In today’s enterprise, the consumerization of IT has led to many interesting developments in Enterprise Mobility space. Based on my reading of various industry reports by market analysts, I anticipate that year 2013 will witness these key trends in the world of enterprise mobility.

1- It’s a Multi-Device World

People today are using more than one device computer, tablet, phone, etc and they use it in complimentary fashion. Conventional Desktops and laptops are being mainly used to produce information; tablets to consume and smart phones to communicate that information. In this scenario, it becomes imminent that organizations take the different form factors and capabilities of each device into account when designing their mobility strategy.

2- Shift from MDM to MAM

As device diversity becomes the standard as pointed out in the first trend, the focus will shift from mobile device management to mobile application management and broaden the mobility solutions to encompass much more capabilities and a better experience.

3- Adoption of Tablets in the Workplace

The adoption of tablets by the enterprises is growing at a phenomenal pace as it is proving to be very effective in the field and as stated in the Gartner’s report , the enterprise could account for as much as 35% of total worldwide tablet sales by 2015.

4- Data Security Remains a Concern

Security of Data on mobile devices is still the number one roadblock in widespread adoption of mobility by enterprises. Enterprises will choose a mobility partner who will impress the CIOs and the IT executives by displaying strength in areas such as device management, end to end encryption, application management, authentication techniques and many more.

5- Enterprise apps development to increase OR the year of the App

A recent IDC report showed that the world’s mobile worker population will reach 1.3 billion by 2015. Gartner says more than 40 percent of enterprise applications will have mobile apps by 2014. The need for function specific apps as generic apps just do not satisfy the enterprise requirements and it is further fuelling the growing app development industry.

6- Big Companies will muscle into the mobile management game

MDM and MAM products in 2012 were mostly produced by specialized vendors like Mobile Iron, Airwatch, Zenprise and Good Technology. With growing acquisitions of the likes of Zenprise by Cisco and Beetil by Citrix, it is apparent that many large organizations will get on with the mobility services game.

7- HTML5 apps will become more popular

There are three key players in mobile platform iOS, Android and windows phone and as there is no mutual development technology shared between them, the development of native apps becomes very expensive and time consuming. Enterprises and consumers need for web based apps which provide similar functionality and experience of native apps.

Gartner predicts that there will be significant shift from native apps to Web apps as HTML matures.

8- Virtualization and Cloud will Become Bigger Deals

Current practitioners of BYOD use app containers and encrypted wrappers to control how data is used on a device. However the IT administrators are not that happy due to the fact that data resides locally in the device and thus not fully secure. This year we can see organizations experiment with alternate approaches to storing data locally on device with virtualization and cloud based solutions.

9- Investment in mobile solutions to boost

As Mobile technology starts to satiate the need of enterprises to increase productivity, faster decision making and supporting collaboration. Many organizations will allocate a bigger slice of their budget pie for mobility solutions. As Forrester points out in its poll of more than 1000 IT Executives, the increased usage of mobile technology will increase services budget in IT to pay for these new services.

The above mentioned trends give us a sense of direction where the mobility industry would be heading. In subsequent posts we will discuss about the impact of Mobility on Startups/ ISVs.

References:

• http://www.forrester.com/pimages/rws/reprints/document/87581/oid/1-LTEQDU
• http://my.gartner.com/portal/server.pt?open=512&objID=202&mode=2&PageID=5553&ref=webinar-rss&resId=1972023&srcId=1-2920760834&prm=wb_gtpr
• http://www.retalix.com/blog/5-enterprise-mobility-trends-watch-2013/
• http://www.gartner.com/newsroom/id/2209615

The e-learning ecosystem for last one decade is predominantly revolving around ‘tracking’, ‘monitoring’, ‘supervision’ and the goal of ‘actual learning’ is left behind. Most of the standards followed by the eLearning platforms and content providers quintessentially ensure whether the course has been completed by the learner or not, or how the learner has fared in the assessments. They are less focused on whether the learning has happened or not. The focus has always been to improve the learning content and less has been the focus on understanding the learning patterns of the users and helping them learn, the way they want to.

