the evolution of smart commodity management

WHITE PAPER

Sponsored by

Commodity Technology Advisory LLC Houston TX and Prague CZ www.comtechadvisory.com

The Evolution of Smart Commodity Management

Smart Commodity Management A ComTech Advisory Whitepaper

© Commodity Technology Advisory LLC, 2014 2

Table of Contents Introduction ................................................................................................................................................................. 3

The Creation and Evolution of a Software Category .................................................................................................... 4

Smart Commodity Management .................................................................................................................................. 5

Eka’s Approach to Smart Commodity Management .................................................................................................... 6

About Commodity Technology Advisory LLC ............................................................................................................... 8



Introduction Over the last twenty or more years, global wholesale commodity markets have grown and evolved substantially and in the process, a sizeable new software category has been established. That software category is widely known as Commodity Management (CM) software and, at the highest level, it can be defined as those software applications, architectures and tools that support the business processes associated with managing commodities. CM software therefore comprises a broad set of functions that can vary considerably depending on which commodities are traded, what assets are employed in the business, where those assets are located, and what the nature of the company’s business strategy and associated business processes. CM software continues to evolve quite rapidly in lockstep with the industry. In past years, CM focused squarely on trading and risk management as CTRM software, but in recent years it has been extended into the supply chain with solutions such as shipping and stockyard bulk handling, for example.

As the software category has evolved, so has the volume and nature of the data that the software captures, manipulates and stores. Today, big data is an increasingly important aspect of the commodity management world as vast quantities of many types of structured and unstructured data potentially hold the key to profitability and even survival of companies that sell or purchase commodities and raw materials. As a result, the requirements that users place on CM software are also changing from essentially an after the trade recording and reporting system, to one that provides real intelligence and value back to the business.

This whitepaper briefly examines the history of CM software and looks at how new demands are being placed on the software to make it increasingly of benefit to decision-‐making and optimization in the business. It also examines how trading and related data has also grown in volume and latency, and changed in complexity, such that CM solutions are challenged to transform big data into actionable insights and strategies for the business. In particular, it looks at how advanced, predictive analytics will be delivered, deployed and used to get the most value from the exponential growth in data being captured.

“Next generation commodity management solutions must have a light footprint, be agile, flexible and deliver significant business benefit by guiding and informing users throughout the supply chain from production source to

consumer -‐ aggregating data and providing real-‐time and easily consumable information and analytics -‐ all with a focus on ensuring

optimized decision-‐making in the increasingly complex environment that is commodity management.”



The Creation and Evolution of a Software Category CM emanated from CTRM -‐ ‘CTRM’ is the acronym for Commodity Trading and Risk Management that originated from what is now a subcategory of CTRM software known as ETRM (Energy Trading & Risk Management) software. ETRM was first coined as a software category name in North America sometime after electric power de-‐regulation took place and was subsequently defined by Vasey & Bruce (2006) and by Vasey & Reames (2010). Subsequently, the term was modified to ‘CTRM’ in order to include other commodities beyond energy such as softs, ags, metals, emissions and freight rates.

The core functionality of a CTRM system is simply to capture trades, calculate and manage position, report on exposure and account for the various transactions. CTRM has recently evolved to CM, or commodity management, as concentric circles of incremental functionality have been added to CTRM, allowing these systems to address the needs of a much wider market beyond just trading. This incremental functionality includes areas like vessel management, storage and facility management, and production management. The edge of what actually constitutes both CTRM and/or CM has become increasingly fuzzy and it now overlaps with other application areas such as traditional ERP, accounting, supply chain optimization, operations management, treasury management and other software categories.

The genesis of the CM software category can be found in the early 1990’s, following the de-‐regulation of natural gas in North America as a direct result of FERC Order 636 in 1992. At that time, a number of small private software companies developed gas marketing software solutions on a client/server platform and began to offer them commercially. By 1996, the North American electric power markets were also being de-‐regulated and, for the first time, traders were seeking commercial software solutions for multiple commodities to manage trade capture, position keeping, risk reporting, scheduling and accounting; the ETRM category software had been established.

As wholesale commodity trading evolved, more and more markets and instruments or contracts were created in regional trading centers around the globe. In turn, this placed demands on the fledgling ETRM software category as more functionality, configurability and flexibility were required to meet the increasing complexity of the market. Traders demanded more sophisticated risk metrics, credit risk emerged as a serious issue in the post-‐Enron market collapse, and the movement and management of physical commodities became more complex in an increasingly globalized market. Added to this was the need to cover a host of other commodities and their particular physical characteristics, often specified in contracts and having an impact on price. Tracking of these physical characteristics or specifications from source through storage and transportation to final point of sale or purchase was also extremely important.

