Today’s enterprise applications primarily target operational efficiency by standardizing workflows and minimizing human involvement in repetitive business activities. Now, as explained in the article, “The future of enterprise apps: Moving beyond workflows to mindflows,”, a new generation of enterprise applications is blending human and software intelligence. This blending is particularly true for knowledge work in which reason, analysis, pattern recognition, and related cognitive skills can be supported by software’s recall, filtering, and presentation of intelligence in the moment.
Because apps of this type explicitly model thinking in their design stage, PwC calls them mindful apps. Mindful apps engage humans as an integral part of enterprise processes. (See Figure 1.) They do so by modeling thinking and incorporating it into the business process of interest, using context and delivering intelligence in the moment to augment the capacity of employees to add value through knowledge work.
Mindful apps have new paradigms and expectations for user interactions, availability, readiness for integration, and design. New tools, platforms, and services are emerging to meet this new generation of computing challenges. The biggest expectation and impact is in elevating the user experience to a new level of simplicity and timeliness to support how individuals do their work. This article details some of the methods and tools that enable mindful apps across the following three categories:
These new tools and methods help designers understand the processes that occur in the mind of the knowledge worker. This activity is often idiosyncratic and personal, but it tends to follow patterns within a persona or a group. To contrast these cognitive, thoughtful activities with traditional workflows, PwC calls them mindflows. Mindflows are goal-driven thinking patterns—such as comparing, evaluating, and summarizing—used by anyone engaged in complex analysis and decision making. The journey to the goal potentially has many paths and unfolds in iterative divergence-convergence patterns. (See Figure 2.)
Mindful apps engage humans as an integral part of a process
Mindflows are goal-driven thinking patterns that usually unfold in iterative divergence-convergence patterns
Mobile technologies have created a deeply personal connection between users and the apps they use on mobile devices. Humans and computers now engage in an ongoing, collaborative exchange. Consumers have come to expect that technology, no matter the platform, will be able to deliver a hyper-personalized experience using the context of their current location, situation, and perceived needs. Whether this expectation is due to people now carrying an always-connected computer in their pockets or the new design patterns embraced by this new digital community, the lasting impact will depend on how well human thinking, or mindflows, is integrated into defining the user experience.
Capturing mindflows is not about mimicking how users reason, as expert systems or artificial intelligence systems tried to do in the past. Mindful apps leave the reasoning to the user and focus only on the states of thinking: a user’s current understanding, what information a user needs to see, what a user is likely to do next, and so on. The following sections discuss emerging methods that vendors and enterprises are using to model and make explicit the mindflows in the context of a user experience.
Design thinking. As the name suggests, design thinking is a methodology to understand the cognitive or thinking activities anyone uses when doing his or her design work. This technique originated in engineering design and has spread to many other domains. Today it is an important trend in management thinking, particularly in support of innovation and creativity.
Design thinking is especially useful for addressing problems that are not well defined, thereby it is a good fit for the exploratory nature of knowledge work. “Everything we do is using design thinking,” says Jonathan Becher, chief marketing and communications officer of SAP. SAP’s design thinking experts engage with customers in multiday workshops. “We’re getting in the mind of the customer and being empathetic. In two days we simulate actual work. We try to understand, ‘At this point, why did you do this?’ We are getting to their mindset,” Becher explains.
As Figure 3 depicts, this methodology focuses on understanding users in context by observing, identifying, and characterizing distinct roles or personas and gathering user stories. The method requires iterative explorations of possible app behavior using rapid prototyping of experiences and frequent conversations with users.
What distinguishes mindful apps from traditional apps is they acknowledge many paths to an outcome—paths that depend on information and human judgment, not on a set of linear steps. Design thinking allows the identification and externalization of multiple paths to a desired goal.
Digital body language. The Internet continues to penetrate daily life. People have gone from visiting a few websites to making ever-greater portions of their total purchases on the web to using mobile computers to share pictures of places they’re visiting—all within the last 20 years. All this online behavior creates a trail of data, or digital footprints. The websites people visit, the e-mails they open, the links they click, the likes they signal in activity streams, the reviews they post, and so on can be thought of as digital body language that, like physical body language, transmits information about themselves. (See Figure 4.) Steven Woods, group vice president of software development at Oracle, created the concept of digital body language when he was the CTO of Eloqua (now a subsidiary of Oracle) and has written a book on this topic.1
Design thinking process as practiced in the Hasso Plattner Institute of Design at Stanford
As users live their digital lives, they leave behind digital footprints—the sum total of which is their digital body language that has clues to their interests and intents
What inspired Woods’ concept was his realization that digital channels were redefining marketing and sales activities. In digital channels, a salesperson is no longer able to read a buyer’s physical body language, cues that were once available to navigate the in-person sales process from prospect to close. But what the web took away, the web is giving back. Savvy marketing organizations use marketing automation products to read, so to speak, the digital body language of their customers and position a target’s readiness for different types of marketing content. By delivering the right content to the right target at the right time, these organizations advance their marketing or sales processes.