Today’s learner wants ‘personalization’, ‘social collaboration’ and ‘anywhere, anytime, any device’ access to the learning content. I delivered a session at Learning Technologies 2013 on the topic ‘Content distribution strategy through multiple devices’. In this session we discussed in detail how a personalization interface along with a powerful annotations engine can help address many of these needs of today’s learners.

Personalization and annotations combined with social features can aid social collaboration, content co-creation and sharing, thereby creating an added layer of enriched content on top of the actual content. Annotations stored on Cloud and synced across sessions offer freedom of using multiple devices, without breaking continuity. Learners can share their annotations, follow others and collaboratively create and manage tags to annotate and categorize content. This makes the learning more effective and gives learners the freedom of applying their learning pattern to the content.

Harbinger, being a thought leader in the eLearning space, has shared this observation in various forums and has helped number of customers to implement it in their context. You too will realize and agree that the future of eLearning is ‘actual learning and not just tracking or monitoring’. Do let me know what do you think?

Even before we start, there is a pitfall that we should make sure we are avoiding. -

In determining the strategy, it is highly essential to remember that the Big Data analysis is only an efficient supporting tool for the overall company strategy. While it may validate conclusions and answer multiple questions — and in rare cases, dramatically affect the overall direction in which the company is going — it cannot be the primary goal of company strategy. The primary goal will always be something like “market driven production”, “demographic based sales strategy” etc where big data analysis will act as a supporting tool towards these goals.

With this in mind, we can start looking at what use cases and data the company has. There are two sides to this problem:

• Analysis Goals
• Data Patterns

As shown in the figure, both these factors will influence each other greatly.

Analysis Goal Definition

A lot will depend on the analysis goal definition. In case, the company is sure of what they are looking for, statistical analysis of historical and real time structured data can be the order of the day.

However, in case the company wants to experiment with various analysis and findings (and does have a very vague goal definition at best) we will need to start with multiple questions as input to experimentation. Tools that conduct polls and surveys, find trends using textual analysis of social data etc will help get a wide range of information for further decision making.

Data Pattern

On the other side of the spectrum, the overall data can be divided into two types:

• Transactional data
• Non Transactional data

Transactional data typically consists of structured data. It can be historical data, user data generated with day-to-day use, data generated by various functions of the organization etc. This is the data that we store in various database tables, and essentially has a predictable structure. The use cases here will deal majorly with the volume of the data as well as the Distributed Architecture of data.

Non transactional data on the other hand is the data that is coming in through various social media interactions. It can make use of various Social Networking Portals as well as emails, SMS etc. Another example of such data can be various logs generated regularly. The Non transactional data is mainly textual, with possible images and audio associated with the text. Typically this data does not conform to a standard schema.

Due to enormous volume of the data, as well as variety and velocity of data accumulation, use of Big Data Platforms like Hadoop will be necessary. These different data types need to be handled through different tools and mechanisms. Typically the transactional data may use business analysis and data mining tools and the non transactional data will need sentiment analysis and natural language processing / crowd sourcing tools.

In conclusion, classifying the use cases as well as Data Source and Patterns will provide us a high level idea of the workflow, platforms and tools necessary for Big Data analysis. This will be the foundation of Big Data Strategy.

Next blog will look at various preparation steps and road block in determining the big data strategy.

Now however, we all know that the big data trend is here to stay. There are both open source and proprietary tools available for us. With integration and gradual changes in architecture, small organizations can also get some share of the big data benefit.

I think the time has come for organizations to re evaluate their big data needs.

In this regard, following flow chart diagram can help by showing the possible first steps towards determining the big data strategy-

As outlined in the diagram, the use case and need / assets analysis is of foremost importance. Answers to these can influence the overall picture. Typical recommendation for any organization is to start small, start with what is already there, and keep on adding further capabilities and integration as the application / portal progresses. After implementation of devised approach, benefits assessment can be done. Based on the benefits the organization can decide to continue improving the portal further.

The flowchart mentions usage of tools and technologies as well as changes in database, operating systems and file system types. We will look at some of these in the subsequent posts.

