Digital Value for Business will provide the complete analysis on what would be required to reach the Value Proposition.
The digital value proposition is the base to develop a digital product or channel. A successful digital value proposition offers a valuable solution to solve an important problem or create additional benefits for the users and create effective value to the company.
A Digital Value for Business can be developed using the CANVAS, that have different templates to different scope, such as Digital Value Chain Business Model and Machine Learning.
Developing a Digital Value for Business have to be a business strategy, not a stand-alone project and have to be supported by the top management commitment, a proper methodology and adequate resourcing.
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.
Why would you care to use Canvases?
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.
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.