This article describes the ‘idea model’ and provides various examples of real ideas — explains how to write effective executive summaries for your concepts.
Ideas are powerful constructs. Provided that they are articulated and communicated effectively, they can become the starting point of impactful initiatives and new innovations.
The problem with business ideas though is that they can come in a wide range of formats and varying levels of detail and sophistication: Sometimes an idea is ‘expressed’ on a sticky note and put on the wall for ‘evaluation’. Often, ideas are documented and presented through lengthy and difficult-to-consume decks, that usually receive limited attention and engagement.
Ideators need a standard, compact way for articulating ideas quickly while innovation leaders need a stream of consistent, standardized ideas, expressed in a comparable way. And this is exactly what the Universal Idea Model is bringing in the innovation process.
A simple, powerful model for expressing new product or business ideas
Similar to the way user stories describe a feature of a product or a user need, the Universal Idea Model can capture any idea in a concrete, ‘executive summary’ statement as shown below.
The idea can be named using a simple pattern like
A/An <OBJECT> THAT <DOES SOMETHING>A/An <OBJECT: the form that the idea could take if implemented> FOR <A CLASS OF USERS: name the personas — users or customers> THAT <DOES SOMETHING: the major function of the idea> IN ORDER TO <ACHIEVE A GOAL: the outcome of its core function>. USERS BENEFIT BY <GETTING SOMETHING BACK: describe the value the get> WHEN <IN A SPECIFIC SITUATION: describe the conditions under which they benefit from the idea>.The
<OBJECT>The
<CLASS OF USERS>The
<DOES SOMETHING><OBJECT>The
<ACHIEVE A GOAL><DOES SOMETHING>The
<GETTING SOMETHING BACK>The element
<IN A SPECIFIC SITUATION>The following are real product ideas captured in my personal backlog using the Universal Idea Model.
Example #1 - Finding the right participants for a business meeting
This is an idea about a system able to identify and recommend relevant and/or valuable participants for a business meeting (or project, or other business activity or collaborative engagement).
One way to describe this idea is through a lengthy, unstructured, detailed description — starting with the problem, then describing the concept, and finally explaining the value. This might read like the following:
Business meetings are expensive to organize and run. In many cases, they are noisy with no actionable output — due to the non-optimal synthesis of the list of participants: People that should be present are not invited; for some of the participants the reason for being invited may not be clear. In many cases, there are too many people in the room making the actual discussion and collaboration inefficient and less actionable.In such scenarios, when a user is setting up a business meeting or a session, an ‘intelligent’ system may capture and ‘understand’ the context of the meeting using NLP and then query the active directory of the organization along with a skills database and a shared calendar to find the most relevant and available people in the context of the particular meeting. In one example, these candidate participants may be recommended based on a candidate score calculated for each candidate participant — based upon a variety of factors, including (1) the particular candidate participant’s relevance to the meeting topic, (2) the extent to which the particular candidate participant has positively contributed to previous meetings, and/or (3) whether the candidate participant has attended meetings that are particularly relevant to the topic.Recommending meeting participants in this manner can reduce the potential for inviting low-value participants to meetings, as well as identifying and recommending potentially valuable meeting participants who would not otherwise attend.
While the above 231-word long paragraph provides a good description of the problem, the solution, and the benefit, it is too long (for an ideator to type, and for a stakeholder to engage with and quickly get the … idea). Especially if ideation is happening at scale, e.g. having a steady flow of ideas in an innovation context, this free-form idea description proves to be ineffective.
Moreover, the above description tends to be technical, e.g. it is talking about NLP, scores, factors, active directories, etc. — this makes it less inclusive as non-technical users might find it more difficult to follow.
Using the Universal Idea Model, the ideator abstracts the concept, avoids the technicalities and unnecessary —when at an early stage — details, saves time, and gains clarity on the idea itself by summarizing it in the following way:
A digital assistant THAT recommends the most relevant participants for a business meeting.
