In today's fast-moving business environment, strategic innovation cannot be left to the board of directors or business leaders alone. In this era of the gig economy and changing demographics, everyone from self-made consultants to down-to-earth clients has the potential to contribute meaningful ideas and strategies, and the same goes for computers.
We have been using computers and the Internet for many years, but for the most part only for statistical analysis and search. We didn't use it to generate ideas – only recently, and not systematically. But that's about to change. That's right, it's all thanks to the generative AI that powers ChatGPT.
To many, the idea that AI can be a source of new ideas sounds counterintuitive. After all, ChatGPT is essentially just collating and processing all the questions people ask and putting together the answers. The strategic advice provided by ChatGPT will inevitably parrot the most common solutions.
Meet a new member of the strategy team
This trait became obvious (but not inevitable) when Wolfram linked ChatGPT to Mathematica software. When people first tried to solve math problems with ChatGPT, it quickly became clear that it was not very good at math because it relied heavily on language recognition. While AI may be able to write a good college application essay, it certainly won't be able to provide an original proof of the Pythagorean theorem.
However, things changed when people cross-connected GPT with Wolfram's software. AI is proven to be able to solve complex mathematical problems and demonstrates the solution process at every step. Inspired by this, we wondered what would happen if we cross-connected ChatGPT with a strategic framework? We found that the strategists of this virtual world are very creative and deserve a place on the company's team.
The strategic framework we chose for this was W. Kim, INSEAD. Chan Kim and Renée Mauborgne developed the "Blue Ocean Strategic Framework" in the 90s of the 20th century and the beginning of the 21st century. The framework has been studied for about 20 years and has proven to be consistently successful. It also has an extensive set of heuristic tools to help strategists make decisions. Connecting these tools with ChatGPT's AI allows us to both provide a "sieve" for ideas and generate a form of presentation of ideas. Let's take a look at what happens when an augmented blue ocean AI strategist is assigned a specific strategic challenge.
Is there a market?
As Americans living in France, we decided to have AI create a bagel shop in Paris. How can we bring bagel to this "City of Light"?
In the blue ocean concept, the core of value innovation is to encourage strategists to study which characteristics of a product or service may continue to discourage customers of non-existing products, and which people may become new customers. When we asked Blue Ocean AI what might make consumers not buy bagels, it quickly replied, "Tourists may be disappointed by the lack of availability, variety, and authenticity." "As expatriates in France, we feel the same way. But AI also believes that health-conscious and gluten-sensitive French people (who don't usually buy many traditional French bakery products) may be interested in bagels, noting: "Bagel bakeries in Paris have the opportunity to open up new markets and undoubtedly create demand in the blue ocean sector of their industry." ”
We then asked the AI for input to see what new measures it could take to attract what it thought were new customers. It came up with some specific ideas, including selling bagels with truffle cream cheese or raspberry fillings. Maybe "people passing by late at night want a snack?" We could also ask the AI to dig deeper. We asked, "Is there really a lot of late-night partyers in Paris craving a feast?" and the AI replied, "...... Setting up a fast-food window in the nightclub cluster of the Champs-Élysées maximizes the use of the untapped market. ”
AI has also come up with different ways to reach customers. It suggests: "We can not just offer bagels, but an experience", "Think about a large conference or business meeting", etc. The AI also recommends adding other traditional American baked goods and sourcing local ingredients.
So, how exactly should we sell bagels in Paris?
Build a value proposition
To develop a new value proposition, regardless of the strategy process, it is important to identify the fundamental factors in the target market that will influence the existing product/service. This is often a time-consuming, tedious task. However, the AI leveraged ChatGPT's search and analysis capabilities to create a list of factors for us to review and edit in less than a minute.
In the next step, AI uses a customized programming interface to identify which elements on the list should be removed, reduced, promoted, or updated through a customized programming interface, using the blue ocean framework connected to it, to generate a value proposition that will appeal to the target customer, and presented at the bottom of the interface in the form of a two-dimensional value curve that we can manually adjust. Once the adjustment is complete, the AI exports the data for us to generate a set of classic blue ocean value curves that demonstrate a value proposition that may appeal to customers.
