Put your AI projects at the center of business management with “canvas”
While AI technologies such as deep Learning, reinforcement learning, and so on are now enhancing the moment more and more to deliver new services and solutions in a row, the significance of how to place AI in the business management is getting more and more important for companies.
In conferences, I often explain that you could not utilize AI to the full potential if you have a conventional modular-architecture perspective or a building-block approach either. Then, what kind of perspective or approach should we take to leverage the performance of AI? To give an answer to it, in this post, I will introduce the approach using “canvas” which is not a thing to paint a picture, but a tool to organize the business strategy throughout your organization.
In the business context, speaking of canvas, some of you may think of “Business Model Canvas” which got very popular about 10 years ago. That is the framework template for the strategic management proposed by Alexander Osterwalder, a Swiss business consultant. It’s comprised of 9 components to constitute the business model. You can use it as a hands-on tool which helps your understanding, discussion, creativity, and analysis.
9 components are customer segments, customer relationships, channels, value propositions, key activities, key resources, partner network, cost structure and revenue stream.
Components on left side are designed for your company or business. Components on right side for the market or customers. You’ll grasp the whole picture of the business and the environment of it at a glance. Using this canvas, you can engage people at any layer of the company which goes from business management to middle-management to project members into having the same view, jointly reviewing, understanding, discussing and planning the strategy of it.
Here is the video to take an example of LEGO and introduce its business model. You see how the Business Model Canvas works.
This kind of “canvas” approach like “Business Model Canvas” to systematically visualize, speak and share it with people concerned had been getting popular all over the world. So many variations had been generated. Some of them are relevant to AI. For instance, there is Deep Learning AI Canvas as a tool for facilitating the process to develop a system involving deep learning with stakeholders. It focuses concretely on how to plan and progress projects of system or service development powered by deep learning.
What’s more. There is another proposed canvas on how to position AI in the business management and how to design, discuss and execute the strategy involving the business executives in order to realize the business model and the business strategy as mentioned early in this article. That’s named “AI Canvas”.
AI Canvas was invented by Prof. Ajay Agrawal at the Rotman School of Management, University of Toronto.
By the way, speaking of AI at University of Toronto, you might think of “Canadian Mafia”. There are famous Canadian based trio. The first one is Prof. Geoffrey Hinton at University of Toronto, and the second one is Dr. Yann Lecan who was a postdoctoral research associate in Geoffrey Hinton’s lab. One more researcher, Dr. Yoshua Bengio was a colleague of Dr. Yann Lecan at AT&T’s Bell Labs. All three also began to work collaboratively at the Canadian Institute for Advanced Research (CIFAR) in Toronto. They have contributed hugely to the evolution of deep learning in the present age. Modern AI could be inseparable from Canada, especially Toronto.
Getting back to AI Canvas, Prof. Agrawal pointed out the fact that the current AI dropped the cost of prediction and can be considered the prediction system based on lots of data, such as demand forecasting, inventory management, etc, in the co-authoring book of “Prediction Machines: The Simple Economics of Artificial Intelligence (Harvard Business School Press, April 2018)”. In the following video, he explained about it.
AI lowered the cost for prediction based on lots of data.
I think this explanation makes wonderful sense. Prediction is about using information you have to generate information you don’t have. So it brings out the essence of a variety of machine learning applications, in particular, supervised-learning, deep learning, and so on. You can boil down what AI is doing such as image recognition, machine translation, document classification, topic extraction and whatever, even aiming at what will happen in the future or what happened in the past, to one idea that AI is predicting something.
The evolution of AI technologies make it easier, quicker and cheaper to predict many things. That means, you can make a decision more confidently in the business under the uncertain surroundings. However, how can you implement this predictive solution into the process of business management? AI canvas was invented to give the answer to that question. It’s the AI version of “canvas” variations. The actual template of AI Canvas is introduced in the following article of Harvard Business Review.
AI Canvas consists 7 components.
Prediction: What do you need to know to make the decision?
Judgement: How do you value different outcomes and errors?
Action: What are you trying to do?
Outcome: What are your metrics for task success?
Input: What data do you need to run the predictive algorithm?
Training: What data do you need to train the predictive algorithm?
Feedback: How can you use the outcomes to improve the algorithm?
With AI Canvas, you can have stakeholders join the discussion to identify necessary data, actions to do and the way to evaluate, and to create the shared blueprint for To-be goal. Then, you will utilize AI to the full potential.
AI Canvas can be applied widely to a variety of cases at each level and at each scale. It goes from the concrete application or service development by using AI to the organizational change of business management with AI strategy. So, you can take a gradual approach. For example, you will first try to apply AI Canvas to a project which is not much critical by involving those across sections and across levels of the company so that they understand how AI canvas works and helps them progress it effectively. And next, you will try to employ it to a more impactful and critical project.
Last year, I met and talked to Prof. Agrawal in person since I was an organizer for his talk at some study session. He said that he conducted AI strategy workshops in collaboration with a consulting firm to lots of companies and proved the effect of installing AI Canvas. About 10 years ago when business model canvas got attentions many companies tried holding workshops to use it. Your company might have also tried it. Utilizing the past experience, it would be good to test the effect of AI Canvas and discuss with stakeholders how to put AI into the business management, to make a strategy and to execute it.