An AI-powered service FOR business users THAT is able to capture the context of a meeting and recommend the most suitable participants IN ORDER TO organize a better meeting with the right people in the room. USERS BENEFIT by instantly finding the right experts and decision-makers to invite WHEN they are setting up a business event.Example #2 - Tackling the problem of Fake News and misinformation
This idea is about a solution to the social media Fake News problem. One way to describe the solution would be through an article or a document like this one: Misinformation Online: A Universal Solution
However, the above-referenced article is an 8-minute read (1745-word long essay). When innovating, there must be a better way to summarize a newly-conceived idea — as the master entry- and then attach additional documents, descriptions, designs, and other artifacts — if and when they become available. Using the UMI (Universal Model for Ideas), the executive summary of this idea could be written as in the following:
A blockchain-powered content center THAT can retroactively score content and distributors based on their trustworthiness.
A decentralized system FOR online users, THAT systematically samples and processes cohorts of News and social posts IN ORDER TO identify ‘Fake News’ or misleading information and score content, social media and content distributors in terms of reliability - while notifying online users for their unconscious participation via sharing fake content. USERS BENEFIT by realizing both their exposure and their unintentional contribution to the problem of Fake News WHEN they use social media to discover, consume, and share content.Example #3 — An Augmented Reality in-shop consumer advisor
In this example, the idea is about a smart, in-store shopping advisor for consumers — able to synthesize ‘smart’, personalized offers and deals to each consumer — by leveraging all the knowledge available for the consumer (history, preferences, lifetime value, etc.), the product catalog and the consumer base overall.
Through a connected device, the system is able to identify the customer entering a physical store, and instantly compute a set of special deals and pricing elasticity — all computed according to the ‘value’, the profile, and the specifics of the customer. As the customer navigates the store, he/she browses physical products through the mobile device (or special, connected glasses) and experiences personalized deals — dynamic pricing and intelligent loyalty offers, appearing as metadata, on screen.
On approval by the user — via a tap on the smartphone screen — the app notifies the loyalty system of the retailer, the order is placed and the user just confirms and pays — physically in the store or online with an extra step. All served as an instant, interactive, personalized AR experience — no cards, no coupons, no loyalty memberships. A seamless experience for both the customer and the retailer.
Using the Universal Model for Ideas, this rather complicated idea could be summarized in the following:
An Augmented Experience THAT allows retailers to offer personalized offers to their customers in physical stores
An Augmented Reality app FOR consumers THAT synthesizes product and pricing information as an augmented reality experience IN ORDER TO offer personalized offers to the consumer - in the form of special prices, loyalty schemes, or discounts. CONSUMERS BENEFIT by discovering better offers, in a personalized manner WHEN they are exploring products in a physical retail store. RETAILERS BENEFIT by optimizing their loyalty schemes and enabling a seamless, personalized in-store experience WHEN they are trying to drive sales through physical stores.Note that in this example, there are two statements regarding the benefit for the user — one for the consumers and one for the Retailers.
Example #4 — A situation-aware ‘Do Not Disturb’ application for smartphones and wearables
This example is about summarizing an idea about an ‘intelligent’ Do Not Disturb mode for smart devices, that is triggered by certain attributes of the current social arrangement. This can be described as in this article or using the following compact form based on the UMI - Universal Model for Ideas:
A smart DnD assistant THAT understands the special character of the occasion and recommends or sets a certain 'notification mode'
An O/S-level software component FOR smartphone users THAT is able to identify certain social occasions as ‘noise sensitive’ IN ORDER TO minimize the disturbance from mobile ringtones and app notifications. USERS BENEFIT from a generalized socially responsible use of smartphones WHEN in a place or occasion that requires focus or quietness.The Universal Ideas Model can be used via a simple form or verbally, in workshops and brainstorming sessions. Ideally, it should evolve as a part of a shared innovation language — allowing teams across the organization to exchange ideas in a compact, solid format. A centralized database of ideas captured using this model can make the discovery and utilization of ideas, easier and most efficient. Most importantly, it can increase the chances of discovering great, high-potential ideas and innovation opportunities.
Cover Photo by Per Lööv on Unsplash)