Process Improvement Methods

I am constantly thinking about how to foster innovation in my product organization. Building teams that are experts at execution is the easy part—when there’s a clear problem, product orgs are great at coming up with smart solutions. But it’s impossible to optimize your way into innovation. You can’t only rely on incremental improvement to keep growing. You need to come up with new problem spaces, rather than just finding better solutions to the same old problems. So, how do we come up with those new spaces? Here are a few things I’m trying at Duolingo: 1. Innovation needs a high-energy environment, and a slow process will kill a great idea. So I always ask myself: Can we remove some of the organizational barriers here? Do managers from seven different teams really need to say yes on every project? Seeking consensus across the company—rather than just keeping everyone informed—can be a major deterrent to innovation. 2. Similarly, beware of defaulting to “following up.” If product meetings are on a weekly cadence, every time you do this, you are allocating seven days to a task that might only need two. We try to avoid this and promote a sense of urgency, which is essential for innovative ideas to turn into successes. 3. Figure out the right incentive. Most product orgs reward team members whose ideas have measurable business impact, which works in most contexts. But once you’ve found product-market fit, it is often easiest to generate impact through smaller wins. So, naturally, if your org tends to only reward impact, you have effectively incentivized constant optimization of existing features instead of innovation. In the short term things will look great, but over time your product becomes stale. I try to show my teams that we value and reward bigger ideas. If someone sticks their neck out on a new concept, we should highlight that—even if it didn’t pan out. Big swings should be celebrated, even if we didn’t win, because there are valuable learnings there. 4. Look for innovative thinkers with a history of zero-to-one feature work. There are lots of amazing product managers out there, but not many focus on new problem domains. If a PM has created something new from scratch and done it well, that’s a good sign. An even better sign: if they show excitement about and gravitate toward that kind of work. If that sounds like you—if you’re a product manager who wants to think big picture and try out big ideas in a fast-paced environment with a stellar mission—we want you on our team. We’re hiring a Director of Product Management: https://lnkd.in/dQnWqmDZ #productthoughts #innovation #productmanagement #zerotoone

Project closed? Bring on the champagne! (And cue the manual detail entry 😓) (Automation Tip Tuesday👇) So this advertising agency client of ours deals with a large amount of new projects coming in weekly. Their process wasn’t too pretty, though. Once the deal was sealed, they requested relevant project details from the client via email, then manually created the project in their PM tool. We smoothed things out quickly. 1️⃣ Client set to “won” in CRM. ↓ 2️⃣ Client automatically receives a pre-filled link to a form like Zapier Interfaces or Jotform. ↓ 3️⃣ Once the form is completed, a new project is automatically created in their tool of choice (Airtable, Asana, Trello, whatever.) Bonus: we set up the field forms to create specific project types based on various templates. Business is humming along with zero manual entries to mar the fun. Got a stellar service — with a stressful process? Get the pros on your case 💥 -- Hi, I’m Nathan Weill, a business process automation expert. ⚡️ These tips I share every Tuesday are drawn from real-world projects we've worked on with our clients at Flow Digital. We help businesses unlock the power of automation with customized solutions so they can run better, faster and smarter — and we can help you too! #automationtiptuesday #processautomation #softwareintegrations

Is it possible to use tech innovation to accelerate mundane processes? Moving fast forward, I'll say "absolutely!" And now, let's get to the most interesting part of "how." Let's consider the adoption of AI in pharma marketing, for example: the same AI can be used to speed up content creation while ensuring all the rules are followed. In our eWizard, a content experience platform for pharma, we are developing a feature that allows users to see the likelihood of content approval, thus speeding up time-to-market. If there are any issues (like content mismatches, sensitive images, or missed references), you receive an alert and, importantly, suggestions on how to improve your piece. Once the content gets the green light, you can recycle and tweak it for future campaigns. Thanks to AI technology, you can automatically tag all your texts and images to compose a new personalized campaign using the already-approved modules. Now, onto some real-life cases: using eWizard, one of our clients has streamlined their content production and cut the time-to-market from three weeks to just one. Impressive, right? So, while technology is posing many new questions, it is also always giving us opportunities to find answers. #ai #mlr #pharmamarketing

