How do you leverage technology and automation to enhance value stream performance?

- 🗺️ Conduct process mapping and analysis to create a visual representation of your processes, including inputs, outputs, activities, roles, and dependencies. - 🛠️ Utilize various software tools and methods such as value stream mapping, business process modeling notation, or lean six sigma to analyze your process maps. - 🔍 Identify sources of inefficiencies, bottlenecks, and opportunities for improvement through detailed process analysis. - 📊 Implement automation technologies to streamline workflows, reduce manual tasks, and enhance overall efficiency. - 🚀 Continuously monitor and optimize automated processes to ensure sustained improvements in value stream performance.

Given that the concept of value stream management has deep roots in Lean Six Sigma, the SIPOC model provides a straightforward method for process mapping. Essentially: Supplier -> Input -> Process -> Output -> Customer Each of these stages expands into subprocesses and workflows, often with Interdependence within the stage and between stages. A great way to map processes and identify gaps, opportunities and redundancies, especially when combined with Systems Thinking.

I start by outlining each step of the existing processes, identifying key inputs, outputs, and bottlenecks. This visual representation allows me to pinpoint areas where technology can drive efficiencies. Once the process map is complete, I use data analytics to analyze performance metrics and identify patterns. This helps in uncovering opportunities for automation, such as streamlining repetitive tasks or optimizing resource allocation. By combining process mapping and analysis, I can make informed decisions about where technology can best be implemented to improve productivity and enhance overall value stream performance.

In order to understand value stream impacts from a process change, the following steps are necessary: 1) Gather Data, Analyze, and Baseline 2) Create the Current State Map and Visualize the Process 3) Analyze the Current State and Identify Bottlenecks and Waste 4) Develop the Future State Map and Define Improvement Goals 5) Design the Future State 6) Create an Action Plan and Prioritize Improvements 7) Implement Changes and Execute the Action Plan 8) Communicate and Train 9) Monitor and Measure Performanc and Track Key Metrics 10) Adjust and Optimize Without any one of these steps, it is impossible to know whether a process change produced the value chain impact or if it’s a temporary lift from another factor.

In my experience, process maps that incorporate real-time data have a revolutionary effect. Dynamic visuals offered by programs like Power BI and Tableau make it easy to identify inefficiencies right away. Companies such as Toyota have made extensive use of these insights to continuously improve their operations, greatly increasing their operational efficiency and decreasing waste.

When assessing any value stream from a technology / automation perspective, a very useful approach that has helped us to view them from 3 dimensions: 1) Productive To eliminate manual operations as much as possible in a reliable, consistent, high quality, scalable manner 2) Predictive To use data analysis, pattern matching and statistical models for optimising performance, proactive issue identification and elimination, etc. 3) Decisive To make data available not just passively in the form of reports and dashboards or even graphs, but in a very intelligent, highly correlated and visualised manner to enable much faster decision making for business outcomes and strategy execution

In my experience, utilizing predictive analytics significantly improves decision-making. For example, Amazon has employed machine learning algorithms to estimate demand and optimize inventory levels, resulting in significant cost savings and improved service levels. Businesses may maintain and even improve their value stream performance by proactively addressing probable disruptions.

Value stream efficiency can be completely transformed by applying AI-driven predictive maintenance. Equipment failures can be prevented and downtime reduced, increasing overall production. Early adopters might experience a drop in unscheduled downtime and a reduction in maintenance expenses, giving them a competitive advantage.

I ensure that we collect and maintain high-quality, relevant data from all aspects of the value stream. This includes transactional data, operational data, and performance metrics. Next, I use advanced analytics tools, such as machine learning and artificial intelligence, to analyze the data and gain actionable insights. This helps in identifying patterns, trends, and opportunities for improvement within the value stream.

Incorporate real-time monitoring systems to continuously track key performance indicators (KPIs) and value stream metrics. This integration provides immediate visibility into process performance, enabling swift responses to emerging issues.

The big advantage over the past decade compared to earlier is the momentum in the industry towards digitally enabled business performance - especially Cloud, Data, ML and AI. What it has done is significantly reduce the entry barrier (especially technology investment and cost) for organisations to truly leverage digital tools to accelerate business performance. No need for data centers, server racks, large infra teams to manage them, development bandwidth to build custom tools, maintain and manage them, etc.

Integrating AI-driven analytics can greatly improve decision-making in value streams. Companies such as Amazon use predictive analytics to optimize inventory and delivery, lowering costs and raising service levels. Such tools not only forecast patterns, but also provide remedies, resulting in a robust value chain.

Claramente el uso de herramientas tecnológicas es indispensable para el flujo de valor. Se puede rescatar y sacar provecho a estas, en la manera que tengamos bien mapeado los procesos y sus falencias. Para que así su aplicación y desarrollo sea mucho más efectivo , así como eficiente. Todo este impacto será relevante para una correcta transformación y sostenibilidad.

