Dr.Michael Wu (@mich8elwu) has written a series of articles on how to leverage the concepts of game theory and ideas about implementing game mechanics to support a dynamic social business strategy. He has included some very interesting points about Enterprise Gamification in one of his recent articles. I recommend reviewing his ideas and insights in “The Future of Enterprise Software will be Fun and Productive“.
I believe Michael made many smart observations and shared several intelligent ideas. Here is what I wrote as a comment in his latest article on Enterprise Gamification. I would enjoy hearing your thoughts on how to “Gamify” Social Business and supporting game mechanics in the Enterprise.
Response to “Enterprise Gamification”:
Thanks for taking the time from your busy schedule to share your thoughts on this very important topic.
Your ideas about a Gamification Strategy for rapid adoption of Enterprise 2.0 Solutions to support fluid collaboration will help business leaders avoid creating a platform brick. A “platform brick” is a solution designed and implemented with very limited collaboration by a small group of people before understanding anything about the culture or business objectives. This silo approach is usually followed up by a raging river of cash and other valuable resources to drive adoption. The flow will continue until this river runs dry or when someone is strong enough to put egos aside and start conversations about real collaborative solutions.
I am also puzzled about why most enterprise software developers and vendors don’t collaborate more with leaders in the video game industry. I believe a background in psychology & sociology will be the new requirement for future enterprise software developers.
Driving Adoption of Enterprise 2.0 Solutions should be a shared responsibility between the players and the platform itself. Platforms should become more intelligent through the course of user interaction and take the lion’s share of driving adoption.
Q: How much do we need to pay an Intelligent Platform to drive adoption?
Q: How many bonuses do we need to pay an Intelligent Platform to drive adoption?
Q: How many vacation days, sick days, and perks does an Intelligent Platform need to do it’s job?
The thought of investing into Dumb Platforms is dead.
Enterprise Gamification is far beyond it’s due date.
The exponential value of Enterprise Gamification can be achieved by applying the principals of game theory to players and objects for unlocking the power of collective intelligence. This collaborative approach to creating game dynamics goes far beyond points & badges for people and things. This type of model is designed to facilitate the growth of a collaborative culture. The players (employees) strengthen relationships and leverage resources on their journey of helping the organization accomplish business objectives and achieve their goals.
I am looking forward to hearing more about your ideas.
Did you know that Call of Duty: Black Ops generated more than $360 Million Dollars in the first day of sales? Call of Duty: Black Ops is the most beautifully intelligent game I have ever played! This masterpiece offers amazing game play, stunning graphics, awards, badges, achievements, customization, and takes game mechanics to a whole new level. Let’s take a look at how we can leverage these success factors for the Enterprise, but first take a look at this funny Call of Duty: Block Opsvideo.
Call of Duty: Black Ops TV Commercial: “There’s A Soldier In All Of Us”
What is Gamification?
Gamification is the use of game play mechanics for non-game applications, in order to encourage people to adopt the applications. It also strives to encourage users to engage in desired behaviors in connection with the applications. You can learn more on the Gamification Blog.
How Does Gamification Apply to Enterprise 2.0?
Gamification in Enterprise 2.0 is about Maslow’s hierarchy of needs, a theory in psychology, proposed by Abraham Maslow in his 1943 paper A Theory of Human Motivation. Most of these needs are met by popular games and should be supported in Enterprise 2.0 platforms to ensure rapid adoption and success. You will discover some simple methods to “Gamify” your Enterprise 2.0 Platform in this article I wrote last year Game Theory for Enterprise 2.0 Adoption. That article also includes a few videos about human behavior. Ideas around the bigger picture of using game mechanics in the Enterprise is coverd in this article Enterprise 2.0 Adoption Patterns: Collective Intelligence.
Gamification Videos & Presentations
The gamification presentations from the Gamification Summit are available to members, but here are a few presentations that will get you thinking differently about using game mechanics in your Enterprise 2.0 Platform to improve user engagement.
Gamification Patterns & Pitfalls
Gabe Zichermann, Gamification Expert and Author discusses some of the main ways that gamification will change your business in this video.
