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Market Alert: Calero-MDSL Develops a UCaaS Management Solution to Rationalize Enterprise Telephony

Key Stakeholders: Chief Information Officers, Chief Technology Officers, Chief Financial Officers, Finance and Accounts Payable Directors and Managers, Human Resources Officers, Procurement Directors, Telecom Directors and Managers, Mobility Directors and Managers, IT Architects, Vice President/Director/Manager of IT Operations, DevOps Managers, System Architects, Product Managers, IT Sourcing Directors and Managers, IT Procurement Directors and Managers

Why It Matters: The era of the business desk phone is coming to an end, but employees still need a variety of unified communications, conferencing, and collaboration apps to maintain productivity. To support this multi-modal communications environment, enterprises need a single view of inventory, cost, and usage for their full telephony and unified communications environment.

Top Takeaway: With this Unified Communications as a Service (UCaaS) cost management module, Calero-MDSL is providing a specialized toolkit to analyze and compare both fixed wireline and UCaaS services to right-size and rationalize telecom investments. 

Calero-MDSL Announces a UCaaS Expense Management Module

On March 17th, 2021, Calero-MDSL announced the launch of a UCaaS Expense Management module designed to support both the fixed and variable costs associated with collaboration. This module is designed to provide one perspective for both landline telephony usage and UCaaS and to provide both end-users and cost center managers with both visibility and self-service options to optimize their calling and collaboration environments. There are several key market trends driving increased focus to UCaaS management.

First, this decade, the 2020s, will lead to the decline and fall of the desk phone.

As of the end of 2020, Amalgam Insights estimates that approximately 70% of employees are assigned a desk phone and 55% of employees use smartphones and cell phones for work purposes. In the face of COVID and the digital transformation and remote work tasks that have been made necessary in a quarantine, Amalgam Insights expects that these numbers will flip-flop by the end of the year as half of the workers who went home for the quarantine will not come back to the office every day. We are moving from a pre-pandemic environment where less than 10% of employees worked from home to a post-pandemic environment where roughly 25% of employees will primarily work from home and another 20% will only come into the office part-time.

All of a sudden, 30% of desk phones will be rendered permanently obsolete at the end of 2021 when remote and in-office work has been rationalized.

Source: Amalgam Insights

Enterprises will need to increase their support and ownership of mobile devices and apps to ensure governance and control of the primary communications channels used by employees going forward.

Second, as enterprises continue to shift both towards Unified Communications as a Service and Communications Platform as a Service (CPaaS) to support telephony, it is no longer sufficient to simply treat the PBX as the end-all and be-all of enterprise telephony. Not only does telephony need to be treated as a potentially cloud-based function, but also as a set of APIs and services that can potentially be embedded into other applications and processes. Telephony is increasingly fragmented and granular, making it harder to compare the supply, demand, and cost for the various on-premises, cloud, and app-based options for telephony services without having a single inventory and cost management source.

Third, the obvious expansion of conferencing solutions ranging from Zoom to Microsoft Teams as well as stalwarts such as Cisco WebEx have resulted in the need to better manage usage, employee plans, accounts, and add-on functionalities to support larger meetings, recording, calling features, and enhanced security. To avoid wasting time in ensuring that appropriate roles are empowered with the right level of access, businesses need to manage their conferencing and UCaaS.

Amalgam Insights considers Calero-MDSL’s development of a UCaaS specific expense management module to be an interesting product launch that will provide value to IT departments. In this case, Amalgam Insights considers UCaaS to be a subset of the larger SaaS management category rather than a telecom expense management topic, as UCaaS is driven by SaaS-like economics and demand. However, the biggest difference between a SaaS Expense Management solution and Calero-MDSL’s UCaaS solution is in understanding the granularity of management. SaaS management tends to focus on the license level of procurement and expense, with some basic visibility into whether functions are being used and if users are logging in. However, by focusing on UCaaS, the unit economics of usage and cost are driven down to the call level where companies can get a per-call or per-conversation cost basis for their UCaaS investments as well as an understanding of how, when, or if the business is better suited to move from landline or app-based services based on employee preferences and remote work trends.


Based on the emergence of this UCaaS module in context of broader IT and economic trends, Amalgam Insights provides the following recommendations.

First, aggregate the usage and cost management of landline, conferencing, mobility, and relevant voice applications into a single area. The tradeoffs between landline, wireless, endpoint-neutral apps, and embedded voice-related APIs cannot be fully analyzed or rationalized unless the business gains visibility to all voice usage in one area. This view allows companies to see if there are duplicate solutions in place or whether specific solutions have been abandoned or used to a greater extent. This perspective is especially important in light of the tumultuous business environment of the past year where the combination of remote work, work-life balance constraints, time-shifting, process automation, and the increased use of video are leading to fundamental and rapid technology shifts. Changes that used to take five to ten years to occur are now happening in months and this is the new normal.