Social Media integration or ability to use social networking portals for furthering the business using viral marketing effect is with us for a long time now. We have also learned that it is a two sided weapon, whereby, it can promote your product by leaps and bounds via a viral positive feedback, and also do irreparable damage by a similar negative one! So the obvious next step is promoting bi directional communication between companies and customers using social media and analyzing the customer feedback to use crowd sourcing for business benefit.

All these viral interactions generate humongous amount of data – big data – characterized by three Vs: Volume, Velocity and Variety. This informal and unstructured social media data is mostly textual and can be analyzed for positive and negative sentiments. Manual analysis is most effective for these sentiments. However, looking at the amount of data, this can quickly become a herculean feat. As a result, making sense of such data needs special techniques.

Enter natural language processing and sentiment analysis techniques.

There are algorithms that consider typical positive and negative sentiment expressions to analyze the data. These can be self learning algorithms that can keep on increasing the accuracy by enriching the sentiment dictionary over time. Basic pitfall here is misreading sentiments containing sarcasm or contempt. Understanding sarcasm comes natural to human brain, but can be very tricky to put in as an algorithm. However, considering that humans do not agree 100% of times, the accuracy of current sentiment analysis algorithms can be comparable to manual techniques.

With this background, Customer Relationship Management has turned a new leaf with introduction of Social Flavor in the CRM offerings. Gartner mentions Social CRM as one of the powerful current trends. There are multiple open source and proprietary Social CRM solutions that can be integrated with the website. At one end there are big players like Jive, SalesForce and SAP where as open source portals Topaz Social and Zurmo are there at the other end.

Typical offerings of such Social CRMs are following:
• Social network integration and operations
• Community platforms for Social Conversations
• Monitoring Social interactions
• Data analysis and relevance ranking
• Tracking results against business goals

As outlined earlier, many Social CRM solutions use NOSQL databases like MongoDB for capturing and handling the generated big data effectively.

Integrating and configuring these Social CRMs is easy. After integration, analysis of customer sentiments about website or product can be at available in no time.

Going the Social CRM way seems to be a no-brainer when it comes to quickly reaping the social media benefits for websites!

The decade old SCORM and AICC specs are set to completely change – ADL is working on Next Generation SCORM and the Experience API (popularly known as Tin Can API) is their first step in that direction. AICC is working on CMI 5 with objectives similar to those of ADL’s. I have been following evolution of SCORM and AICC specifications right from their initial versions, though I was never so excited looking at what is happening as I am now!

The Tin Can API specification is fast getting into good shape and once it is formalized it will have profound impact on the way we think of eLearning. Tin Can API will not really give us a ready solution or a detailed specification of a next generation eLearning platform; however it will give us a new way of thinking using which innovative solutions can be built to make learning more effective. It will help remove most of the restrictions imposed by current specifications and give us a foundation to build upon.

AICC is also planning to use foundation of Tin Can API to achieve the set goals of CMI 5 (next version of AICC spec). This would be a welcome change as the industry would need to deal with only one type of interoperability model. It is particularly important for content creators and platform developers as they would not need to worry about being compliant to two different standards.

My intention is not to introduce the Tin Can API or talk about its basic concepts, please read an overview here or dive deep here. I would rather attempt to present key benefits and opportunities it will offer. In my opinion, following are the important benefits (not in any order) of this paradigm shift:

Decoupling of Content from LMS

• The key change Tin Can will bring is decoupling of Content from LMS. Content can be anywhere in any form, as long as it can communicate with the LMS by passing ‘statements’ through REST web-service calls. With current SCORM specs, the content package has to be managed (import, launch and track) by LMS, and content needs to communicate with LMS through JavaScript API calls. This forces us to create content in a form that can be played by web browsers.
• The tracking can also be decoupled through integration with external LRS (Learning Record Server). LMS companies can also build their own LRS and have a tighter integration and at the same time collect data from other sources/LRSs.
• This paradigm shift will enable building distributed systems and help us leverage true benefits of SOA and Cloud.