The use of AI chatbots has completely changed customer support. These chatbots offer individualized service, speeding up response times and improving customer satisfaction by examining previous exchanges and market trends. This deliberate application of AI increases client engagement while also improving efficiency.

I focus on identifying software solutions that streamline processes and improve efficiency across the value stream, such as enterprise resource planning (ERP) systems and customer relationship management (CRM) platforms. These tools centralize data, allowing for real-time monitoring and decision-making. I also prioritize automation software to optimize repetitive tasks, reduce manual errors, and free up time for higher-level strategic work. Including collaboration platforms enhance communication and coordination across departments, fostering a more integrated and efficient workflow.

Robotic process automation (RPA) turbocharges value stream performance by handling repetitive tasks like data entry and validation with bots. This shift not only cuts operational costs and boosts speed and accuracy but also reallocates human talent to more strategic roles, enhancing overall productivity. Drawing from my experience, integrating RPA has been transformative, allowing teams to focus on innovation and critical thinking, thereby driving business growth. RPA's role in ensuring consistency and compliance further solidifies its value in technological transformation.

I identify suitable tasks, such as invoice processing and data entry, for automation. After selecting user-friendly and scalable RPA tools, I design and implement workflows that align with existing processes. Continuous monitoring and optimization ensure maximum efficiency and accuracy. By providing training and tracking key performance indicators, I drive productivity and cost savings.

Consider scalability when incorporating RPA. Early adopters reported increased agility through the use of bots in customer care and IT operations. The secret is to implement in stages: start small and keep improving. This tactical method optimizes ROI and avoids bottlenecks.

1. Process automation works best with structured data, high volume transactions with simple decision making. 2. Start small and don’t try to do too much when introducing. Expect to make mistakes and pivot fast when something is not adding value. 3. Complex processes with lots of decisions are expensive. Humans are better at making complex decisions particularly ones that impact customers. 4. RPA can be seen as a threat to jobs. Be honest and clarify that RPA may help take away the boring repetitive parts of their roles allowing them to focus on more customer focussed & complex tasks. 5. Demonstrate business value early to build momentum & support when introducing RPA. This is as much about hearts and minds as it it about technology.

RPA comes in 2 flavors: attended and unattended. Unattended RPA is when you have a software robot doing tasks in the background end to end without human input, in other words, fully automating what would usually be done by a person. Attended RPA is when software robot is embedded into business processes and operates like a digital assistant, at the command of its operator, it takes over and quickly does the previously manual process much more efficiently than the human. During the inception of RPA, unattended automations were synonymous with the technology, however, as time progressed and we've learned from implementations on the field, attended RPA is a lot easier for end users to digest and much more beneficial in most cases.

As you try to support the user journey with you value stream aligned organisation, you want to get a better predictability. To do so you can have a look at the batch size of what you ship. If you want to lower to the maximum the variability you will consider small batches released at high frequency and to do so, investing in automation (auto testing for instance) is a necessity. It's a necessary holding cost to build for future and to better serve the value you bring to you customers.

Always, always, always start with trying to improve the process before changing the tech. So many times I've seen businesses saying nothing will change unless they put some new tech in, and then replicate exactly what they currently do but with a new shiny software package. And then they wonder why nothing has changed. If you can refine the process first, you might find that the vast majority of your issues are resolved. If they aren't solved and you do then need to put new tech in, you're already half way there by having improved the processes first.

Think of technology as a lever, amplifying your ability to push the value stream forward with less effort and greater impact. 🚀 🤖 Automation of Repetitive Tasks: Identify tasks that are repetitive and time-consuming, and use automation tools to streamline them. 📊 Data Analytics: Utilize data analytics to gain insights into the value stream and identify areas for improvement. 🔄 Continuous Integration/Continuous Deployment (CI/CD): Implement CI/CD pipelines to ensure faster and more reliable software delivery. 🌐 Cloud Computing: Take advantage of cloud services for scalability and flexibility in your operations. 🧠 Artificial Intelligence (AI): Employ AI to predict trends and make informed decisions.

1. Provide training and upskilling opportunities for your team to adapt to new technologies and automation tools. This ensures they have the necessary skills and knowledge to leverage these tools. 2. Continuously monitor and evaluate performance of your value stream against key performance indicators (KPIs) and benchmarks. Technology can provide real-time visibility into performance metrics, enabling you to identify and address issues promptly. 3. Stay open to emerging technologies and trends that could further enhance value stream performance. Technologies like artificial intelligence, blockchain, and machine learning are constantly evolving, and exploring their potential applications within your value stream can bring further benefits.

Start by mapping your value stream, identifying bottlenecks suitable for automation. But then here's the fun part: a) Use AI to predict future bottlenecks, enabling proactive optimization. b) Further implement digital twins to simulate process changes before deployment. c) Consider citizen automation programs, empowering team members to automate their own workflows. This way you are creating space for innovation.