For most of its history, Telecom Expense Management (TEM) has served a very specific type of customer: the traditional enterprise that buys WAN access, Internet connectivity, mobile services, and MPLS circuits to connect offices and users. TEM platforms were designed to answer financial questions. What do we have? Where is it? Who bills us? How much are we paying? Are we paying correctly? Can we optimize it? The model worked well for two decades. But a new category of

In a traditional mobile account, it's easy to identify a line: you just use the phone number . For smartphones, that works fine as a unique service ID in your inventory and billing systems. With IoT lines , it's not that simple. IoT services often don't behave like phones. Many don't use voice at all. Some don't even truly "use" the phone number that the carrier assigns. Yet the same account may contain multiple identifiers: ICCID MSISDN IMSI If you pick the wrong one as

Why Monthly Mobility Invoice Audits Still Matter (Even After Issues Are "Fixed") There's a common assumption in mobility expense management: once an issue is fixed with a carrier, it should stay fixed. In practice, that's not how it works. Large mobility carriers including AT&T, Verizon, and other operate highly complex billing systems with multiple platforms, provisioning paths, contracts, and automation layers. A change in any one of those layers can unintentionally rein

Federal Universal Service Fund (USF) recovery charges can appear on an invoice even when you don't see any separate "voice usage" line items that month. That's because USF isn't triggered by minutes. It's tied to the carrier's assessable end-user telecommunications revenue (primary interstate/international revenue) and how the carrier chooses to recover that cost. Importantly, the FCC does not require providers to pass their USF contribution through to customers, and it als

Contract negotiations and operational strategy go hand in hand. The rates you negotiate don't just determine your monthly invoice - they shape the day-to-day work required to manage usage, prevent surprises, and control risk. A "good deal" on paper can become a costly operational burden if the rate structure pushes risk onto the customer. To show what I mean, here's an IoT example comparing two real-world pricing designs: AT&T vs. T-Mobile. The Key Point: Rate Design Drives

For years, Bring Your Own Device (BYOD) has been sold as a simple equation: let employees use their own phones and laptops, save money on corporate devices, and everyone's happy. Fast forward to end of 2025, and the picture is a lot messier. The global BYOD market is now worth well over $100 billion and growing fast, driven by hybrid work and the expectation that "work can happen anywhere." Most organizations allow at least some form of BYOD, and many employees use personal

A Policy Checklist for Enterprises For years, international roaming has been painfully simple and painfully expensive. An employee lands in London, their phone lights up with a "Welcome abroad!" text, and suddenly you're paying $10-$15 a day for the privilege of email, maps, and Teams calls. Travel eSIMs break that model. With a few taps, a traveler can download a local or regional data plan, often at a fraction of classic roaming rates. That's great for the employee's exp

When enterprises shop wireless contracts, most of the attention goes to one number: the Monthly Recurring Charge (MRC) per line. In the U.S., that usually means comparing offers from the three facilities-based carriers: AT&T Mobility, Verizon Wireless, and T-Mobile . On paper, one carrier may look clearly cheaper than the others. But when the invoices start coming in, finance asks a painful question: "If we negotiated such a good rate, why is the bill still so high?" MRC vs

Many enterprise clients who manage IoT lines through AT&T, T-Mobile, or other mobility providers have historically operated on Pod 11 within Cisco Jasper (Control Center). Over the last year, however, carriers have been transitioning customers to Pod 17 or Pod 19 , as the legacy pod approaches deprecation. The newer pods promise better API performance, updated security and identify management, more reliable lifecycle automation, and overall improved system stability. Ideal

Over the past year, I've been integrating AI into different parts of my mobility expense management workflow. Not through massive projects, but through small, practical steps that make daily work faster, cleaner, and more scalable. One of the biggest wins has been using AI APIs to automate tasks that used to require a lot of manual review. Automating Rate Plan and Device Classification I first used AI to identify rate plan allowances by analyzing plan descriptions. Normall