Freedom for Content Creators

• As Tin Can API will recognize and track wide range of learning activities, including non web-based content, it will present huge opportunities for content creators. It will enable them to use content of various types and forms, from various sources, and in online or offline mode. It will support tracking of content defined data. Tin Can API recognises that learning is a continuous process and it cannot be confined by structured courses delivered through web based systems.
• Content built using any technology with an ability to consume web-services will work. Device specific features and device optimized user experiences (specifically on mobile devices) can be effectively used. Real life experiences can also be tracked with simple calls to LRS (using plain text statements or even binary data like audio/video clips).
• Hybrid learning paths can be easily built by mixing content of various types – traditional learning, mobile learning, simulations, virtual sessions, serious games, real life experiences, collaborative learning, social-learning interactions, offline learning, etc.
• Compared to SCORM and AICC, Tin Can will help you stay in better control of your content as you no longer need to have everything in web compatible form, there is no need of distributing content packages as zip files, and there are no cross-domain limitations.

Better Learning Experiences through Improved Analytics

• Today we live in a data-rich world. There are many businesses that use loads of data collected from user’s experiences and activity streams to enhance their product and services, or enhance user’s experience of their products and services. Same can be certainly done for learners, and Tin Can will help in enabling it. It will provide means of tracking data that can be as fine-grained or as coarse as you want. With current specs of SCORM and AICC, there are limitations doing this, as the data model is limited/pre-defined and there is limited support for user defined variables.
• Tin Can API will allow saving almost everything on LRS (including multiple attempts, run time data etc). Wisely formed queries on actor, verb and/or objects can provide interesting information and will provide whole new level of reporting detail. Even a raw activity feed of a user will reveal good information if the statements are used appropriately.

I believe this paradigm shift will open many opportunities in future, going well beyond Tin Can API. I understand that there are some gaps/work-in-progress items in the current version (0.95) of the Tin Can spec and ADL folks are working towards resolving most of those. I would prefer to be optimistic and wait until ADL publishes final version of the Experience API, likely to happen early next year. However one thing is clear that eLearning industry is going through an important transformation, using newer and lighter technologies!

Operations Support systems exist in different modalities, ranging from personalized services to automated emails. But tele-support systems are the most popular, as they provide a right balance of convenience and affordability. But these telephone systems are rapidly aging as they are not able to keep up with changing technologies. Due to this, companies are desperately seeking measures to enhance their systems.

Recently Harbinger Systems undertook a project for a giant enterprise (with over 50,000 employees). The enterprise had a conventional telephone based system integrated with an IVR (Interactive Voice Response – keypad only, no voice) interface. Though the system was successfully run for a number of years, it had started falling behind on the user’s growing demands for more convenience. For instance, during the peak load the phone lines were getting jammed, users only had audio aids to state their problems; and all this resulted in long duration calls, incorrect redirections and importantly larger call dropouts.

The solution to this problem was to make the support system more accessible and better interactivity. Fortunately, the answer wasn’t far. The enterprise had made it mandatory for all its employees to use Microsoft Lync for all intra office IM communication. MS Lync clients were already installed on all computers connected to their network. So we came up with a radical solution, to build an interface to the Operations Support system into the Microsoft Lync infrastructure. With this employees were no more dependent on telephone lines, as Lync communicates over the network.

The solution was built using a combination of technologies. UCMA (Unified Communication Managed APIs) was used for handling the Lync connectivity and communication. A custom BOT on the Lync server managed the redirection. The Lync client was extended using a Lync CWE (Conversation Window Extension) which used a Silverlight UI. This interface had a cool looking Windows Phone (metro style) like of interface. This UI made it very easy for the user to state the problem just by clicking on buttons carrying easy to understand graphics.

This new interface surely solved the two core problems – accessibility and interactivity. But here are some more advantages it opened –

• For IT issues, users could share their screens from Lync in the context of the support call
• Conferencing with multiple in the same support call became a piece of cake
• Using the Conventional IVR system, an employee spent an average 48 seconds on the phone to go through the menu reaching the right queue of support helpdesk. This interface reduced this wait time to a few seconds. That is huge time savings for employees and enterprise
• This will also result in huge savings on 1-800 toll charges the enterprise pays to telecommunication companies

This solution is just one of the places where Microsoft Lync played a role. Going forward, we strongly feel more problems could be solved with the Lync based solution. For instance, Lync being used by back office employees to answer Support calls.