Opening Cross: Automation Doesn’t Automatically Make You an Automaton
The next upgrade to systems automation is automating systems upgrades, according to startup DynamicIQ.
Less high-profile, however, are the types of automation that go on behind the scenes, for example around the painstaking tasks associated with market data management and systems administration.
In recent issues, we covered developments by Axon Financial Systems and West Highland Support Services that automate the processes of accurately pricing requests for datasets, and for managing the process of implementing changes and updates from vendors in entitlement systems. Axon’s new “What If” add-on module to its PEAR (Policies, Explanations and Reporting) repository of exchange fees and policies allows firms’ market data departments to instantly determine how much it will cost to implement datasets and markets, based on factors such as the number of end-user accesses required, the number of exchanges from which data is needed, and what the license for each dataset allows. This potentially saves a huge amount of time spent manually looking up and trawling through each exchange policy to find relevant information, then calculating the numbers and costs.
Meanwhile, West Highland’s Data Notification Manager distills the spreadsheets of change notifications—such as fee changes, and re-naming or reconstitution of datasets—from vendors into a file of notices relevant only to each firm. “There can be hundreds of changes.... This had become a monumental task for people, and it was screaming for automation,” says West Highland chief executive Steven Roe.
Similarly crying out for automation is the process of managing software rollouts and updates to ensure consistency across a firm’s operations, according to DynamicIQ co-founder Thierry Hue, who set up the company after experiencing issues with updates and version management in his prior roles running client connectivity and quality assurance at tier-one banks. The vendor has recently begun marketing its Application Modeller tool to potential clients among financial institutions, vendors and exchanges, and is hoping to carry favor with potential clients seeking to automate a time-consuming and tedious but risk-inherent process.
Don’t get me wrong: these are important tasks, to be sure. But just as automation has allowed firms to shift human traders to focus on higher-value tasks, data professionals—once these can be safely offloaded to automated processes—can then focus on higher-value, strategic tasks around market data, such as identifying new datasets and suppliers that can deliver alpha and add value and top-line growth, or focusing more on strategic vendor comparison, bake-offs and negotiations that also impact the bottom line. After all, the value of an experienced data professional doesn’t lie in their ability to manage software upgrades; it lies in their knowledge and experience of vendors, their data, and its uses and limitations.
Plus, automating some of these important—but menial—tasks not only reduces the risk of human error, such as mistakes when re-keying data; automation also offers the potential to capture and process new sources of information, such as text reports, video maps and handwritten drilling reports in the commodities markets, as described by Platts’ Andy Bose in this issue’s Open Platform.
In short, automation allows you to stop sweating the small stuff and concentrate on the big picture. So, will the call to automate prove to be your best mate, or checkmate?
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