Most mobility cost strategies were designed around smartphones and tablets: one device, one user, fairly stable usage patterns. You trend each line's usage over time, pick the right plan, and revisit periodically. It's not perfect, but it's predictable. IoT is different enough that this approach can actually mislead you. In our Verizon IoT environment, we saw something that looked completely backwards at first glance: total data usage went down, but monthly recurring charge

Managing enterprise mobility cost has long been a tedious and manual process. For many organizations, identifying rate plan allowances buried in carrier invoices requires hours of research and cross-referencing. This step, though essential to accurate cost optimization, often slows down analytics teams and limits how quickly insights can be delivered. The Challenge: Manual Data Interpretation Traditionally, mobility analysts manually review each rate plan description to det

When I review mobility invoices from major North American carriers, one pattern jumps out every time: the biggest international roaming spend usually isn't pay-per-use data. It's the flat daily passes. TravelPass, International Day Pass, "IDP" or whatever the label, the model is the same: a fixed daily fee that lets employees "use their phone like at home." For Verizon and AT&T, that's typically around $12 per day per line in most destinations, with variations for Canada/M

Most U.S. carriers including AT&T Mobility and Verizon Wireless let you suspend a line with billing (you keep paying a reduced or even the full charge) or suspend without billing (you stop paying, but usually for a limited time). What I see over and over: companies put lines on suspend with billing, leave them there for months, sometimes years and quietly keep paying. At that point you have to ask: are we preserving value, or just paying rent on a parking spot nobody uses? T

Two quarters ago, a leadership team I worked with thought their wireless run-rate was stable. Headcount was flat, hiring controls were in place, and no one had requested new device budgets. Yet invoices crept up month after month. A quick cross-check found what the spreadsheets hid: lines still active for people who had left, devices marked "spare" that were checking in from the field, and numbers ported to a new carrier but never disconnected at the old one. Within thirt

Talking to decision-makers about how to control cost when data jumps even though the fleet size is flat. When the number of deployed devices holds steady but network usage surges, it can feel like the ground moved beneath a carefully planned budget. In IoT, that "step change" rarely comes from adding more SIMs; it comes from small behavior shifts, an over-chatty firmware build, a retry storm, a new payload format that ripple through pooled plans. If you manage Cisco IoT Con

An executives-friendly take on the Niquivest method for mobility invoices. Every month the wireless bill lands, the number moves, and someone asks, "Why?" The right answer isn't a data dump; it's a short, confident read on what changed and what we're doing about it. That's what the Niquivest approach gives you. No equations, just a consistent way to separate signal from noise. The three levers (plan English) When spend shifts, one of three things moved: Rate (the price y

Many employees who've relocated abroad but kept U.S. lines (Verizon, AT&T, T-Mobile) create quiet double spend: plan MRC + international/roaming passes. Flag persistent roamers, confirm status, then move them to local service and park the U.S. number. What to look for (fast signals) Repeated pass/roam activity for 60-90 days. One dominant country in usage/roam records. Roaming most days in a cycle (practically living abroad). My take: 15+ roaming/pass days in a month for

AI keeps getting smarter. But for wrapping an API in an IT/mobility cost workflow, does chasing the newest model actually matter? It depends on the task. My use case here: analyze mobility data across invoice months, surface drivers, and generate a short explanation. Models I tested (price reference) Prices change, so treat these as reference points and always check OpenAI's page for current rates. Model Input Output gpt-4.1-mini $0.40 $1.60   OpenAI gpt-4.1-nano $0.10 $0.

Most people assume that once their wireless contract ends, their monthly bill automatically go down. After all, if the phone is paid off, shouldn't the cost drop too? Unfortunately, that's not how the big carriers, Verizon, AT&T, and T-Mobile work. In fact, many customers are surprised to find their bills stay the same or even go up unless they take action. That's why a wireless plan audit can save you real money. Verizon: The Hidden Carryover Cost Imagine this: Sarah, a