeen, is in the SOA model which “allows corporations to start weaving together people, applications, and data to support individual and unique processes, helping you and your business partners meet the challenges and opportunities in a global, multi-channel environment.”
To make a connection between SOA, which is not a data-centric discipline, and business intelligence, which is very data-centric, companies will need to model the relationship between business services and data models. As recognized by Forrester, an SOA offers significant potential benefits. Most companies are still focusing on how to leverage SOA for designing business processes, but there are tremendous benefits to reap by addressing information management in an SOA architecture. This will enable companies to leverage SOA not only for enabling business processes, but also for measuring and optimizing business processes as well.
Energy companies that are embracing SOA-enabled BI (SOBI) solutions are creating integrated data service provider components as well, which mimic traditional warehousing architectures with an SOA layer to expose the data to SOBI requests. SOA-enabled business intelligence for energy companies can allow disparate and loosely coupled business processes and data to come together in ways never before possible. For example, in the upstream space, SOA-enabled BI can help bridge across the entire well life cycle, from AFE approval, through exploration, production, and ultimately facility shut-down, and allow executive management to assess this long-term investment in a holistic manner, comparing the capital expenditure across assets to optimize future investments.
Trend #9: “Rightshoring”
“Rightshoring” is determining the right mix of onsite, offsite and offshore work that delivers high quality results at a
lower price point while mitigating risk. Although offshore sourcing for BI development has gained fairly widespread acceptance over the past several years, enthusiasm has waned due to lower than
expected benefits in terms of quality, as well as price per unit of output.
To determine the optimal mix of onsite, offsite and offshore development, it is imperative that a company be able to monitor and evaluate or measure performance of each of these development models. A best practice for monitoring and evaluating sourcing options is to implement analytics around IT and development, which will allow a company to understand the true costs and benefits of its sourcing choices. The first step is to establish a sound development methodology and IT performance measurement program internally, or “onsite,” before attempting to measure offsite or offshore performance. This way, the company will have benchmark information for meaningful comparisons with the offsite or offshore performance results.
Many energy companies are adopting the offshore model, in many cases having been incented by procurement to move a portion of their IT spend to a lower cost structure. To mitigate the learning curve an offshore model imposes, a multitiered delivery model is emerging. This model involves an onsite, offsite and offshore team to pass work components back and forth with a high degree of quality, facilitating a relationship between offsite and offshore teams that transcends any specific project. Thus, the “individual project” learning curves and excess QA infrastructures do not need to be put in place to mitigate the risks typically associated with a two-tiered model.
Energy companies should pay particular attention to the proper split and measurement of their onsite, offsite and offshore efforts given the strategic, complex and business-intensive nature of the projects. For example, energy companies are setting up offsite “centers of integration,” or COIs, for specialized integration work that can be leveraged across the organisation. These COIs face off with the onsite team for requirements, pass development components onto an offshore team, provide the QA when the components come back, and face off with the onsite team for testing.
Trend #10: Semi-structured and unstructured data
Many companies are beginning to think about the challenges that exist in integrating unstructured data with structured data
so that it can be analysed together. Structured data is typically generated from OLTP (online transaction processing) systems. Unstructured data is data that is not found in tables or records, and
has no keys or attributes. Semi-structured data is unstructured content with associated metadata to provide some context of the underlying data. Common examples of unstructured and semi-structured
data include well logs, seismic data, e-mail, memos, documents, telephone records, voice recordings, instant messages, terms and conditions of a supplier or customer contract, or customer survey
feedback, which does not adhere to a standard format. Gartner predicts that by year-end 2007, a framework and terminology will have emerged to help companies better align their structured and
unstructured data.
The benefits of integrating semi-structured and unstructured data with structured data include the ability to provide richer contextual meaning. Energy companies using state-of-the-art BI techniques could analyse technical, operational and financial data once structured and unstructured data has been integrated. For example, energy trading companies are using BI techniques to enforce trading regulation. More than $4 billion in fines have been issued by regulatory bodies over the past two years. In some cases, the activity precipitating these fines was legitimate, but unexplainable due to the difficulty in proving the intent of the trades from an event that occurred in the past, or even more difficult, recreating the all of the structured and unstructured information at the time of that event. Using BI techniques, patterns in structured and unstructured data such as trades, voice recordings and instant messages are analysed real time for anomalies and, when found, a compliance officer can document the intent at the time of occurrence, mitigating the fines that could have resulted otherwise.
Leveraging Business Intelligence
Clearly, a greater appreciation for timely, quality information exists within organisations of all industries. Although some of the trends
discussed in this series may be more relevant to energy companies than others, the opportunity to leverage business intelligence to maximize production safely, efficiently and cleanly is
tremendous. I will be addressing these opportunities in future articles by focusing on news, issues and trends appearing to have the most impact on the energy sector.
For Knightsbridge’s white paper on the Top 10 Trends in Business Intelligence, please visit http://www.knightsbridge.com/.
Click here for Part 1 of this series.
John Ruddy joined HP's Information Management Practice (formerly Knightsbridge Solutions) in January 2005 and leads the firm's Energy Practice. John has more than 20 years experience in management consulting, systems integration and data management, with an exclusive focus on energy throughout his career. John has worked across various segments and functions of the energy industry, including upstream, midstream, downstream refining and marketing, electric power, energy trading, oil field services, and pipeline operations. His experience spans a range of energy commodities, including crude oil, refined products, power, natural gas, NGL's, and associated financial instruments. John has brought innovative solutions to more than 45 major energy clients to solve complex business problems. Prior to joining Knightsbridge, John was with IBM's Business Consulting Services (formerly PricewaterhouseCoopers), where he provided leadership and engagement management for their global energy trading practice. John is active in multiple industry associates, including the Petroleum Industry Data Exchange (PIDX) and the International Energy Credit Association.
Editor’s note: More energy articles, resources, news and events are available in the Business Intelligence Network's Energy Channel. Be sure to visit today!
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