This concept, which has transformed marketing, will have a similar impact on other processes. “The design of any application for any business function will exist within the same intensive world of information and media bombardment. They all need to catch the user’s interest and thinking at the moment in time so as to cause the user to take an action that will move them forward,” Woods explains.
The use of such data in targeted ads from Google or Facebook is now familiar. Their platforms monitor a user’s Internet searching, status updates, or likes as indications of what a person is thinking and feeling about specific products, services, and even political candidates. Techniques and information associated with digital body language also can deliver powerful predictions of what a person is thinking in the enterprise context. When combined with well-defined models of mindflows associated with how a user’s thinking evolves toward a specific decision or conclusion, digital body language can be a key enabler for orchestrating the overall experience.
Other methods to externalize mindflows. Additional methods to consider when attempting to capture and include mindflows in future apps include the following:
Armed with methods for formalizing the mindflows, the next challenge to defining the experience for mindful apps is to take advantage of context and deliver intelligence in the moment.
If mindful apps are to be impactful at the time of need, they must be available at the time of need. The rise of smartphones—mobile computers, really—uniquely established the possibility of delivering on this promise. They are the one computer that is always with a person.
Smartphones bring a lot of personal context with them. They generate a wealth of sensor information that helps apps to know where, how, and for what purpose a person is using the device. Developments to bring context to apps are taking place in both hardware and software. On the hardware front, the computing systems allocate a separate processor to manage context. For example, Apple’s new iPhone 5S includes an M7 motion coprocessor to compute context, and Google/Motorola’s new X8 compute system has a contextual computing processor.3 With a separate low-power processor, context can be continuously monitored and made available without draining precious battery life.
On the software front, context-aware platforms, such as Qualcomm’s Gimbal, allow developers to access sensor information and awareness of the surrounding environment. For example, if the phone hears that it is inside a movie theater, it can provide content related to the movie. Gimbal is offered as a software development kit (SDK) and therefore abstracts context information into application programming interfaces (APIs) for use by mindful apps.
The sensors and context-computing capabilities collectively define the contextual power that mindful apps can use to anticipate the next action the consumer wishes to take with as little user interaction as possible.
The effectiveness of any mindful app depends on how well it anticipates what the user needs and delivers it as content or functionality in the moment. Two technologies are relevant to this anticipation and delivery: development platforms that are an ecosystem of capabilities and that ease integration to access those capabilities; and real-time analytics so the apps can deliver predictions and analysis as events are occurring.
Development platforms become the foundations for mindful apps into which all other functions, such as analytics, can be integrated. Platforms can be on-premise or in the cloud, such as Fusion from Oracle, Force.com from salesforce.com, and HANA from SAP. There are also platforms specifically focused on integrations between software-as-a-service (SaaS) or on-premise applications, such as MuleSoft and SnapLogic.
Real-time analytics solutions are available from an array of solution providers. Vendors such as Chartbeat and Visual Revenue (acquired by Outbrain) present real-time insights in marketing or online media consumption contexts. Google and Webtrends provide real-time analytics platforms of online advertising data and website traffic data. Splunk and Vertica (part of HP) are emerging as general-purpose platforms for aggregating data across websites, sensors, machines, and other sources, and providing capabilities to process and analyze them in real time.
As explored in the Technology Forecast 2012, Issue 1, in-memory computing is bringing a new level of real-time capability to customers. Solutions such as Exalytics from Oracle, HANA from SAP, and in-memory analytics from SAS are some examples. In-memory technology achieves performance by keeping data in solid state memory rather than reading from disk, a process that adds latency to the process.
Predictive analytics solutions include algorithms and models that provide the ability to predict future actions that a user is likely to take based on current behavior. Vendors such as Angoss Software, Oracle, Revolution Analytics, SAP, and SAS offer such solutions. Increasingly, such analyses make use of big data analytics techniques as they work with large data sets and need access to scalable computing capabilities.
Mindful apps are complementary to the core system of records that most enterprises have and offer a way to extend their value to new use cases. In that sense, mindful apps do not need to be distinct or separate from core applications, except they bring the data residing in these systems to the point of action where it can have impact. Today many, but not all, mindful apps are on mobile devices because mobile apps have come to represent contextual, bite-sized, goal-oriented solutions—characteristics that they share with mindful apps. Hence, this section will briefly cover the trends in solutions for the development of mobile apps.
Mobile development platforms used in enterprises
Unlike traditional desktop or web applications, the life span of a mobile app is short; most mobile apps average around 14 months.4 And unlike the PC and desktop world, the mobile world presents a need to support multiple mobile devices and operating systems.
To meet these challenges, development platforms have the following key characteristics:
The development community has also explored the use of HTML5 frameworks for platform-neutral apps development. HTML5 provides many advantages, although it includes user experience tradeoffs because access to the native capabilities of a device is limited. For example, user experience concerns led to Facebook’s high-profile decision to transition from HTML5 back to a native development approach.6
There are drawbacks to hybrid approaches as well. Users expect the app to act as a native app and not a web application in a browser, and they have little patience for substandard performance. A hybrid approach has limitations on caching data and offline functionality compared to a native app, which can limit the functionality that can be implemented. Sometimes it is also necessary to make changes for platform-specific idiosyncrasies, which removes the benefit of a single code base and raises maintenance costs.