“Now, researchers at MIT and Harvard University have developed an efficient process that can convert carbon dioxide into formate, a liquid or solid material that can be used like hydrogen or methanol to power a fuel cell and generate electricity. Potassium or sodium formate, already produced at industrial scales and commonly used as a de-icer for roads and sidewalks, is nontoxic, nonflammable, easy to store and transport, and can remain stable in ordinary steel tanks to be used months, or even years, after its production. The new process, developed by MIT doctoral students Zhen Zhang, Zhichu Ren, and Alexander H. Quinn, Harvard University doctoral student Dawei Xi, and MIT Professor Ju Li, is described this week in the journal Cell Reports Physical Science. The whole process—including capture and electrochemical conversion of the gas to a solid formate powder, which is then used in a fuel cell to produce electricity—was demonstrated at a small, laboratory scale. However, the researchers expect it to be scalable so that it could provide emissions-free heat and power to individual homes and even be used in industrial or grid-scale applications. Other approaches to converting carbon dioxide into fuel, Li explains, usually involve a two-stage process: First the gas is chemically captured and turned into a solid form as calcium carbonate, then later that material is heated to drive off the carbon dioxide and convert it to a fuel feedstock such as carbon monoxide. That second step has very low efficiency, typically converting less than 20 percent of the gaseous carbon dioxide into the desired product, Li says. By contrast, the new process achieves a conversion of well over 90 percent and eliminates the need for the inefficient heating step by first converting the carbon dioxide into an intermediate form, liquid metal bicarbonate. That liquid is then electrochemically converted into liquid potassium or sodium formate in an electrolyzer that uses low-carbon electricity, e.g. nuclear, wind, or solar power. The highly concentrated liquid potassium or sodium formate solution produced can then be dried, for example by solar evaporation, to produce a solid powder that is highly stable and can be stored in ordinary steel tanks for up to years or even decades, Li says.” https://lnkd.in/g4pHVdss

The average churn rate exceeds the average growth rate in U.S. hospitals by 3%. Patients may leave for a variety of reasons – some beyond control of the health system, such as changing residency or insurance coverage. What IS in the health system’s control is the patient experience. But that's difficult to improve when the delivery of care is fragmented and inefficient. Here are some primary examples of missed opportunities: • Diagnosis: 1 in 18 ED patients receive an incorrect diagnosis [1] • Referral: 22% of patients were referred out-of-network by physicians [2] • Follow-up: Less than 40% of recommendations for additional imaging are completed [3] Despite health systems throwing more people at many of its core challenges, the struggles persist. The answer to really becoming more efficient is AI technology, which can assist with helping reduce churn at three different points of the patient’s journey: Patient capture: Flagging and triaging cases for clinicians to review to ensure patients don’t fall through the cracks and suffer preventable medical harm. Care coordination: Driving digital collaboration between clinical stakeholders on each patient identified as being in need of care, simplifying communication and access to clinically relevant data. Follow-up: Identifying follow-up recommendations in records and alerting clinicians to them to ensure patients are reached out for critical follow-up imaging in an orderly fashion. However, there is the potential for AI to miss the mark in these areas if it’s deployed in a fragmented, disconnected and disparate fashion. If anything, improper deployment can exacerbate the fragmentation problem and uphold the clinical service line silos that already exist. What’s needed is a holistic approach, across the patient journey, where the patient is managed from entry through to the operating table and post. This is where a platform has become the only real viable technical option for AI to drive better patient care with maximum efficiency. By deploying AI holistically, in an inter-woven fashion, clinical care teams can improve the patient experience with the following examples: Improved disease awareness: A PE response team at Yale New Haven Health found that AI could help clinicians identify 72% more patients in need of vascular care consultations that were initially overlooked. [4] Reduced time to treatment: A radiology team at UT Southwestern found using AI could help reduce prescription retrieval time for patients with incidentally-found pulmonary emboli from 38.6 hours to 2.2 hours. [5] Reduced patient hospital length of stay: Clinicians at Cedars-Sinai Medical Center found AI in radiology workflows could reduce length of stay for patients with intracranial hemorrhages (ICH) and pulmonary emboli (PE) by 31 hours and 50 hours, respectively. [6] Reduced readmissions: An average 33% reduction in readmissions observed across 13 hospitals who were using AI for ICH and PE patients. [7]

