The Benefits of Integrating Xmon with an EDM System

Xmon integrates with EDM (Enterprise Data Management) systems allowing firms using them to increase their benefits and optimise their data usage even further.

EDM systems facilitate the management and governance of a firm’s data, which would otherwise be prone to inconsistencies, inefficiencies, security breaches among other issues. Xmon complements an EDM solution by providing transparency, control and cost optimisation.

Transparency

Xmon allows tracking every data request that flows within the firm, whether it is an internal request from a data consumer to the EDM system or an external request from the EDM system to a data vendor. If the EDM system provides data caching as one of its services, Xmon can compute the cost saving or the ROI (Return on Investment) achieved by the caching mechanism as the difference between the cost of all internal requests and the cost of all external requests. This allows evaluating the efficiency of the cache and fine-tuning it further through request-level analysis.

Additionally, through the integration with the EDM system, Xmon can access the user consumption data, which it then uses to allocate the data costs fairly and accurately across the user base by employing its powerful data dictionary and data mapping capabilities.

Data lineage is yet another benefit achieved by this integration as Xmon allows tracing all fields requested by the EDM system from data vendors to check that they are actually used by, or distributed to, at least one of the internal data consumers. This makes it straightforward to then verify the business rationale for each field requested in order to limit requests to the data actually used and needed – one really good way to ensure costs are always optimised.

Control

As part of its useful toolkit, Xmon offers a powerful Rules Engine which allows different levels of monitoring over reference data spend in real-time. This monitoring ranges from soft-limit rules which issue alerts or warnings when certain limits are breached to hard-limit rules which interrupt expensive or questionable requests for review and investigation before they are directed to the vendor, or even block them altogether if needed. Use-cases can be cost-driven such as issuing a warning when a certain data consumer exceeds a certain daily volume or cost limit or compliance-driven such as blocking certain users from requesting a specific data category. By interfacing to the EDM platform, Xmon obtains all the usage information required for implementing the needed control.

Cost Optimisation

By drilling down into internal (user-to-EDM) requests and external (EDM-to-vendor) requests, Xmon can explore further optimisations for data management and identify opportunities for cost reductions and savings. It can detect duplication patterns in requests at the data field level as well as the security level and offer recommendations and best-practice tips for mitigating MultiHit costs by leveraging the caching capabilities of the EDM system among others. Xmon can also suggest alternative methods for sourcing reference data, for example using Bulk Data provision from certain vendors, and allows users to simulate these methods to gauge their cost benefits before switching to them.

The benefits of integrating Xmon with an EDM System

To find out more about how Xmon can integrate with EDM platforms or to request a product demo, please contact us. We would love to hear from you!

TRG Screen announces acquisition of Xpansion!

January 19, 2024 – New York – TRG Screen, the leading provider of enterprise subscription spend and usage management software, today announced it has acquired Xpansion, the leading provider of cloud-based solutions for reference data usage monitoring in the financial services industry. The acquisition of Xpansion will further solidify TRG Screen’s position as a global market leader in market data management solutions.

Xpansion – established in 2013 – is focused on empowering data operations teams to proactively manage their usage, control costs and optimize data workflows. Xpansion’s offerings include Xmon, Xprocess and Xplore, and provide real-time analytics, giving clients unprecedented transparency, visibility and control into their reference data usage.

This deal consolidates TRG Screen’s unique position as the only provider of enterprise subscription management capabilities spanning the whole spectrum of market data optimization, from spend and inventory tracking, through to usage and enquiry management, exchange reporting and compliance.

“Xpansion and TRG Screen have been partners for many years. Bringing Xpansion into the TRG Screen family is a very logical next step for both companies, given our strong relationship and shared view that the industry demand for integrated usage management solutions is going to continue to grow,” said TRG Screen CEO Leigh Walters. “Xpansion is an established firm with excellent customer satisfaction and retention, and highly experienced and industry respected leadership. We are very excited at the opportunities this acquisition brings.”

“We are thrilled to be joining TRG Screen,” said Xpansion co-founder and CEO Amjad Zoghbi. “Reference data usage is one of the most complex aspects of market data management, and managing it correctly is essential to maintaining contractual compliance and ensuring clients are right-sizing their usage based on actual consumption and business need. I’m very pleased that Xpansion’s customers, and team, will now be part of the best-of-breed solution with the industry’s leading provider of market data management solutions.”

