Evaluating The Role Of Automation In Cost Reduction

When considering implementing an Autonomous Mobile Robot (AMR) system, conducting a Return on Investment (ROI) analysis is crucial. The evaluation should encompass both costs and benefits, including tangible and intangible aspects over a practical timeframe. Here's a comprehensive breakdown of what you should take into account: 1- Initial Costs (CapEx): - Robot purchase cost: Unit price per AMR. - Fleet management software/license fees. - Infrastructure upgrades: Wi-Fi, charging stations, navigation, etc. - Integration costs: ERP/WMS/WCS integration, APIs, and IT support. - Training and onboarding for staff handling AMRs. - Installation and deployment services. 2- Ongoing Operational Costs (OpEx): - Maintenance and support: Annual contracts, spare parts. - Battery replacement (typically every 2–3 years). - Software updates and cloud service fees. - Operator oversight: Supervisors or technicians monitoring AMRs. - Energy consumption costs (charging expenses). 3- Cost Savings / Financial Benefits: - Labor cost reduction: - Decreased need for workers in repetitive transport tasks. - Reduced dependence on temporary or seasonal labor. - Productivity gains: - Enhanced throughput or reduced cycle time. - Potential for 24/7 operation without fatigue. - Reduced damage and safety incidents: - Decreased injury claims and downtime. - Minimized goods damage due to consistent handling. 4- Intangible / Strategic Benefits: - Scalability and flexibility for easily adding more robots. - Improved employee satisfaction through reduced manual labor. - Enhanced space utilization as AMRs can navigate tight spaces effectively. - Data and analytics for improved tracking and optimization opportunities. Implementing or considering AMR in your operation is critical to face the challenges of managing manpower while improving productivity !!

Sales & Marketing Drive Revenue Operations Drives Profit What are you doing in 2024 to make sure both are optimized? Start with an audit of your processes. 1️⃣ Have each team member make SOP's for all their daily, weekly, monthly tasks. Make sure it's detailed. You need this for a few reasons - 1) to find out what they're using for processes 2) for them to think through the steps they take 3) for someone else to pick up the thread if they leave or are on vacation. 2️⃣ Make sure they're putting in a time estimate on manual work (processing inbound sales orders, EDI, demand planning, outbound POs, logistics tracking, inventory management, etc). KEY TO NOTE: Likely they will underestimate this hourly work by at least 1/3 if not more. When you're reviewing their analysis, calculate and add to this. 3️⃣ Have them identify if there is an automated solution to their manual work - ask for research on tech stack, different options, including syncing google or Excel sheets together to eliminate double entry. Having them do this is critical for a couple reasons - 1) your time is better spent driving your company forward 2) they are most likely to know which features are needed 4️⃣ Ask for an analysis of the time it's taking or manual work multiplied by their hourly rate vs. what an automated solution might cost. Now you have a cost of what your processes are currently costing you to compare against the cost of automation. I would bet that 90% of the time, automation is cheaper in the long run. Plus less chance of mistakes in those processes, which also saves you money.

Focusing on AI’s hype might cost your company millions… (Here’s what you’re overlooking) Every week, new AI tools grab attention—whether it’s copilot assistants or image generators. While helpful, these often overshadow the true economic driver for most companies: AI automation. AI automation uses LLM-powered solutions to handle tedious, knowledge-rich back-office tasks that drain resources. It may not be as eye-catching as image or video generation, but it’s where real enterprise value will be created in the near term. Consider ChatGPT: at its core, there is a large language model (LLM) like GPT-3 or GPT-4, designed to be a helpful assistant. However, these same models can be fine-tuned to perform a variety of tasks, from translating text to routing emails, extracting data, and more. The key is their versatility. By leveraging custom LLMs for complex automations, you unlock possibilities that weren’t possible before. Tasks like looking up information, routing data, extracting insights, and answering basic questions can all be automated using LLMs, freeing up employees and generating ROI on your GenAI investment. Starting with internal process automation is a smart way to build AI capabilities, resolve issues, and track ROI before external deployment. As infrastructure becomes easier to manage and costs decrease, the potential for AI automation continues to grow. For business leaders, identifying bottlenecks that are tedious for employees and prone to errors is the first step. Then, apply LLMs and AI solutions to streamline these operations. Remember, LLMs go beyond text—they can be used in voice, image recognition, and more. For example, Ushur is using LLMs to extract information from medical documents and feed it into backend systems efficiently—a task that was historically difficult for traditional AI systems. (Link in comments) In closing, while flashy AI demos capture attention, real productivity gains come from automating tedious tasks. This is a straightforward way to see returns on your GenAI investment and justify it to your executive team.