Your problem is to bridge the gap you don’t see It’s between now and the goal to reach. Have you ever felt overwhelmed by inefficiencies in your practice? I recently worked with a local chiropractor who faced this exact challenge We turned things around remarkably, and this is how we did it ↓ Dr. Williams was struggling with: → High patient wait times → Inefficient administrative processes The bottleneck was primarily in the patient intake process Our mission was to reduce frustration for both staff and patients. I introduced Dr. Williams to my network of professionals They integrated a digital intake system to streamline the process. This system allowed patients to fill out necessary forms online before their appointments. He also conducted training sessions for the staff to ensure a smooth transition and optimal use of the new system. The results were astounding. The new system reduced patient wait times by 50% The new system led to a significant increase in patient satisfaction. The streamlined operations led to a 20% rise in new patient referrals The happy patients shared their positive experiences with others. Dr. Williams was now focusing exclusively on his practice He was not the middleman anymore. Delegation helped him to: → Plan for his finances → Create competitive executive bonus plans → Review the benefits package for his staff The moral here is you can’t be everywhere. Asking for help is your superpower. This experience reinforced a crucial lesson: Embracing technology can significantly improve operational efficiency and patient experience. You can address inefficiencies head-on and leverage modern solutions Private clinicians can enhance their practice and better serve their patients. Have you implemented any technology solutions in your practice? Share your experiences in the comments below Let’s learn from each other and continue to improve patient care!

Unlocking Excellence in Hospital Operations with Data-Driven Insights In the complex world of healthcare, where every second counts and resources are stretched thin, data-driven decision-making is a game-changer for hospital operations. By leveraging data to track key performance metrics, hospitals can uncover inefficiencies, optimize workflows, and deliver superior patient care. Inspired by Lean principles, this approach fosters a culture of continuous improvement that transforms challenges into opportunities. Let’s dive into how data can revolutionize hospital operations and drive meaningful change. Why Data Matters in Healthcare Data acts as a clear lens, illuminating the inner workings of hospital processes. By systematically tracking metrics like patient wait times, bed turnover rates, and medication error rates, administrators and clinicians gain actionable insights into inefficiencies. These insights enable hospitals to prioritize improvements that enhance patient outcomes, reduce costs, and improve staff satisfaction. The key is moving from reactive fixes to proactive, data-informed strategies. Key Areas Where Data Drives Impact Optimizing Patient Flow Bottlenecks in patient flow—such as delays in lab result processing or slow discharge procedures—can frustrate patients and strain resources. By analyzing admission-to-discharge data, hospitals can pinpoint where delays occur. For example, one hospital discovered that lab result delays stemmed from manual data entry. By automating this process, they cut turnaround times by 25%, improving patient satisfaction and freeing up staff for other tasks. Streamlining Resource Management Overstocked supplies tie up capital, while shortages disrupt care. Data on supply usage patterns helps hospitals maintain optimal inventory levels. For instance, tracking bandage or IV fluid consumption can prevent over-ordering, saving costs without compromising care quality. One healthcare system reduced inventory waste by 15% through data-driven forecasting, redirecting savings to patient care programs. Enhancing Staff Scheduling Understaffing during peak times or overstaffing during lulls can harm efficiency and morale. By analyzing patient volume data, hospitals can align staffing plans with demand. For example, an ER department used historical data to predict busy periods, adjusting nurse schedules to ensure adequate coverage. This reduced wait times by 20% and eased staff burnout. Building a Data-Driven Culture To maximize impact, hospitals must integrate data into daily operations: - Engage Frontline Staff: Train nurses, physicians, and administrators to interpret data and suggest improvements. A nurse’s insight into workflow hiccups can spark transformative changes. - Conduct Regular Reviews: Monthly or quarterly data reviews keep teams focused on continuous improvement, ensuring gains are sustained and new inefficiencies are caught early.