I have been in Africa for several days and have learned more about Culture, Relationships, and Resources. Our Mission Team from America has been working with local teams at Humble School in Uganda. Humble School provides care and education to children here in Africa. The school, just like many organizations and individuals here, have very limited resources. Some people come here and see the needs and then try to implement THEIR solution. Some of these solutions die a horrible death and it’s usually due to poor communication and disregard of culture. It’s sad to see that here and in Enterprise 2.0 Solutions.
When I see hungry people in the morning, I think eggs, but no eggs were to to be found. I was thinking we could buy eggs to help feed the people. Eggs got me thinking about chickens, which lead to plans about lunch and dinner. What if we gave the school a truck-load of chickens?
The Chickens and Eggs System
A chicken ranch would give the people a simple system for producing chickens and eggs. A big chicken ranch could feed the community and provide an income stream by selling chickens and eggs to other communities. This sounds like a great idea, right?
Death Before Life
The “Chickens and Eggs System”, just like any solution will die without a full-lifecycle plan. The ideal plan puts Cultue first with a focus on Sustainability. A plan without these two key elements produces a stagnant (If something such as a business or society is stagnant, there is little activity or change) solution, which leads to Death before Life.
What’s Wrong with The Chickens and Eggs System
How would you keep them healthy?
How would you feed them?
How would you protect them?
How would you help them be productive?
What if the community could not or would not eat chickens or eggs?
What if the community preferred fish?
A Little Culture Goes A Long Way
Our “Chicken and Eggs Solution” is not that different from Enterprise 2.0 Solutions. The main lesson I see is understanding Culture first improves our ability at creating Sustainable Solutions. Attend any Enterprise 2.0 Conference and you will hear, “It’s about the people, not the tools”. This is more than a “buzz phrase” and goes beyond responses from a subset of people in the Enterprise. This is about a complete understanding of the culture within the Enterprise. What works in one Enterprise, does not work in all. A good place to start understanding more about culture in the Enterprise is with Susan and her teams at The Adoption 2.0 Council.
In a previous article “Game Theory for Enterprise 2.0 Adoption” we took a look at some simple ideas for improving the intelligence of profiles in Enterprise 2.0 platforms. There we looked at some simple modifications that can be applied to any platform to have the system improve the Adoption Rate. This article will review how to improve the intelligence of things, such as documents and links. These patterns can also include activities outside the platform. You can learn more about Enterprise 2.0 Adoption Patterns here.
The whole is greater than the sum of it’s parts
Collective intelligence is a shared or group intelligence that emerges from the collaboration and competition of many individuals. Collective intelligence appears in a wide variety of forms of consensus decision making in bacteria, animals, humans, and computer networks. [Wikipedia] This goes beyond “User Contributed Content”.
Enterprise 2.0 Pilots and Collective Intelligence
We can also see that time will improve the Collective Intelligence of Enterprise 2.0 Platforms in this article “Enterprise 2.0 Pilot: Yes, No” by Emanuele Quintarelli. Most of this article covers the pros and cons of Enterprise 2.0 Pilots, which is important to understand.
How Much Scale Is Needed in Enterprise 2.0 Employee Adoption?
Improving the Intelligence of Enterprise 2.0 Platforms
Add a “date field” for the updated date. Display “recently updated documents” list on the documents dashboard.
Add a “date field for the last viewed date. Display “recently viewed documents/links” list on the enterprise dashboard. Members and Community Managers can easily see which documents/links are active in real time.
Add a “int field” to store the count of document/link views. Display “most viewed/clicked documents/links” list on the enterprise dashboard. Members and Community Managers can easily see the most active documents/links, which can be a trigger to find and/or add similar content. This will also help members identify and possibly remove content with lower values.
Display a limited “recently viewed by” in the document details view. The limit works with time, while the list surfaces activity. This encourages connections. Members can find “like minded” colleagues along with discovering related documents/links.
Display “recent activity widget” Most users enjoy seeing the intelligence value of documents/links in visual ways. You can dynamically pull in these stats and display chart and graph widgets of this valuable information.
