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Latest insights and trends in Personal Analytics, Operational Intelligence, and Workplace Productivity.

Feb 01
Personal Analytics in the Enterprise
The explosion of enterprise communication devices (including IM clients, email clients, mobile phones, desk phones, social networks, and web browsers) has created an unparalleled opportunity for businesses to streamline operations and boost team performance.  But for most companies, the volume and velocity of Big Data these devices generate turns this analysis opportunity into paralysis.  To better understand the opportunity that’s being missed, we need to take a closer look at the difference between 'business analytics​’ and ‘business intelligence,’ both of which are useful in slicing and dicing data and improving business performance across the enterprise.   

 
Business Analytics versus Business Intelligence

 
Business analytics focuses on developing fresh, new insights that drive smarter business decisions.  By contrast, business intelligence typically focuses on measuring past business performance (by year, month, day or minute) and using those metrics to guide future business plans.  While business intelligence based on historical data has value, for many business managers trying to steer their company through complicated commercial, retail or regulatory environments, navigating this way can be a bit like trying to drive a car by looking in the rear-view mirror.  Real-time business analytics provides insight into high-volume streaming data sources, communication patterns, and ongoing business processes and provides a bigger and more complete picture of your enterprise environment, especially if your goal to streamline or simplify business processes that drive customer experience.  Tools like Hypersoft’s Personal Analytics can give your enterprise a better view not only of what you’re driving through, but also what’s around the bend and further down the road.

 
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Making Sense of a Business Unit Merger

 
Case in point is an assessment that Hypersoft’s Organizational Intelligence analysts recently did of a business unit merger involving a large global enterprise where three different business units (originally 240 persons in total) were merged into a new business unit of 98 persons.   By using Personal Analytics tools to automatically collect and analyze shared communications and work processes, including data from telephony, e-mail, and instant messaging where both desktop and mobile clients were measured, analysts were able to capture a snapshot of the underlying connections and communications channels among widely dispersed employees in all three units, and the results helped the merger team articulate a vision of what the combined business units’ optimized business processes should look like.  Personal Analytics was especially useful in helping see beyond the formally defined roles within the three business units to identify and analyze informal knowledge-sharing and professional collaboration networks.  These insights enabled merger decision-makers to have a better grasp of the hidden aspects of their workplace communities in operation (who was talking to whom and to what degree) and to understand who was important and influential within the different business units.

 
The use of Personal Analytics provided before-and-after insight into the success of the merger.  In this case, immediately after the merger, PA data monitoring showed that the legacy business units were still functioning as stand-alone units despite having been formally merged into one organization.  Six months into the project, Personal Analytics was able to show that all members of the new business unit were now part of a single working community, which confirmed the successful transformation the merger team was looking for.  

 
Driving Sales with Personal Analytics

 
After the failure of sales optimization project at a large European energy company that involved face-to-face interviews with most of the company’s 300 sales reps, the energy company decided to try a business analytics approach that used Personal Analytics to get a clear and unbiased picture of the communication activities of each of their salespeople.  Personal Analytics gave both sales managers and individual sales reps a clear picture of how the different sales teams were spending their time, that is, how much of each salesperson’s day was sales-active (interacting with existing and potential customers) and how much wasn’t.  This customer interaction data collected was used to develop a profile of each sales team based on three months of communication data from telephones, iPads, calendar appointments, etc., as well as to do benchmarking to assess the performance of each sales rep relative to industry best practices.

 
Here’s a sample graph that shows the data being collected on a weekly basis: 
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Here’s a roll-up report based on three months of communication data:
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Let Hypersoft Create a Personal Analytic Project for Your Enterprise

 
With over a decade of experience in understanding the right metrics to use to monitor communication in ​​​dynamically changing environments, Hypersoft can help you properly choose and interpret metrics and do the analysis required to streamline and improve your company’s business processes.   
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This includes using Personal Analytics to improve core business operational processes like sales, marketing, purchasing and manufacturing, as well as strategic management processes like merger/acquisition strategies.  Find out more here​.  

 

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