The acquisition demonstrates TRG Screen’s ongoing commitment to servicing the needs of market data consumers, vendors and exchanges.

Financial terms of the transaction were not disclosed.

About TRG Screen

TRG Screen is the leading provider of enterprise subscription management solutions. Founded in 1998, TRG Screen is uniquely differentiated by its ability to monitor both spend and usage of data and information services including market data, research, software licenses, consulting and other corporate expenses.

TRG Screen’s solutions provide its customers with full transparency into their vendor relationships and their subscription spend and usage, enabling them to optimize their enterprise subscriptions. TRG acquired Priory Solutions in 2016, Screen Group in 2018, Axon Financial Systems in 2019, Market Data Insights in 2020, and Jordan & Jordan’s Market Data Reporting (MDR) business in 2021 and with these acquisitions is now positioned as the global market leader in the financial, legal, and professional services markets.

TRG Screen’s product portfolio includes subscription spend, usage, enquiry and compliance solutions.

About Xpansion

Xpansion delivers next-generation reference data solutions that empower financial institutions to streamline their reference data operations, reduce costs, enhance data quality, and improve data discovery. With a focus on customer satisfaction, continuous innovation and quick time to value, Xpansion is a trusted partner for financial institutions in the buy- and sell-side as well as solution providers in the industry.

Learn more and discover how Xpansion can elevate your reference data operations at trgscreen.com/xmon.

 

Xmon Reference Data Statistics 2023!

Here are some numbers from the Xmon analytics engine for 2023:

Maximising Efficiency: Monitoring Xmon Components With Xprocess

Xmon is the leading solution for monitoring reference data usage and spend. While Xmon operates seamlessly as a cloud service, some clients opt to integrate their data requests flow with Xmon using an on-premise Xmon agent. Such hybrid mode is required when using a dedicated private line with their data vendors or when credentials need to stay within the client environment. Ensuring the continuous uptime and optimal performance of this on-premise agent is where Xprocess steps in.

Why Monitor The Xmon Agent?

It is important to monitor any component for uptime, availability and reliability. In fact, our team uses Xprocess to monitor our backend cloud infrastructure. For clients using an on-premise agent, it is important to monitor the service for:

Service Continuity: Monitoring the Xmon agent is crucial for uninterrupted service. Any downtime can impact the flow of critical data and processes.

Quick Incident Reaction: Timely identification of errors or performance issues is essential. With Xprocess, you can swiftly react to incidents and address them before they escalate.

Proactive Notification: Xmon support can be notified promptly about any issues with the agent. This proactive approach enables the support team to take immediate action and resolve potential problems efficiently.

What Does Xprocess Monitor?

The Xmon agent has a seamless interface to Xprocess and this allows for monitoring of:

Xmon Agent Uptime: Track the continuous operation of the Xmon agent to ensure it is always available, when needed.

Realtime Error Monitoring: Identify and address any errors generated by the Xmon agent promptly to maintain a smooth operation.

Performance Evaluation: Keep an eye on the performance of the Xmon agent to guarantee optimal functionality.

The Power of Xmon and Xprocess Integration:

Although Xmon and Xprocess are distinct products, this use case illustrates their seamless integration. Together, they provide a comprehensive solution to ensure proactive monitoring and maximum reliability of components.

In conclusion, the combination of Xmon and Xprocess is a powerful duo for clients looking to bolster their monitoring capabilities. By keeping a watchful eye on the Xmon agent’s uptime, errors and performance, businesses can ensure a continuous and efficient operation. It’s all about staying ahead of potential issues and maintaining a proactive approach to service reliability. If you’d like to learn more about Xprocess or Xmon, please reach out to us here.

Our Most Read Article Of The Year Revisited: Xmon’s Efficient Management of Reference Data Flow Within Your Organization

In today’s data-centric business landscape, the proficient management of reference data is paramount. Robust reference data management ensures informed decision-making, regulatory compliance, and effective risk management. It is crucial to monitor the inflow of reference data from external sources, such as data vendors, into the organization, as well as the movement of data among internal systems. Navigating the tracking of reference data within an organization can be complex, particularly when dealing with diverse systems and varied data source formats and mappings. This is where Xmon comes into play!