During this evolution, the software category became known as CTRM to acknowledge the widening reach of these products, from energy to a variety of agricultural and soft commodities, base and precious metals, and freight and shipping derivatives. The footprint of what constituted a CTRM software solution was expanding and growing rapidly.

In the last several years, what was the CTRM software category grew further into the supply chain. One of the unique elements of commodity companies is that not only do they participate in the financial markets to manage risk but, in addition, they operate very physical supply chains. It was a natural progression for the vendors to integrate deep supply chain functionality such as bulk handling, processing optimization and shipping to their trading and risk solutions.



Of course, while all of this evolution and change was going on in the commodities markets, significant change was also occurring in information processing and technologies. Vendors were able to leverage these newer technologies, increasing processing speeds, improving the user experience, and introducing greater modularization of the applications -‐ allowing buyers to pick and choose just what they needed within the common CM footprint. The use of flexible tools meant that the software could be more configurable and personalizable, reducing implementation timescales and improving the users’ interaction experience with the software. These new technologies have also allowed improved data visualization, increasing productivity and enhancing risk management capabilities. Finally, newer architectures also improved the connectivity of the CM solutions making it easier to interface or integrate with third-‐party software. Underlying all of this however is data. Back in the early days of natural gas marketing systems, all that was really needed was daily volume and price data. As the industry evolved, more and more data was generated, stored and processed. Simple data sets grew to incorporate massive time series data sets (and multiple versions of the same data) for forward curves and expanded details for deals needed to be captured such as contract terms, complex price structures, timelines, quality requirements, weights, and so on. Document images and other types of non-‐standard data were increasingly required to be stored, especially associated with scheduling and supply chains. On the trading side, storage of phone recordings, IM logs and other evidence of negotiations became more important as regulations and regulatory oversight increased. These regulations, such as Dodd Frank in the US and EMIR and REMIT in Europe, have placed increased demands on the technologies of trading, requiring high levels of transparency and reporting, including trade reporting to central repositories. Essentially, as the CM software category expanded, evolved and matured, so did the data management requirements -‐ Big Data, both structured and unstructured, needed to be better stored, manipulated and displayed.

Smart Commodity Management A key requirement of Commodity Management is that it needs to assist users in making informed decisions by transforming large amounts of data into insights by providing predictive and user controllable analytics. Smart commodity management solutions must provide real-‐time, meaningful and actionable information to traders, risk managers and executives in order to enable them to view, analyze and simulate positions, market movements and risk metrics. Users need to be able to monitor metrics like position, exposure, inventory, in-‐transit movements, scheduled movements, counterparty risk limits, P&L, and so on by both commodity and instrument type, across both physicals and derivatives, enterprise-‐wide or via drill-‐down to trading unit and individual trader levels. Smart Commodity Management must provide a wide range of tools to mine, analyze and generate insights from transactional data, for use not only in strategic decision-‐making by C-‐level executives, but also by risk managers and traders for tactical purposes.

Unfortunately, most of today’s CM software systems have a legacy of being built as client/server solutions, focused primarily on capturing and storing transaction data. While they do provide some tools to analyze and report that transactional data, these capabilities are by and large standard risk calculations (such as VAR) and

“The use of big data will become a key basis of competition and growth for individual firms. From the standpoint of competitiveness and the potential capture of value, all companies need to take big data seriously. In

most industries, established competitors and new entrants alike will leverage data-‐driven strategies to

innovate, compete, and capture value from deep and up-‐to-‐real-‐time information.” McKinsey & Co., Big data: The next frontier for innovation, competition, and productivity.



relatively static reports that usually require in-‐depth knowledge of the relational database to update or customize as the databases of these systems have been architected to ensure transaction integrity and performance, not for optimized speed of calculation or to provision an understandable data schema for user inquiry. In the era of big data, this is simply not good enough.

