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Revamping the MSE User Interface

As part of the WLC 8.0 release, we addressed customer comments and revamped the user interface (UI) for the MSE. We wanted to make it easier for customers using both MSE and PI to adjust to larger deployments. We also wanted to quicken the pace at which we could deliver features to the customers. Today I want to walk you through the landing page and configuration of the new MSE UI.

Landing Page

The landing page is the first thing one sees when logging into  the MSE UI. This page provides the user with a basic snapshot of system health, an easy way to launch the apps, and a quick status of the various services on MSE.

System Health

The new UI highlights important parameters like CPU and Memory usage in order to give the user an indication of the stress being handled by the MSE.

 mseui1 Read More »

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Analytics to Identify and Strengthen Organizational Collaboration and Drive Innovation

Companies with many employees face various challenges w.r.t. their size. One of these challenges is to identify key people, skills and information across (and outside) the organization and use them in the most effective way to drive innovation, new initiatives, but also sales.

Situation Today

The natural way for employees to cope with such a challenge is to build social networks (I mean networks of people not software) and collaborate across the organization. This organic social network building happens through various activities such as projects with colleagues, social activities, company events, etc… However, such social networks take time to create, and are typically not that extended. The effectiveness of these social networks is hard to measure (unless perhaps you equip your employees with location trackers). This social network building, I call the qualitative approach to organizational collaboration.

Connect and Collaborate

Connect with the right people inside and outside the enterprise

Many companies have deployed technology solutions (tools) to cope with the challenge described above. Companies have personnel directories that show employees’ groups and the official organization hierarchy. Some of these personnel directories allow users to add more personalized information (but this information is not always up to date). More sophisticated personnel directories (or other collaboration tools) also feature timelines of activities/tasks, blogging, integrated search, etc…. .Video conferencing enables people to connect people remotely. Despite these new social tools, email and mailing lists still play an important role in connecting people and disseminate information as well as external social networks and resources. All these tools provide a wealth of information. In essence: collaboration is Big Data.

Do all these social/collaborative enterprise tools help us doing our job better and promoting innovation? From a personal point of view I am tempted to say yes, but much more can be done. My main concern with most of these tools is the lack of analytics features to quickly identify user-relevant information or contacts. New tools -- and newer versions of already existing tools -- are starting to provide some of these capabilities, but IMO that is still not enough (or not accurate enough) to fully understand the evolving social networks or the relations between people and information (documents, emails, etc…).

What can be Improved

The goal of exposing more of the right analytics to end users would be, for a user, to faster gather insights, new ideas, and enable quicker decision making and eventually translate these insights and ideas to new opportunities, projects and/or costs savings.

Analyze and Correlate

Correlate different sources to identify information

To achieve this goal, users should be able to identify patterns in their organization’s data, specifically on threads or evolving thoughts and interactions that can be relevant for their particular projects or questions. In essence, analytics should foster more and improved collaboration with like-minded people, or people that share a common goal. As mentioned earlier, people naturally do this already, but in large organizations it is humanly impossible to scale this effectively and fast, without the help of analytics tools. This type of analytics I call the quantitative approach of organizational collaboration, which I see as complementary to the qualitative approach.

When I look for example at mailing lists or video conferencing, a few questions always pop up in my mind that modern enterprise collaboration tools should be able to answer in just a few clicks:

  1. What topics are trending during the last week/month? Perhaps type a topic in and get trend information or have the computer generate topics based on a context analysis of your posts or email conversations.
  2. How are the groups and hierarchies evolving over time (who is talking to who)? Can software recommend groups of people that are relevant for me and my projects?
  3. What people can be considered as experts on certain topics, based on their posts, replies, published articles, etc…?
  4. For particular topics, who are the top contributors and how do they relate to the experts? Are people clustering around certain topics?
  5. Who are the influencers/thought leaders, and how do they relate to experts?

From a strategic point of view companies can leverage analytics from social/collaborative tools to answer questions like:

  1. Are best practices shared across the organization between the appropriate groups?
  2. Is there an alignment between strategy and direction of the company?

This is not an exhaustive list and as a software engineer I think that an additional relevant feature for any tool should be the ability to provide an environment to mashup and integrate data by employees, to answer some of these questions.

How can it be Leveraged

Various groups and people (MIT, Virginia Tech, …) do research on this subject and translate this research into strategic insights at the enterprise level. The next step will be to provide the insights to individual employees as well. Enterprise tools with more sophisticated analytics capabilities (many focused on machine learning) are beginning to emerge. Perhaps the biggest challenge is integration of such capabilities across multiple internal and external tools and platforms.

Organizational collaboration is for me not limited to an enterprise environment. Groups with different affiliations who organize themselves as “virtual organizations” to work together towards common goals (for example, Open Source communities or standard bodies) can benefit from this type of analytics too.

To be more successful in capturing the value of collaboration, companies not only need to deploy the right tools, but also need to foster a mashup environment to leverage the organizational insight and tacit knowledge of its employees through analytics.

Special thanks to Marco Valente and Yannik Messerli for the discussions and insight on this subject.

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Why ISVs Must Transform In SMAC Environment

In today’s era of SMAC – Social, Mobile, Analytics and Cloud based solution, Pay-Per-Use licensing and Dev Ops software development methodology, Independent Software Vendors (ISV) are facing major challenges on many fronts. ISVs strive to differentiate from their competitors and gain new customers, as well as retain existing customers and generate additional revenue from them. This shift is happening throughout the software developer market and has surfaced technological and business changes for ISVs.

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Show Me the Retail Data

retailSuccess in retail often comes down to a counting game.  How many people pass by your store?  How many come inside?   How long do they stay?  And most importantly how many ultimately buy?

Today, the retail counting game has gotten a lot easier because we can now count devices as proxies for people, since many potential customers today, myself included, won’t leave home without their smartphone.  As soon as they enter a store, the beacon on their cell phone effectively announces its arrival to the Wi-Fi network and voilà, we have a count.

With the help of CMX Presence Analytics, these smart devices can help answer many key retailing questions with a single access point.

  • Who?
    Who is passing by the store versus coming in?  Presence Analytics uses both the cell phone’s signal strength as well as the time spent in the area to determine the number of people walking by versus in-store visitors.  Presence Analytics provides simple, quick reports on retail conversion metrics.   You can also track how often visitors return to a store in a given time period can be tracked, which can be key for customer loyalty programs.

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Next Generation Applications and Data Analytics

I was speaking with a customer today at VMworld and, unlike many discussions, which are focused on the infrastructure (servers, storage, networking), this one turned primarily on the application. This person was describing to me his need to match the server to a new set of applications he is being asked to support and then what to do with all the data being generated.   With much of the conversation at the show focusing on virtualization of resources, he made the point that consideration of the architecture itself – how servers, storage and networking is leveraged – was still critical to mapping the requirements of the application back to what that application lives on.

This is a trend we’re seeing more and more.  A new breed of applications, and the increasing density of data, is driving a new way of thinking about the underlying infrastructure.  Often, these applications are developed internally, leveraging many of the toolkits available on the market today, and delivered through a private or public cloud.  These applications can be run from Read More »

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