How Xmon Enhances Reference Data Management

1. Tailored Mappings for Securities and Data Attributes

A standout feature of Xmon is its customizable mappings for securities and data attributes. This functionality empowers businesses to map their internal security references and data attributes, ensuring accurate representation, classification, and organization of data. It enables the tracking of reference data points within the organization, even when modified or mapped during their journey from source to consumer.

2. Customizable Cost Models

Xmon offers customizable cost models, allowing businesses to track the costs associated with reference data as it flows within the organization. This feature facilitates internal monetization and equitable allocation of expenses, promoting transparency and fairness.

3. Customizable Data Formats

Whether data is distributed via queues, files, or various formats like JSON or XML, Xmon provides integration adapters that allow the ingestion of data requests in their native formats for efficient tracking within the organization.

Significance of Tracking Reference Data Internally

1. Transparency of Usage and Accountability

Internal tracking of reference data enhances transparency of usage and fosters accountability. This practice provides insights into who is utilizing specific data within the organization, promoting transparent spending and reporting. It ensures that reference data is employed effectively and in the most cost-efficient manner possible.

2. Data Lineage

Tracking reference data enables the establishment of data lineage. This is vital for tracing the origin and transformation of reference data, ensuring accuracy, reliability, and alignment with business needs.

3. Internal Cost Allocation

Effective tracking of reference data supports internal cost allocation, ensuring that data management costs are appropriately distributed across the organization. This optimization ensures cost-effective management of reference data.

Client Use Case: A Leading Asset Management Firm

A global asset management firm utilized Xmon to track data requests from its central Enterprise Data Management (EDM) system to external vendors. Following successful external deployment, Xmon was leveraged internally to track reference data between the EDM system and internal consumers. This resulted in optimized spending, identification, and removal of unused data points from vendor calls, and fair cost allocation based on actual usage. The outcome included improved transparency, enhanced compliance reporting, and an 8% reduction in overall data spend.

Conclusion: Managing Internal Reference Data flows with Xmon

Xmon empowers organizations to effectively track reference data both internally and externally. With customizable mappings and cost models, Xmon enhances transparency, fosters accountability, enables data lineage, and facilitates cost-effective internal management of reference data. Ultimately, Xmon enhances operational efficiency, transparency, and decision-making through reliable and consistent data.

If you’re interested in learning more about how Xmon can enhance reference data tracking within your organization, feel free to reach out by clicking here.

Challenges in Data Management Mitigated by Xplore

The Challenges

The data management issues that firms, across industries, face because of the abundance of data they generate and consume and its dispersion across a plethora of internal and external systems that are complexly intertwined cannot be understated.

Time Lost Looking for Data

When data is not properly catalogued and is often spread out across the different departments of the firm, employees waste a lot of their time looking for the data they need. Instead, they could be using this time to analyse the data, draw insights from it and drive their business forward.

Duplicated Data

Without a data inventory, it is also difficult for data consumers to find and leverage existing data sets. As a result, they end up duplicating data by recreating it or purchasing it from vendors multiple times.

Siloed Data Impedes Collaboration

Data is typically held in silos and not easily or entirely available to other departments or teams. This makes data sharing and collaboration difficult across the firm.

Limited Visibility of the Data Landscape

Such a data culture also limits the visibility of the data landscape, and, as a result, data managers have a poor overview of what data exists and where it is.

Poor Data Quality

Siloed data, together with the data duplication that usually results from it, give rise to inconsistencies in the data which compromise its quality, integrity and reliability.

Non-compliant Data Access

Non-compliant data access is yet another problem. Even with the best intentions to do the right thing, firms face challenges when trying to comply with, and report on, all the regulations around data access and usage entitlements.

Xplore: Data Discovery, Data Classification and Data Management

Xplore is Xpansion’s Data Discovery, Data Classification and Metadata Management solution, which tries to mitigate these challenges.

