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Benefits of collecting and harnessing product operational data
Puneet Pandit
Thursday, February 2, 2012
Traditionally, we have lived in a world where technology manufacturers build, ship and install their products at customer sites and then tend to ‘lose sight of it’. There is little information on products’ actual configuration, performance, and related usage characteristics - that is on how customers are actually using different features. Today, the sources of feedback that typically relay back such information on a product’s current state could be CRM systems, Databases that log support cases, emails and conference calls with field sales engineers or customer contacts. Needless to say, these sources are archaic in nature and are unsuitable for a rigorous and timely analysis of a product’s operational state.

This old paradigm is changing rapidly where today’s world is characterized by intelligent, networked products that routinely generate and send back machine data to a centralized location. This data (sometimes referred to as “call-home data” or “support bundles”) contains valuable information about performance trends, defects, configuration changes, and on the state of the installation at client sites. If harnessed correctly, it contains information that can provide immense value to an organization -- helping them resolve support issues more efficiently, building smarter product roadmaps, understanding the extent of exposure to a product defect, creating new service revenue opportunities, and in enhancing overall product differentiation in the market place.

Acting on this market need, Glassbeam has developed a new, patent-pending technology to collect and parse product operational data, and to present deep analytics to product manufacturers in a compelling, graphical format. The platform lets one define a scalable data warehouse from any kind of semi-structured data in a single development step, at a fraction of the cost, that would otherwise take multiple people number of months to execute as a complex IT project.

There are three broad functional areas that can greatly benefit by an analysis of log file data emanating from devices in the field:

1. Support

2. Engineering and Product Management

3. Sales and Service Support teams

Support teams of almost any complex product manufacturer frequently face one seemingly intractable problem: quickly identifying the root cause of any issue and efficiently delivering a solution that is satisfactory to all stakeholders.

The products they support are constantly exposed to scenarios where interacting or embedded systems malfunction, or to maverick customer behavior like undocumented and unwarranted changes to existing configurations. When a problem occurs there is often no efficient way to collect and assimilate relevant data and make it available for analysis. There has traditionally been a paucity of powerful tools that collect, sort, and distill this semi-structured machine data, transform it into discernible trends, and present these through a powerful visual interface.

In addition to the need for resolving support issues expeditiously, there is also the desire to integrate knowledge or bug databases allowing the system to set up incoming alerts and error messages that flag specific recommendations. Support and field engineering teams can act upon threshold summary reports and e-mail alerts to take requisite remedial action, or to provide proactive recommendations to ensure optimal system performance.

Let us take an example: A disk drive at a customer location is reaching its storage capacity. In a world without call-home data, the drive would malfunction at some point and this would also degrade the performance of systems it interacts with. The system manufacturer would get a support call and typically spend considerable time understanding the issue, assigning it to the right support person, and then delivering a solution. However, if the manufacturer has access to a system that collects and analyzes log file data, then support teams can be notified in advance of a possible technical issue. Support teams can quickly access relevant information, cross-verify it with relevant data points, act proactively to inform the customer of the scenario, and implement steps that prevent any degradation in the system’s performance.

Glassbeam Support Portal™ helps support engineers address and resolve technical issues. It parses, organizes and presents relevant information about product configuration changes, patterns of events and statistical readings on parameters including performance, capacity, and whether products are being used outside of normal limits or baseline configuration.

Engineering and Product Management Teams

A majority of technology product manufacturers incorporate market signals and customer needs into their product roadmaps. However, a deeper analysis reveals that they use numerous unscientific and purely anecdotal signals to define product direction. In a typical scenario, product managers conduct some primary research, collate findings with inputs from field sales, engineering teams and marketing managers and then triangulate with numerous external considerations to define product roadmaps. The approach has several shortcomings: Focus groups and e-mail surveys provide only a fragmented slice of the overall product usage information. Customers are typically averse to detailed surveys and focus just on burning issues that need to be addressed urgently. Second, the data can easily get distorted by personal biases, incomplete responses, and pure lack of knowledge regarding where, how, when, and to what extent products are actually being used. Finally, CRM datasets can only provide ad-hoc and incomplete analysis that skews vital statistical information on actual product deployment status.

In a world characterized by ‘closed loop’ feedback, technology manufacturers can avail of granular, real-time data from installed devices to get an accurate and detailed picture of their install base and on how their products are being used by customers. Glassbeam Business Intelligence (BI) Workbench™ provides a user interface (UI) and query tool that enables the parsing and mining of countless parameters and combinations of data and presents the information in an easy-to-understand format. This enables them to get powerful insights into popular features, optimal system configurations, and on various other parameters. The data and inferences drawn from analyzing the findings can form the basis for a much more informed product roadmap that accurately aligns new features with customer needs.

Services Teams

Services organizations are constantly looking for opportunities to deliver value-added offerings to existing customers. However, the approach towards a potential sale or a services contract is influenced by classical inputs – volume, discounts, customer history, buying patterns, competitor offerings and industry-specific dynamics. These inputs are often combined with stale and inaccurate data in CRM systems to arrive at a customer profile – which in turn forms the basis for deciding on the likelihood of succeeding at renewal, upselling and cross-selling opportunities.

In an operational setup characterized by access to relevant, timely and actionable machine data, Service and sales teams can complement traditional up-sell and cross-sell methods by leveraging the “truth” being reported back home. Sales operations can study daily usage trends to track customers that are peaking at capacity. Such customers become active prospects for proactive sales and marketing campaigns. Service teams can use Glassbeam Dashboards to launch Health Check Services that can provide their customers’ centralized access to key reports like current configurations, capacity usage and trends, and performance summaries. These reports can be used to track current data and trends across the entire installed base, segment events by severity and location, identify applications or groups that are utilizing full capacity, determine causes of network congestion, and numerous other important metrics. The reports can be used for better planning and resource allocation to ensure all installed products are functioning at optimal capacity.

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