Session Notes: Karen — Introduction and Work Areas

June 3, 2026 · Nate St. Pierre, Karen

Overview

This was an introductory session with Karen on Day 2 of the engagement. The goal was to get to know Karen, understand her background, and map the major areas of work she owns before going deeper in a follow-up session later in the day. Karen gave a clear and candid account of her history at RCB and the challenges she navigates. The conversation ran about 28 minutes and covered her background, the major buckets of her current work, and left open space for a follow-up on specifics.

Karen's Background

Karen holds an electrical engineering degree and spent the early part of her career at National Instruments in Austin, Texas, and then at GE Healthcare. At National Instruments she worked on arbitrary waveform generators — hardware suites used to automate production testing for other manufacturers' equipment. At GE Healthcare she worked on patient monitoring hardware. Both were hands-on hardware engineering roles.

After that, she stepped away from professional work for about fifteen years to raise her kids and help co-found a hybrid school — a structure where kids attend school three days a week and work from home two days, designed intentionally before COVID made that model common. She also taught Spanish at the school for a period.

When she was ready to return to work, she wanted part-time hours — a maximum of twenty hours a week — which made most engineering roles impractical given how much the field had changed during her time away. She applied widely and found it difficult to get traction. She joined RCB starting on the production floor. During her interview, Briana had already indicated that there could be a path to front-office work, and that's eventually what happened. Spending time on the production floor first gave Karen a useful foundation — she now draws on that experience directly in her work on labor data and process standardization. She's been with the company for about three and a half years.

Major Work Areas

Labor Data Capture and Analysis

One of Karen's most significant ongoing projects is building usable labor rate data for the production operation. The goal is to know, for any given product or SKU, how many man-hours it takes to produce and what that costs. That information is used for three things: pricing products for customers, capacity planning for the production schedule, and setting production goals so workers know what output is expected of them.

Data is currently captured using checklists — Microsoft Forms-based — that production workers fill out as they work through processes. The raw output comes back as an Excel spreadsheet. Karen then works through that output manually, going line by line to clean and normalize it before any analysis can happen.

She named the core challenge clearly: product variety. RCB produces an enormous range of products, each with different production steps, and even within a single product line there's significant variation. Getting meaningful, comparable data across all of that variation is hard. Some fields on the checklists are standardized across products; others differ. The raw data that comes back isn't clean enough to analyze directly without manipulation.

Karen also identified a structural tension in how the checklists are being used. They currently serve two purposes: they're used as training documents — walking a newer worker step by step through a production process — and as data capture instruments. Her observation was that those two purposes have incompatible requirements. A good training checklist is detailed and instructional, covering every step. A good data capture form is minimal and structured, collecting only the fields needed for analysis. Trying to make one document serve both purposes means it's not doing either particularly well. She noted this explicitly: "Is it doing two things at once okay, or two things poorly?"

She described sitting with Rachel on the production floor to walk through what the checklist actually looks like in practice, and confirmed that the tension is real — a fully trained operator and a new worker need very different versions of the same document.

The end goal of the labor data work is a master reference: for each product, a single number representing the man-hours required per unit, regardless of how many people worked on it. That number feeds pricing, capacity planning, and internal production targets. Getting there is the challenge.

Product Entry into Antera

Karen is also involved in maintaining the product catalog in Antera Advance, the company's order management system. Adding a product is more involved than it might appear — it's not purely data entry. It involves deciding whether a product is worth selling, researching appropriate marketplace pricing, and entering a full set of product attributes and specifications. The pricing field in particular requires research into what comparable products go for, because pricing isn't just a cost-plus calculation.

The catalog has been built up over time by multiple different people without a standard entry process, which has created inconsistency throughout. Some products have pricing entered for a specific order quantity with nothing else. Others are missing fields entirely. Karen's description of the trust level: when you look at a product's price in Antera, you can't assume it's correct. "Everything has to be double checked" is how she put it. She's been working through the catalog systematically to clean it up, which is a significant ongoing effort.

There's an additional dynamic: sales sometimes adds products ad hoc in real time during customer calls, when a customer needs a size or configuration that isn't already in the catalog. This means new products enter the system under time pressure, often without the research and review that a properly priced entry would have. If that product is used again later, whatever price was entered initially — which may have been a one-time estimate — is what's in the system.

Pricing Updates

Separate from product entry is the pricing update process — when pricing changes, either due to vendor cost changes or internal pricing decisions based on labor rate data. Karen confirmed this is a distinct workflow from product entry, even though the two are related. This process also has an overhead and indirect labor component that connects to the broader labor rate analysis work.

Sage and ASI Integration

Antera connects to two distributor platforms: Sage and ASI. The Sage connection is particularly important because Sage data pushes directly to RCB's public retail website. End customers — businesses placing orders for recognition products, branded merchandise, and similar items — can place orders through the website, and the product catalog on that site is driven by what's in Sage.

Karen has been working on the Sage integration as part of the broader Antera cleanup effort, since data quality issues in Antera flow forward into what distributors and retail customers see. ASI is maintained separately — there is no automatic sync, so it requires manual effort to keep current alongside Sage and the website.

This detail — that RCB has a live retail website driven by Sage catalog data — was new context for the engagement.

Production Floor Standardization

Earlier in her time at RCB, Karen was more involved in the physical production floor — helping organize the space, standardize where equipment and materials are stored, and make it easier for multiple people to work comfortably in shared areas. She described this using language consistent with 5S-style process improvement: getting things organized so that the space works for more than one person's working style.

She was careful and diplomatic about this — the production floor grew up around the way Cindi worked, and adapting it for multiple workers involved some navigation. That work is mostly done, though she still engages informally with the floor team on process questions.

Follow-Ups

• Karen mentioned she didn't have additional AI-related project areas to name off the top of her head, but invited Nate to reach out by email and said she'd do the same if anything came to mind.
• A follow-up session will go deeper on specific workflows for labor data capture and product entry.