From Business Model Canvas (BMC) to Machine Learning Canvas
The Business Model Canvas (BMC) is a strategic management tool to quickly and easily define and communicate a business idea or concept.
It is a one-page document which works through the fundamental elements of a business or product, structuring an idea in a coherent way and providing the detail needed for the value proposition and all the information to decide if the project is justifiable or not.
This tool has been deployed into a lot different CANVAS, such as the Deep Learning Canvas, All Project Canvas, Machine Learning Canvas and many more.
Canvases are visual charts that allows the description of complex objects in clear way: each key component has its own block and blocks are arranged on the chart in a way that makes sense visually.
Machine Learning Canvas is the tool that translates the organization’s data science activities with the organization’s strategic business initiatives. It can be enriched using the Machine Learning ROI that could demonstrate how to model the investment value of Machine Learning.
Benefits of using Canvases
Why would you care to use Canvases?
- Easy to understand, very visual and only in one page
- Keeps the team focused
- Flexible: It’s quick and easy to make changes to your model and sketch out different ideas.
- Customer Driven: the canvas forces you to think about the value proposition that you’re providing to your customers and to your business and what it takes to deliver that value.
- Demonstrate correlations: The single page graphical nature of the canvas shows how the different parts of the model interrelate to each other.
- The canvas model is so easy to understand that will allow you to share and explain the progress with the team, making it easier to get them on board with your vision.
Why Machine Learning Canvas?
The Machine Learning Canvas it’s a first step to make sure you connect what ML can do to your organization’s objectives, and towards assessing feasibility.
You’ll be able to identify key constraints of your ML system, which have an impact on the technology to choose. The ML Canvas should be done before Exploratory Data Analysis.
The Machine Learning Canvas allows to describe the actual learning that takes place in intelligent systems.
Should be started with the Value Proposition of the system where ML is going to be used. The value proposition includes the What, Why and Who: What are we trying to do, why is it important, and who is going to use the system or will be impacted by it. Then there’s the How, which can be split in two parts: learning and making predictions.
Live Evaluation and Monitoring, allows to specify methods and metrics to evaluate the system after deployment, and to quantify value creation. It is dedicated to measuring how well the system works.
When finished, the Team should decide if this idea should continue.
When it is a Yes, the Team should use the Machine Learning ROI to demonstrate the return on investment of the Machine Learning to validate the value for business.
SMART Digitalization
Technology innovation are driving business to transform the traditional way of work in your business using digitalization, expecting that this change will contribute to improve cost, performance, quality and safety.
After the transformation, sustainability is a must, so it is required to change the processes and adapt the skills to this new way of working.
This is why it is so important to validate the initiatives your company are promoting, before start spending hug amount of money in solution that later will not serve the company objectives.