In today’s business and technology environment, CM solutions must provide the ability to record transactions but they must also provide the advanced analytics necessary to rapidly (and even in near real-‐time) provide actionable intelligence to users. In many respects, it is in the area of the commodity value chain and the commodity management function where this approach is being innovated. Commodity intelligence will come about in many ways, including the usage of complex scenario analysis and optimization. In addition, next-‐generation systems will leverage public information for sentiment analysis combined with internal transaction data to draw insights and foresights. These next-‐generation systems will use sophisticated visualization tools to further enhance the analysis and decision support. The new visualization tools will allow users to rapidly build or modify dashboards themselves as opposed to having to rely on the vendor’s programming staff or expensive consultants to enhance or modify them. Indeed, user control is a key feature of the next generation of CM products -‐ Smart Commodity Management solutions.

The next generation Commodity Management solutions will by definition, need to incorporate the following:

• Predictive analytics, optimization solvers, and sophisticated visualization tools to support turning large data sets into decision making information.

• Flexible and usable user interfaces that allow the users to personalize and adapt how and what information is displayed on screen.

• Modern, extensible and flexible architectures that are optimized for performance, connectivity and improved handling of massive quantities of structured and unstructured data.

• Ability to be deployed not only as compute grids, but also leverage in-‐memory data grids. • Improved analytic capabilities to include a broader set of analytics, and structured to allow users to plug

in custom analytic approaches.

Next generation commodity management solutions must have a light footprint, be agile, flexible and deliver significant business benefit by guiding and informing users throughout the supply chain from production source to consumer -‐ aggregating data and providing real-‐time and easily consumable information and analytics -‐ all with a focus on ensuring optimized decision-‐making in the increasingly complex environment that is commodity management.

Eka’s Approach to Smart Commodity Management Early on, Eka recognized the need for an end-‐to-‐end, intelligent CM platform, not only to cope with the complex contracts, pricing structures, and financial derivative instruments that are needed to manage commodity supply chains, but also to provide advanced commodity intelligence and decision support. Eka’s next-‐generation architecture is designed to turn large sets of data, or big data, into actionable insights and foresights. Eka’s Smart Commodity Management platform helps customers run businesses more efficiently, effectively and profitably. What is most valuable to companies managing commodities is to go beyond the basic question of, “At what price should I sell this commodity?” to answer questions such as:



• How can I make sure that my demand, supply, production and logistics are optimized across each area? • How do I measure the true profitability of a deal, book, category, or line of business, which includes other

costs such as fees for transportation, brokerage, and inspection, plus premiums, demurrage and invoice adjustments?

• If market conditions were to change, what product, market, customer and supplier mix would be best in the new scenario?

• Which suppliers are delivering the right quality, at the right price and right time?

To do this, a CM platform must provide an intelligence driven architecture necessary to effectively manage and optimize a global scale operation. Eka’s Smart Commodity Management begins at the incoming supply end of the supply chain, be it the farm gate, mine, or oil well, and then supports the process all the way through to delivery to the end customer, helping to mitigate risks and efficiently move physical goods across the entire commodity supply chain. Eka’s platform is analytics-‐driven to better manage commodity value chains and make fact-‐based decisions. Unlike other commercially available first-‐generation Commodity Management solutions that focus on capturing contracts, end-‐to-‐end logistics, risk calculations, and building reports, Eka’s software goes beyond this to provide optimization and predictive analysis.

With Eka’s next-‐generation CM solution:

• The solution provides predictive analytics, optimization solvers and sophisticated visualization tools. • Large amounts of data are transformed to insights and foresights for improved decision-‐making. • Users benefit from the use of web-‐enabled, component and service oriented architectures. With these

modern technologies, Eka is able to deliver upgrades to the user faster and with significantly less disruption and cost to the business while ensuring a significantly lower total cost of ownership.

• The solution can be delivered on premises, as a hosted solution, or in the cloud.

Eka’s Smart Commodity Management platform provides fact-‐based, predictive, and prescriptive decision support to enable commodity organizations to better manage in today’s complex and volatile business environment.



About Commodity Technology Advisory LLC Commodity Technology Advisory is the leading analyst organization covering the ETRM and CTRM markets. We provide the invaluable insights into the issues and trends affecting the users and providers of the technologies that are crucial for success in the constantly evolving global commodities markets.

Patrick Reames and Gary Vasey head our team, who’s combined 60-‐plus years in the energy and commodities markets, provides depth of understanding of the market and its issues that is unmatched and unrivaled by any analyst group. For more information, please visit http://www.comtechadvisory.com.

ComTech Advisory also hosts the CTRMCenter, your online portal with news and views about commodity markets and technology as well as a comprehensive online directory of software and services providers. Please visit the CTRMCenter at http://www.ctrmcenter.com.

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