Mindful apps – putting people at the center supported by data

When preparing for my session The future of business process apps – a Microsoft perspective  last year I got inspired by this great article The future of enterprise apps: moving beyond workflows to mindflows – which introduced the concept of mindful apps. The core message is that if we want to automate the last mile we have to analyze how people work day in and day out and start our system/application design with people at the center. One of the quotes which is mentioned in the article is from Bill Murphy (CTO of Blackstone one of the largest investment funds worldwide) – “We aim to take away as much of the stress as possible from easy stuff, by automating the routine and mundane actions, and give users more time to focus on the higher-end pieces of what they need to do.”

Most of the characteristics which are outlined in the comparison between traditional and mindful apps are not revolutionary (See table above) but there is one one important key message.
Mindful apps will allow us to assess and compare options in decision context, they will allow us to quickly respond to events and make the best decision given a specific context and will provide us with “extended intelligence” by understanding and recognizing patterns within the data at hand. We as humans are good at problem solving, pattern recognition, identifying outliers, making creative leaps and incorporating new information when making decisions. We should be able to focus on these high end tasks by being freed from laborious and menial tasks which can be automated.

There are 3 different trends which will impact how these mindful apps will be shaped:

• User context matters – make it personal. When we make decisions or work within the context of specific processes, there are a lot of parameters which determine how we react or how we make decisions – these parameters should be integrated into the decision framework driving mindful apps. Our calendar, availability of colleagues to reach out to, input from communications (using e-mail, messaging or other formats), information that we capture from blogs, social networks such as LinkedIn or open data sources together with available information within your organization should be filtered and at your fingertips. Machine learning and cognitive algorithms will drive the second machine age (a term coined by Brynolfson from MIT) but we are only at the start of how these algorithms can drive the future workplace for information workers.
• Mobile shapes our expectations.  Mobile apps and the user experience they provide is shaping at how we see an ideal enterprise application as well. Mindful apps should strive to combine beauty, simplicity and purpose to create an experience that delights us and that is effortless to use. Mobile apps are easy to understand, when people use a good app for the first time, they intuitively grasp the most important features, why can’t we do the same for enterprise apps. Simplicity rules. The apps should also incorporate necessary logic to evolve as the user grows more comfortable with its use and is exploring more advanced functionality. Apps should learn people’s preferences over time and show the interface which is best suited for the task at hand.
• (Big) data and advanced analytics are the driving force. There is a lot of hype and confusion around the term Big Data but one thing is for sure – storage costs and processing cost have dropped significantly in the last decade. When you combine this with the rise of new storage platforms such as Hadoop, NoSQL datastores  such as HBase, Cassandra, etc … and new data processing frameworks such as Apache Drill, Dremel, Spark, etc..  new opportunities arise to support users in their decision making processes. While there is a lot of emphasis on the 4 Vs (Volume, Velocity, Variety and Veracity) – there is one more V that you have to think about that is Value (Also see  Big Data beyond the hype, getting to the V that really matters)
• Cloud will lead the way.  A lot of the innovation which will enable this next generation of apps is coming out of the datacenters of Google, Amazon, LinkedIn, Microsoft, Yahoo, etc… but most organizations don’t have the available capacity (nor the same financial resources) as these internet giants. Luckily the economies of scales which are offered by the cloud allows solution providers to provide you with a data infrastructure which can scale from prototype size to production environments able to handle huge amounts of data. The different major cloud players – IBM, Microsoft, Amazon and Google all seem to make big bets in building out the data analytics platform of the future and this competition will drive prices further down. This competition  will also force them to focus on more innovative solutions which allow them to differentiate from the competition.

The best examples where we – as a consumer - see the power of Big Data, Analytics, Machine Learning and the cloud appear is mobile. The three major players (Microsoft, Apple and Google) are relying quite heavily on the cloud computing power and huge data stores to provide the experience of digital assistants. Microsoft is currently working on Cortana (which has been released in a number of countries worldwide), Apple was definitely the trendsetter with Siri and Google has Google Now.

The future is already here — it's just not very evenly distributed. (William Gibson)

Tags van Technorati: machine+learning,analytics,big+data,collaboration,vision,apps,nwow,hnw,engaged+workplace,future+workplace