Data Discovery

First and foremost, Xplore is a data discovery platform that allows firms to connect to their various data sources and launch crawlers, which discover the datasets on the sources and pull their metadata into Xplore.

Data Classification

Moreover, Xplore allows the firm to build a data classification that is customised to the specific business context and needs. This classification can then be used to place the datasets represented by their metadata into a meaningful organisation which facilitates navigating through, and searching for, the data.

Metadata Management

Equally important, Xplore is a metadata management system that is used to manage the technical metadata obtained by the crawlers as well as add a layer of user or business metadata such as descriptions, reviews, additional notes, and custom metadata fields depending on the use case.

Access Rights Management

Finally, Xplore can be used to control the permissions that users have over the different datasets and allows the firm to enforce the regulations around access and entitlements. It also allows and tracking, and reporting on, data usage.

This range of functionality allows data managers and data stewards to get a better overview of their data and to put it at the disposal of all the data consumers across the firm. The datasets are discovered, classified and described through their metadata in Xplore. Data consumers can then consult this catalogue or inventory of datasets, to search for the data they need as well as to browse the data assets available in their firm. By looking at the metadata, users can evaluate the usefulness and relevance of datasets before accessing the data itself and thus find what they need more quickly and more efficiently.

To find out more about Xplore or request a product demo, please contact us. We would love to connect with you!

Track ICE EOD Price consumption in Xmon!

Xmon is vendor agnostic and as such it is able to track usage and control spend over a multitude of reference data vendors. One example of these is ICE. Xmon is able to ingest and monitor ICE EOD price requests and track usage in real-time. Using Xmon you can configure your ICE commercial models and start tracking usage and spend in real-time as the month progresses. Using our advanced analytics, reports and dashboards, you’ll be able to view your organisation’s spend as it is progressing and meeting your estimated budget: No more surprises at the end of the month!

Using the pay-as-you-go rate card, a charge is incurred every time a data request is made. Many data vendors follow this model for their products, including ICE. Xmon is able to monitor ICE EOD Prices usage intra-month, and helps avoid any unwanted spikes in usage and cost. In addition to tracking usage in real-time, with Xmon you can configure alerts that are triggered on abnormal requests or consumption and you can allocate spend fairly to data consumers within your organisation.

Integration of ICE EOD prices is supported in all integration modes of Xmon. For more information on tracking ICE reference data usage and other vendors, reach out to our team here!

Maximising Optimisations: Benefits of Internal Reference Data Usage Metering with Xmon

As presented in one of our previous articles “Xmon: Managing Reference Data Flowing Within The Organisation”, Xmon has the capability to monitor reference data requests flowing between internal systems. This is especially useful to do in organisations that leverage capabilities of an Enterprise Data Management (EDM) platform, as it enables deeper tracking of data flows and a more complete understanding of usage patterns. In this article we illustrate the benefits of such an integration and highlight how market data officers are able to fully view and manage the flow of market data throughout the whole organisation.

Enabling Internal Cost Allocation

 

The above diagram illustrates how Xmon can be integrated to track data flowing into the organisation, i.e. from external data vendors, as well data flowing within the organisation, i.e. from internal data distribution systems, such as EDM platforms to internal consumers.

By defining the same commercial model for the ‘Internal Requests Contract’ as the vendor’s rate card, Xmon is able to reconstruct a complete cost profile for each internal consumer, and produce a true cost allocation by consumer or cost centre. Consequently, this allows market data officers to allocate spend fairly to each business line/consumer, based on their actual consumption.

 Monthly cost allocation by internal system/consumers

 

In addition to providing cost transparency to end data consumers, Xmon can also deliver a Return On Investment (ROI) dashboard, which measures the efficiency of the internal data distribution platform. It calculates the savings generated by consolidating the requests for market data internally before acquiring the actual data from the vendors.

Return on Investment dashboard measuring the efficiency of clients’ internal data distribution platform

 

Enabling Data Lineage

Maintaining data lineage is crucial for ensuring data integrity, compliance and cost efficiency. Xmon takes data lineage to the next level by offering field-level visibility and look-through capabilities, by tracing data flow from data acquired from the vendors to its final consuming applications. This data lineage is made possible thanks to the definition of field dictionary synonyms, which maps equivalent fields between vendors’ mnemonic and internal data distribution layer dictionary.