Add two “int fields” to store the document/link ‘like’ counts. One filed to store the number of voters, the other to store total vote count. This will support a “star rating feature” or a simple “like rating feature”. A simple “like” feature will support finding the average by dividing total against count. You could also create a separate database table the stores all your rating/like data.
The key to taking advantage of automatically adding intelligence to your platform assets, especially bookmarking tools, is to always pass the request to your recommendation engine before redirecting to the requested asset. This type of behavior is similar to what you see in http://bit.ly, the popular link shortening tool used mostly on Twitter. My thoughts on apps in the Enterprise, “E 2.0 Apps: if they can’t be measured, then they have no business on the Enterprise Platform.”
These are just a few ideas on adding that “addictive property” to an Enterprise 2.0 Platform. These simple ideas will also help platform managers identify weak assets and key assets on the platform. Enterprise 2.0 Adoption Patterns are key to increasing the total value of the platform.
Mind Reading Enterprise 2.0 Platforms
Collective Intelligence and Recommendation Engines
What if the platform delivered value directly to you through benefits you can use right now?
What if the platform made your job super easy?
What if your colleagues were so addicted to the platform, they stopped clogging your inbox?
What if all your colleagues used the platform, but you did not?
What if your new job requires the efficient use of Enterprise 2.0 tools?
What if the platform actually made your life easier?
What if you discovered that the more you use the platform, the more it understood what you wanted?
Imagine this. Yesterday you logged into your Enterprise 2.0 Platform and wrote an article about Augmented Reality. Today you are thinking about forming a group to discuss your topic and you are wondering if there are other people in your organization interested in working together to learn more. You login to your Enterprise Dashboard and see several colleague connection recommendations that are interested in Augmented Reality. You also see a widget that recommends several groups: “AR World”, “AR Bytes”, “Human Interaction Tech”, “Mobile Apps”, “Band of Geeks”. You see another widget that recommends a list of external resources about Augmented Reality. You might feel a little freaked out at this point and start wondering how did this platform read my mind?
This is the same type of technology that had made Google Billions of dollars. We also see this type of technology used at Amazon to improve the user experience and boost sales. Google hit the JACKPOT with their “sharable content objects” known as AdSense, these micro mashups are embedded in web pages all over the internet. It is important to understand the incredible value of “sharable content objects” and mashups, but we will save that for another time. Other good examples include LinkedIn and NetFlix.
Programming Collective Intelligence
Adding simple rating, view, and point counters will improve the user experience and help breath intelligent life into Enterprise 2.0 Platforms. These type of patterns are also supported in game theory. You can take this a step further by creating behavior algorithms for recommendation engines with well known mathematical formulas. Many of these metric formulas are available here on Wikipedia. These formulas were a bit daunting for me, so I bought an amazing book that explains how to quickly build intelligence into Enterprise 2.0 Platforms.
Programming Collective Intelligence: Building Smart Web 2.0 Applications
This book takes theory of Collective Intelligence and breaks it down into tasty byte sized morsels of tantalizing apps for improving the experience on any platform. The author carefully crafted several enjoyable sections and includes step by step guidance for creating multiple types of recommendation engines. I recommend buying this book, before your next update. Here is the quick overview list of just a few topics covered in this very helpful book.
Collaborative filtering techniques that enable online retailers to recommend products or media
Methods of clustering to detect groups of similar items in a large dataset
Search engine features–crawlers, indexers, query engines, and the PageRank algorithm
Optimization algorithms that search millions of possible solutions to a problem and choose the best one
Bayesian filtering, used in spam filters for classifying documents based on word types and other features
Using decision trees not only to make predictions, but to model the way decisions are made
Predicting numerical values rather than classifications to build price models
Support vector machines to match people in online dating sites
Non-negative matrix factorization to find the independent features in adataset
Evolving intelligence for problem solving–how a computer develops its skill by improving its own code the more it plays a game
What are some of your favorite Enteprise 2.0 Adoption Patterns?