After 300+ automation implementations, I've learned a thing or two. 10 best practices that drive long term success: (also great if you want more value out of automation) 1. Focus on groups of 3 to 5 Don't try to do 1000 automations at once. Get 3 to 5 done and move on to the next group. 2. Test/troubleshoot before launch Spot check records that match trigger conditions. Send content to yourself to make sure its 100%. Run test records through automations. 3. Don't reinvent the wheel Use blueprints, tutorials, and best practices fully. Starting complex is risky in multiple ways. 4. Master the pilot group Large or apprehensive organizations especially. Dip your toes in with an interested internal group. Show success and expand to everyone. 5. Manage automation risk Riskiest to safest: Client comm, Candidate comm, Internal, Database Update. Start safe. 6. Self awareness What are internal expectations for deliverables? Strategize, measure, and optimize accordingly. 7. Start easy Focus on high ROI and repeatable journeys. Quick wins build confidence, increase buy-in, and momentum. 8. Self service is the goal The ultimate goal is building out on your own. Absorb knowledge and build confidence with consistent action. Check in on new features and stay connected to learn new ideas. 9. Marathon mindset Consistency is key to success. Automation is a marathon not a sprint. Worst thing you can do is take a long break. 10. Start from back to front Which of the following experiences would you choose? Bad - Bad - Bad - Good. Good - Bad - Bad - Bad. I know my answer, plus highest ROI is on the back end. ... A bonus just for you! 11. Map your process and automations Find gaps and automation opportunities. Future proof your automation success. Happy automating! _ Staffing Automation posts weekdays at 11 AM EST. #BuildWithBilly

How quickly can you gather the smallest amount of data to reliably predict innovation success?   If you work within any division in a business that involves innovation, perhaps you have had reason to explore this question yourself.   Many entrepreneurs working in AI are suggesting they can do a lot to make better choices.   In October, we at Rapid Alpha hired our own in-house software development team to explore opportunities for AI and automation. Based on our experience in addressing our own needs and how we could apply automation and AI on behalf of our clients, I can tell you two things with confidence.   One. Developing automation tools offers so many benefits that AI does not need to be a central focal point in mastering tools to deliver a substantial Return on Investment (ROI).   Two. The present and future of AI is Human in the Loop AND proprietary datasets.   Earlier this month, I presented at the AI Focus Seminar. In my presentation, I detailed the opportunities to automate certain aspects of research by leveraging the benefits of human-in-the-loop (HITL). I outline the basic premises behind how we assess the value of an automation effort, the effectiveness of our work, and how we consistently help our clients ask the right questions.   https://lnkd.in/gcfa4_PD   There are a lot of limitations that AI faces when it comes to any effort related to competitive intelligence. Before we ever move to AI to do the things it is effective at, like classifying information, we see value in just automating efforts like opening web pages, scraping information, and pushing data into structured databases for retrieval. In essence, we build a custom data set of things you know you need to know and share to get buy-in on any innovation effort.   Unlike commercial tools that are intended to work for everyone and more likely work well for no one, we recommend ALWAYS starting with documents and processes you already use.   In one example, we started with an Idea Capture and walked through opportunities to support an analyst in finding key information using our client’s process to make a go-no-go decision. While the deep dive into their process uncovered NEW research opportunities, simply augmenting their existing process paid immediate dividends on multiple other efforts being assessed.   Once we have our initial dataset, we can take it to another level by scaling up the volume of data from different sources and applying AI classifiers to move additional unstructured data into a database that can be searched. The net result is having a much larger data set to pull information from. You can manually review information, monitor what insights and assumptions inform go-no-go decisions, and see if your innovation process is improving in its ability to predict market success.   What are some of the things you might want to automate or save in a database? #innovationmanagement #HITL #intellectualproperty