In addition to this field-level lineage, Xmon can report on the list of security ID’s requested by each consumer, which among other things, serves as a base for calculating a fair cost allocation based on actual consumption.

Enabling Cost Optimisation

With its advanced reporting capabilities, Xmon’s transparency empowers organisations to identify opportunities to mitigate their market data spend and ensure they only pay for the data they actually consume. Thanks to the field-level data lineage we can easily trim unnecessary costs by identifying fields which are collected from the vendors but not used by any internal system. In addition, reporting on the internal consumer usage enables market data officers to highlight to the business some expensive categories triggered by just a few fields and discuss alternative solutions to source such fields using a different commercial model from the same vendors for optimisation. Alternatively, the universe of securities requesting those fields can be trimmed down.

The analysis described above is able to generate additional savings between 10% to 15% of total spend, and importantly, enables fair spend allocation and powerful usage metering for data flowing within the organisation.

If this article is interesting to you and you would like to find more about this topic, please get in touch, we would love to help you!

Reference Data Management: Some best practices and common pitfalls

The effective management of reference data has emerged as a pivotal element in sustaining operational efficiency, optimising spend and fostering a transparent, repeatable, and informed decision-making process. Reference Data Management (RDM) entails the organisation, categorization, and oversight of reference data – the foundational data used for classifying and contextualising other datasets. However, distinguishing what strategies yield success and what pitfalls to avoid is integral to building a solid RDM strategy.

What is Reference Data Management?

Reference Data Management (RDM) is a set of processes, people and technologies that allows the organisation, maintenance, and optimisation of reference data within a financial institution. At a high level, RDM can be divided into three functional areas:

– Managing Reference Data usage and spend
– Managing Reference Data quality, availability and distribution
– Managing Reference Data governance and policies

Managing Usage and Spend management, as well as Managing Data Governance are cross-business functions and generally benefit from being managed by central teams within organisations. Managing data quality, availability and distribution are entity specific and therefore their functions should typically be siloed within organisations, as different business units will have differing requirements for data and how it is sourced and distributed.

At Xpansion we provide solutions for all three functions above and we believe it is important to distinguish these, as each will bring its own challenges and requirements. In this article we provide some best practices and common pitfalls when dealing with Reference Data Usage and Spend.

Reference Data Management, best practices, and common pitfalls

 

Best practices

Monitoring usage 

Gaining insights into data consumption behaviour is a cornerstone of a robust RDM strategy. Metering data usage allows you to ascertain data consumption patterns, understand data flows, and paves the way for better decision making through precise actions and predictable outcomes. Data usage metering should focus both on inbound and outbound data for a more comprehensive view and deeper analytics.

Actively Controlling Non-production data usage

By limiting access to data without genuine business value, you curtail wasteful expenditure on irrelevant datasets and avoid unnecessary spend and mitigate cost spikes. Actively creating data access control rules in the organisation also avoids compliance pitfalls and licensing issues, so that it is not just applicable to non-production data.

Checking and reconciling invoices

Reconciling invoices maintains accountability and reduces spend leakage. It is imperative to have mechanisms to check that your organisation is being charged correctly, in line with current agreements in place. Mistakes happen, however having tools in place to validate invoices removes doubt and maintains accountability and transparency.

Know what data you have and what data you have access to

Cataloguing data isn’t limited to merely identifying what data your organisation possesses. It extends to understanding the spectrum of available data, including both external vendor sources and internal sources, as well as using metadata attributes to enhance the meaning of the data. By assessing the data landscape comprehensively, you minimise redundancy, understand user requirements and curb inefficient expenditure.

Establishing cross-organisational team units for RDM

To be most effective, Reference data management usage and spend function should be incorporated within a cross-business team. Optimal results arise from globalising RDM operations within expansive organisations, facilitating insights-driven decisions that benefit the entire enterprise in an efficiently orchestrated manner. This is especially true for usage and cost optimisation, as well as data governance.

