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Utilities are under growing pressure to meet the seemingly conflicting goals of minimizing costs and maintaining or improving grid reliability. In developed markets, decades of underinvestment in the transmission and distribution (T&D) infrastructure have created a pent-up need to replace aging components of the electric power system and gas delivery network. This legacy means that modernizing aging infrastructure is now an imperative for a number of reasons -- the projected increase in electricity demand, emerging influx of renewable power generation, electric and hybrid vehicles which threaten to strain existing power systems, and in many developed countries the concern about losing important T&D infrastructure knowledge as many experienced workers reach retirement amongst others.

While there is no question that T&D infrastructure modernization is urgently needed, the capital-intensive nature of these upgrades poses major challenges. With many utilities facing financial pressures, securing the funding to buy new T&D equipment and for the ongoing operation and maintenance of existing assets can be daunting.

New view to assets in entirely new ways

Over the past decade, modern approaches to asset management have helped utilities mitigate these infrastructure funding challenges, while also enabling numerous grid health and reliability benefits. However it has been difficult for utilities to readily access and take full advantage of the information required to make sound, data-driven and fact-based decisions.

Till now. The introduction of powerful new analytics capabilities is driving a fundamental shift in utilities' ability to proactively avoid asset failures, extend asset life, and make better-informed asset investment and management decisions. Analytics can be defined as the process of using quantitative methods to derive actionable insights and outcomes from data. As technologies have advanced, so too has the sophistication of analytic methods. These are now giving utility operators a "new view" across the totality of their systems and data -- yielding more insights and improved decisions about asset performance management, asset strategy and asset investment planning.

Within the analytics domain, a key area of development focuses on advances in business intelligence, statistical and quantitative analysis and predictive modeling. Enhanced intelligence has enabled a shift from descriptive (what is happening?) or reactive (what happened?) analytics to more compelling and valuable predictive analytics which answer questions such as: "why is this happening?", "what is the best that can happen?" and "what will happen next?"

Advanced asset analytics capabilities are enabling asset management capabilities to become increasingly more focused on predicting system deficiencies and ensuring that investments and maintenance decisions are correct based on in-depth analysis and evaluation of detailed asset-level data.

An important recent development making advanced asset analytics includes in-memory computing and database appliances, which can be used to analyze data up to 3,600 times faster than traditional databases. This speed results in dramatic performance improvements, and the almost instantaneous availability of real-time information enables new insights into asset performance, health, and utilization impacts.

Utilities - long used to gathering the required data for effective asset management from distributed sources and numerous applications that are stored isolated silos, which result in decisions often based on insufficient information -now have the ability to view and manage their assets in entirely new ways. In particular, they can interactively query, filter and aggregate -- on demand -- the data needed for forecasting, simulations, failure modeling, planning, conducting what-if scenarios and other processes.

Visual, spatial and temporal analytics are innovations underpinning advanced asset analytics. New software correlates data from asset management, enterprise resource planning (ERP), work management/field operations, grid sensors, weather feeds and other sources into multi-dimensional displays that present asset operating status visually in a spatial, temporal and near real-time context. This correlation takes asset management to a new level -- far beyond safeguarding asset transactional health -- with the ability to help identify disturbances and condition-based equipment problems before they occur. So utilities can identify things like which assets are in danger of failing, which should be repaired first, and how much revenue is at risk should an asset fail.

The benefits of asset analytics

Accenture's experience shows that the benefits of asset analytics can include reduced equipment maintenance costs through better asset insights; lower support costs through automation, removing the need to manually gather and evaluate information; opportunities to reassign asset management personnel from low-value information gathering to high-value analysis and execution; improved returns on investment from existing data and systems; and the ability to defer capital projects by extending the useful life of assets and improving project planning.

Alongside these advantages, utilities gain enhanced visibility and decision-making and improved employee safety by reducing the exposure of a utility workforce to obsolete assets. Advanced asset analytics also enable efficiencies in regulatory filing and compliance by providing the precise, auditable information requested by regulators.

How do asset analytics deliver all this? Experience shows that at all levels -- from the field, to the asset manager, to the board room -- asset analytics provide the unique views of information, analysis capabilities and insights needed to make better decisions. For example:

• Asset strategy teams can improve asset replacement, refurbishment, and investment and maintenance strategies. These teams can merge and analyze historical information, failure statistics and scientific results to optimize capital and O&M investment strategies, and to identify and prioritize projects and programs.

• The board room gains new, easy-to-understand performance insights through at-a-glance "dashboards" and highly visual "cockpits". An asset risk management cockpit provides a high-level "executive summary" view of overall grid or system risk, together with the ability to drill down to specific high-risk areas and issues.

• Asset maintenance and planning teams can view events in near-real time, enabling them to proactively identify future issues and react more effectively to disruptions. Collation and visualization of historic, temporal event-driven and spatial data enable faults to be clearly displayed and root causes identified. Also, line-of-sight visibility into the current asset state and future plans can drive both capital and O&M savings.

• Field crews gain a much more thorough understanding of an asset's inspection and maintenance history. And mobile analytics help them better understand the importance of the data they are capturing to the functions and decisions across their utility's energy value chain -- thus underlining the need for accuracy.

The advanced analytics advantage

Based on work with 200 utilities in more than 30 countries, including planning and delivery of more than 100 asset management solutions, Accenture has learned valuable lessons that can help utilities take advantage of advanced asset analytics. Here are three of the most important.

Start now, use what you have

Utilities do not need to fix and integrate all asset data to generate meaningful results using the data they already have. For example, even if the available geographical information system data mis-locates some of a utility's equipment, the enterprise asset management-based maintenance history and condition data can be analyzed to provide valuable intelligence.

Integrate -- don't duplicate

Avoid creating additional pockets of data in siloed repositories by using modern integration architecture and frameworks. Some utilities have several hundred data stores?an approach that is expensive and ineffective. Tools and technologies are now available to integrate different types of asset condition data from across the utility to be used by analytics programs.

Choose the appropriate technology

There are many options available when it comes to analytics software, data stores, data warehouses, business intelligence tools, and visualization platforms. Similarly, there are varying degrees of automation. Over-engineering is not the solution, it'd be advisable for any utility to make choices based on factors including the desired results, the time available to deliver them, and the systems currently in place. And the underlying IT architecture should be configurable, platform independent, scalable and extendable.

Also, an agile technology implementation approach can help utilities benefit from ongoing incremental solutions that provide new asset management insight, situational awareness and data integration. Similarly, Web services should be leveraged to enable different applications to share data and services among internal departments, customers and partners.

No time to lose, the time in Now

To succeed, today's utilities need to better optimize their returns on capital investment, run their operations more efficiently, and meet rising customer and regulator expectations. All of these goals require a "next generation" of asset management, underpinned by a deeper and more forward-looking understanding of T&D assets.

Asset analytics meets these needs by enabling utilities to immediately improve asset longevity, performance and health by using systems and data that are already in place -- boosting the return on investment from those systems. Utilities that move quickly today, and a few already have, to seize the opportunities presented by asset analytics will be well-placed for high performance in the years to come.