As hybrid approaches continue to mature, mobile app design elements should continue to spill over into desktop and web apps. The impact of mobile design can already be seen in the responsive design approach taken by many large media websites, such as NYTimes.com and BostonGlobe.com.
Looking forward, mobile development vendors must address many challenges, in particular:
The design and development of a mobile app are only half the activities needed to launch a solution. The other half is the delivery and deployment channel. Much like development tools, the deployment and management of mindful apps will be influenced by emerging methods for the deployment and management of mobile apps.
The success of consumer app stores has cemented user expectations for how apps are discovered and acquired. These expectations and the employee-driven app-centric movement have turbocharged the mobile application management (MAM) and enterprise app store (EAS) ecosystems. Table 2 presents a sampling of vendors that provide MAM/EAS solutions to enterprises. MAM/EAS systems have gained traction in the enterprise by providing two core capabilities:
A sampling of vendors that provide mobile app management and enterprise app store solutions
To continue to meet the evolving demands of today’s organizations, MAM/EAS solutions need more than their initial core capabilities. Security is an important part of governance but without a flexible solution in place, these lock-down and control methods often inhibit the usefulness and value of the mobile business tool. Finding the balance between security and risk management is challenging. Without that balance, IT and governance will be viewed as adding bureaucracy, not speed.
Leading solutions also include or will need the following key characteristics to support mobile management goals:
As the number of apps and associated content increases, the need for features that discover helpful apps for a particular user also increases. In an environment with hundreds or thousands of apps, only a handful might be useful to any one person. How they are filtered becomes important. Matching apps to users can involve sophisticated algorithms that use information from a variety of sources such as identity systems, usage data, and an understanding of the process that any app is in and the roles it is designed for.
App stores today primarily manage mobile apps. That is expected to change. “An app store is an excellent way for users to find and access an app, whether it’s a mobile or a desktop or a cloud application,” says Sam Liu, vice president of marketing and business development at Partnerpedia, an MAM vendor. He forecasts a convergence to a single management solution to manage apps on all platforms, mobile or not.
More vendors are entering the MAM/EAS market, providing alternative approaches and services built on top of a core MAM/EAS platform. These vendors are working to solve not only security issues but also to provide approaches for better app and content management. Table 2 highlights some of the vendors providing MAM/EAS solutions.
With the continued move away from monolithic apps toward smaller, more narrowly focused solutions, the need for better app management will be great. MAM/EAS solutions must evolve into portal-like solutions that provide not just discoverability but also access to content, files, analytics, and other advanced features, as shown in Figure 5. These future MAM/EAS solutions may even become the bridges between enterprise data, partners, and customers.
Evolution of mobile application management and enterprise app store solutions
The future of enterprise applications will unfold with the rise of mindful apps—apps that model human thinking as part of the business process of interest, use context to augment the capacity of employees to conduct knowledge work, and deliver intelligence in the moment. Although mindful apps don’t need to be mobile, many are. That is because the mobile platform is personal, brings with it considerable context, and can support users in the moment.
In contrast to workflows, which have been the foundation for enterprise applications thus far, the foundation for mindful apps will be mindflows, which are goal-driven thinking patterns—such as comparing, evaluating, and summarizing—used by anyone engaged in complex analysis and decision making. Enterprises have access to methods and techniques such as design thinking, activity-centered design, and digital body language that externalize and make explicit the user’s mindflows. These methods can be used during the design of the user experience to capture and model mindflows. They are complemented by solutions to develop and manage the overall user experience, available from a growing base of established and emerging vendors.
As mobile paradigms become mainstream, traditional applications and mindful apps are borrowing from mobile fundamentals, such as responsible web design, app stores, and cloud offerings. The expansion of mobile technologies is only beginning. Almost all enterprises are expected to adopt mobile solution in the next few years, which means the evolution and innovation in mindful apps will continue for some time. And they will change the form and character of apps on other platforms, such as desktop and web.
1. Steven Woods, Digital Body Language (Danville, California: New Year Publishing, 2009).
2. “Activity theory,” Wikipedia, http://en.wikipedia.org/wiki/Activity_theory
3. “Cory Gunther, “Apple A7 and M7 CPUs come to contextually compute: Motorola X8 on watch,” Android community, September 10, 2013, http://androidcommunity.com/apple-a7-and-m7-cpus-come-to-contextually-compute-motorola-x8-on-watch-20130910/
4. Josh Wolonick, “Where is the booming app market going?” USA Today, March 7, 2013, http://www.usatoday.com/story/tech/2013/03/07/booming-app-market-minyanville/1970245/.
5. The term composable refers to the characteristics that enable the development of new functionality by combining components of available functionality.
6. Daniel Eran Dilger, “Facebook admits HTML5 not competitive with Cocoa Touch,” AppleInsider, September 11, 2012, http://appleinsider.com/articles/12/09/11/facebook_admits_html5_not_competitive_with_cocoa_touch.