Leveraging External Expertise

Recognising the intricacies of RDM and how complex reference data commercials can be, seeking guidance from experts augments your data management strategy. Collaborating with knowledgeable professionals lends insights into best practices, innovative tools, and strategic methodologies. Seek experts that continuously add value to your team rather than performing one-off exercises.

Common pitfalls

Introducing complexity through data caching 

Data caching, when not offered as part of a more complete Enterprise Data Management (EDM) or Master Data Management (MDM) solution, adds both technical and operational complexity which, in most cases, yields disappointing returns, masks data quality issues and creates confusion with data consumers.

When properly implemented, a solid EDM/MDM solution will provide the ability to remove duplicated requests for data, store bulk file information and provide a golden data copy to users within the organisation, as well as the possibility to benefit from multiple data vendors at the same time.

A solid data strategy in an organisation should include one or more EDM systems which are properly configured, and which will also negate the need for a separate and complex data caching and distribution system.

Using multiple vendor accounts

Relying on multiple accounts for cost allocation and usage reporting fragments the organisation and leads to inefficient processes, duplicated usage and increased spend. Streamlining cost allocation through a unified reference data hierarchy enhances financial tracking and reporting accuracy and is in the spirit of keeping things simple. Rather than duplicating accounts, it would be more advisable to reduce the number of accounts and apply usage monitoring to allocate spend internally, in a fair way and combined with a full usage report.

Using a One-off approach

RDM is a continuous process, not a sporadic effort. Treating RDM as an isolated task might deliver some value in the short term, however it is a false economy as over time, inefficiencies will arise again and will be more costly to address. A more effective strategy would be to introduce continuous controls and monitoring to enable a proactive management strategy that is able to respond in real-time to business requirements and changes.

Conclusion

 

We hope this article has helped shed some light on some best practices and common pitfalls in the area of reference data management. RDM can be a daunting task with clients not quite sure where to start and how to deliver value quickly with little impact to the business. At Xpansion we advocate a bottom up approach: start with small projects that deliver and gradually expand best practices throughout. We have been helping organisations of all sizes for more than 10 years and are here to help. Get in touch with us for a demo of our products or to discuss your needs further!

Spotting Data Over-Consumption Early

In this article we show how Xmon, through the use of Rules and a new Standard Report, can help flag users or systems that have exceeded their usual or allowed data consumption and, therefore, mitigate potential spikes in multi-hit cost. As a reminder, multi-hit cost is a feature of certain reference data pricing models and is incurred when an organisation requests the same billable category multiple times on the same day for the same securities. Click here to recall how Xmon can be used to understand and mitigate multi-hit cost.

Standard Report 32: Average Daily Usage by System

Xmon has benefited from the recent addition of a Standard Report which computes the average daily usage per system over a selected period of time. By default, the time period is the latest quarter.

New Standard Report 32 in Xmon computes the average daily usage by system

 

This report is available under REPORTS > Standard Reports > Standard Ratecard.

Example output of the Standard Report 32 in Xmon

 

The example above shows that, during the given period of time, System 1 has requested on average 68 securities per day. The maximum number of securities it requested in a single day was 151. System 2 averaged a daily multi-hit cost of $168.54 over that same timeframe and its highest multi-hit cost in one day was $575.60.

Setting up Rules to Monitor Daily Consumption

These average and maximum figures can be used to draw limits on the daily consumption of the different data users and systems. And these limits can, in turn, be used to define rules that would issue warnings when exceeded. As cost could vary between the first day of the month and the subsequent days of the month, we suggest defining these limits on daily volume. For instance, based on the maximum daily number of securities requested by System 2 over the last quarter (11,756 securities), we can setup a limit of 12,000 securities on the daily volume of this data consumer. If this limit is breached on a certain day, a warning e-mail is sent to the “Market Data 1” mail group.

Example rule setup in Xmon to raise an alert when System 2 requests data for more than 12,000 securities on a day

 

When rules are created on the daily consumption, they can be monitored in real-time from the dashboard. We can see below an example showing the Dashboard when System 2 has already requested 10,273 (amounting to 86% of its “allowed” daily volume) on the day.

The Dashboard in Xmon showing the actual consumption of System2 compared to its daily limit

 

If this article is interesting to you and you would like to find more about this topic, please get in touch. We would love to help you!