Mapping ecosystems
On the execution side, we've trained the AI to map the extended ecosystem we're in. AI will soon be able to present the leading players across the baking industry and the products and services they offer, as well as the non-bakery product suppliers that bakery product customers are likely to turn to. The businesses identified are highly diverse, including street vendors, ethnic grocery stores, sushi parlors, confectionery shops, ice cream parlors, and gourmet markets, offering products such as croissants, sandwiches, cream cheese rolls, and quiches.
Next, the AI creates a sortable, editable list of potential suppliers, distribution channels, and potential customer bases. Suppliers include dough mixer manufacturers, malt extract producers (a key ingredient in high-quality bagels) and bagel cutters. Potential sales channels include retail bakeries and cafes, as well as airport kiosks. Possible customers include hotels, catering companies, and tourists. Finally, its influencers include travel bloggers and food critics, but also fashion influencers, which is a counter-intuitive but well-thought-out insight.
As with other tools, humans will next use a specially designed and intuitive computer interface to classify, modify, and easily change the various elements of the ecosystem. Once done, humans click to select the outcome they want, and the system immediately creates a slide with squares and arrows representing the industry's value chain, clearly mapping the players in the ecosystem and how they relate to each other in the process of creating value.
MBA vs.AI,孰胜孰负?
In total, the AI ideation process takes about 60 minutes, with most of the time being a human typing in a question and then editing the response. Eventually, the AI generates a presentation for the investor. To see if this manuscript works, we ran the same test the same way as before.
We asked a group of MBA students to develop a blue ocean strategy proposal in one week, using traditional paper-based tools such as flip charts and standard software (Google, PowerPoint). They each conduct their own research and bring the results back to the brainstorming session. Together, they mapped and discussed value curves — which took up to three hours to agree on — and spent about two days mapping ecosystems. In the end, they made a PPT by hand. The whole process was repeated many times because it was for different teams.
After the test, we compared the results of the MBA with those derived by the AI. In fact, the results are very similar for both. Therefore, AI is clearly competitive. However, we also found some differences. For example, the AI suggests that a bagel shop can offer certain items in limited quantities for a short period of time, just like the fashion chain Zara. On the surface, this may seem unrealistic, but after careful consideration, we think it's a promising direction to explore. We suspect that the reason the MBA team didn't come up with this idea was because of an unconscious bias at work on their part – a good illustration of how surprised we were at the idea at first.
The conclusion is quite sobering. AI is able to develop a strategy in as little as 60 minutes, and it's very similar to, and in some ways more ingenious, than a group of INSEAD MBA students who spent a week developing. Understandably, students, many of whom are considering becoming strategy consultants, were shocked by how advanced tasks as strategy development could be automated. While this is the first time most of them have experienced strategy automated, the idea is not new. Increasingly, we are finding that tasks that require analysis and experience can actually be automated. Accountants, bankers, and doctors – all of whom have traditionally been considered highly prestigious – are increasingly encountering this phenomenon. Moreover, this trend will only continue.
Of course, if people imitate robots, and robots do better than humans, then humans may be replaced. However, there is also plenty of evidence that strategy development still requires human involvement, and that the best way to do this is to pair intelligent machines with humans. In fact, in almost all areas, technology enhances human value. AI frees strategists from routine tasks and allows them to imagine and experiment more. With spreadsheets, financial analysts become more efficient, and with word processors, writers become more proficient. While the shift to automation will be challenging, well-crafted digital tools will ultimately increase human productivity, and they will create new jobs.
Our hope is that virtual strategists can empower their human counterparts to do their jobs better, enabling companies to create inclusive value propositions that deliver sustainable pathways to profitability and more products. The resulting impactful new strategy will create more value and lead to more jobs. Our "blue ocean"-centric strategic framework, AI, is fairly basic early software, but we are still rapidly continuing to research and improve. Future AI strategists will have multiple frameworks at their fingertips in addition to the blue ocean, making them even more valuable. We can't predict every turn, but we wouldn't be surprised if, in a few years, every company's strategy team has a virtual member.
迈克尔•奥利尼克(Michael Olenick) 彼得•泽姆斯基(Peter Zemsky)| 文
Michael Olynyk is an executive fellow at INSEAD's Blue Ocean Institute for Strategic Studies. Peter Zemsky is Professor of Strategy and Innovation at INSEAD. The college is a global business school with campuses in Abu Dhabi, France, and Singapore.
DeepL、Chat GPT | 译 张雨箫 | 编校
How important is it to follow the trend?
Want to see yourself clearly and ask "what" rather than "why"