Second, drive beyond license and account-level economics for your voice, telephony, mobility, and endpoint spend and consider how to analyze cost at the level of calls, transactions, and data across all areas of telephony. As voice has become an app, it is important for companies to treat voice as the data that it has become and to track not only call traffic and minutes of usage, but also bandwidth usage and the security of the endpoints involved in the conferencing and calls being made. To know how much an organization needs to invest in bandwidth and data plans, one must first track telephony on a per-call and per-megabyte level as well as understand which calling, conferencing, and data plans are most appropriate for employees to use.

Finally, as a broader recommendation, Amalgam Insights believes that the combination of public cloud, the shift of telephony from hardware to software, and the trends towards remote work all require telecom expense managers to look beyond carrier management and to consider all of the applications, subscriptions, and services associated with communications and collaboration. The world of telecom expense management provides a mature framework and rigor for cost management, invoice processing, dispute management, vendor management, and contract negotiations that is increasingly needed in the rest of IT. This is a time for CIOs to take best practices from their telecom expense teams and to work on their center of excellence for IT expense management and technology rationalization.

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Market Alert: Zuora Launches Collect AI to Increase Subscription Revenue

On March 17th, 2021, Zuora announced the launch of Zuora Collect AI as an addition to its suite of subscription management applications. As a research firm focused on the practical use of AI in the enterprise and a firm that provides guidance on subscription finance, expense management, invoice processing, and business model management, we explored this announcement to consider what aspects of artificial intelligence have been brought into this product and the business value that can be expected from this launch.

Zuora Collect AI is focused on the value of payment processing and collections. This application analyzes a variety of transaction characteristics to discover top drivers that affect payment and revenue recognition. These characteristics include payment methods such as the bank, credit card, or payment gateway involved as well as client characteristics such as the region, payment value, and history of payment success.

Rather than simply treat all customers as a single payment cohort under the same calendar for all payment processing activities, Zuora Collect AI allows for greater granularity of payment pursuit, transaction channels, and recovery tactics. As a result, Zuora customers can be expected to reduce the dunning rates and delinquent payment status while providing a more efficient dunning process for late payers. In addition, Zuora Collect AI collects data daily from a variety of payment gateways and payment methods to continue updating parameters associated with payment success over time.

This use case is a strong value proposition for machine learning in that it combines the volume of billions of transactions across hundreds of currencies and regions and uses this information to solve a million dollar problem for enterprises. Zuora’s use case fits into the framework for practical, high-value AI that Amalgam Insights has advocated for years.

To elaborate on how this is a scalable issue, consider that Amalgam Insights estimates that the average subscription revenue company faces revenue leakage of 2% when using a billing system and will only recover 40 – 50% of that revenue over time. With better tuned and scheduled payment processes, organizations could gain an extra 10 – 20% in revenue recovery.

This difference would have equated to a 5% – 10% percent increase in net profit in 2020 for the average non-financial services firm that registered a 4% net margin in 2020.

In Zuora’s public-facing documentation, they have documented three organizations (Whitepages, RankingCoach, and Motortrend Group) with results ranging from 10 – 18% increases in payment recovery through the use of Zuora Collect AI compared to manual payment retries and an umbrella policy for retrying payments within collections dunning cohorts.

Although this type of payment analysis could theoretically be done by an on-site data scientist, Amalgam Insights notes that one of the key challenges with expense and payment optimization is the changing nature of the data as new payment types, schedules, quantities, and patterns emerge. Because of these changes, transactional optimization is not served well by creating a one-time model to find optimal payment processing times and patterns for each customer and payment type. At volume, it requires ongoing data intake and monitoring to maintain the efficacy that maximizes revenue optimization which is better served through treating revenue optimization as an ongoing process and service rather than a one-time audit and model creation.

Based on this announcement, Amalgam Insights makes the following recommendation for subscription and usage revenue-based organizations:

First, pursue the use of machine learning to support revenue recovery.

This one activity has the potential to increase your net profit margin by 10% or more even if your organization already has a mature dunning process for subscription customers.

Second, invest in the ongoing maintenance and updating of these models.

To maintain these gains over time, your organization will need to invest in daily data processing and ongoing model optimization to ensure that your payment collection schedules and processes keep up with ongoing trends. Otherwise, Amalgam Insights estimates that the models created will lose their value within 18-24 months and leave the organization back at a point where significant revenue is being unnecessarily lost due to poor dunning and payment processing schedules.

The big takeaway here is that machine learning continues to be brought into the business world to solve the highly transactional analyses that are too time-consuming to be solved through manual analysis or even through traditional data analysis tools. Take advantage of the increasing availability of productized AI and the data associated with digital payments to solve operational issues with million-dollar payback potential.