Sunday, July 22, 2012

Leveraging machine data to reduce support costs

Most progressive support organizations are now moving to leverage Big data to become proactive. They want to put behind the days when support teams were always behind the curve, with the customer knowing about problems much before support knows about it. Further its takes days or weeks for support teams to understand what is going on based on logs uploaded. Tools to analyze logs and determine possible issues have helped but they are mostly single user tools which help highlight simple keywords and when a log file consists of bundles of files with multiple sections and formats a simple search does not help.

According to a recent survey among the support groups of 3 of the world’s top selling storage vendors, it takes an average of 12 hours to identify and resolve any issue. Of this, up to 30% of the time is spent in determining root cause - finding, organizing, and making sense of the glut of diagnostic data coming back from the product.

At Glassbeam we have been working on some very interesting solutions that dramatically improve support productivity. What if you could parse multiple sections of a log file or a set of files, whatever format they in, and apply business rules on data within the file to determine if there were known issues. As an example – say your customer uploads a log file into you instance( or whatever CRM you use) while creating a case. What if the log file can automatically be parsed, a quick summary of current configuration shown, rules from your knowledgebase applied to the file to determine possible issues and even recommend solutions based on previously known cases? That's a potential savings of 11 hours and 55 minutes per case!

At Glassbeam we are applying big data to solve thorny problems for the enterprise and its executives.

Sunday, July 15, 2012

Looking at the softer side of execution

Many people ask me what are some of the core values (or I call them guiding principles) for Glassbeam.   We have a list of 10 things here.  But if I were to pick top 3 that make the most impact, interestingly they all relate to the "people" side of the equation.  Here they are:
Hire the best...

We should hire only the BEST and no one else. This is very true especially as we are at a critical growth phase in our evolution. “A” players tend to hire A+ players because they care about their reputation and know that is the only way to excel and achieve higher goals. “B” players end up hiring similar caliber or “C” players, and “C” players go down the rank to build a team of “D” players because they avoid tackling tough problems. By being careful and deliberate on hiring the best and the best only, we avoid a deck of cards that does not take anyone anywhere.
Never give up...

Never give up, retool if necessary, but never ever give up. Start-­-ups are like swimming in an ocean where tides come and go. By having the courage of constantly trying and not giving up, we tend to dramatically increase our probabilities of success. Markets change, strategies change, products change, but if one is clear on the core values of why we are in this together, then each downturn is an opportunity to excel at the next upturn of events.
You cannot do everything...

It is very easy to want all and not be able to focus on one or two important things that can drive product success in the market. Therefore, we owe it to ourselves to constantly keep reminding each other on making clear choices and tough decisions. This is truer for Glassbeam since we deal with data end to end as an end user application. We have to make a conscious effort to focus only on a few things that we do the best and leave others for our customers and partners to derive value on their own.

Tuesday, July 10, 2012

Moneyball for sales and service

With the buzz around Big-Data it is important to keep in mind what can be done with the data. For those of us who have read or watched Money Ball it is apparent that you can use insights derived from data and combine that with your intuition to make better decisions.

Glassbeam gives you the tools to make such decisions in your business, based on unfiltered machine data.

Once products are sold to customers, the product manufacturer has very limited visibility into how a customer uses the product. The customer feedback is always filtered through the words of the field person or the call center agent or the customer themselves. And not all data is captured. This is not the way the internet companies work. Web based product companies are constantly collecting data on consumer usage and mining the data to make their web pages better, to provide a better experience to their customers or to help realize additional value to simply provide a better performance by knowing and acting on issues proactively. Physical product manufacturers are reactive because the tools to collect and mine log data are not geared towards business users.

Any product executive needs to be on top of how customers are configuring and using their product and find issues before their customer does. As one of our customers put it, “It is embarrassing when my customers know more about what is happening to my product before I do”.  Many product manufacturers log or collect tons of data but don't have tools to make sense of the data being collected.

With Glassbeam, sales and service people can arm themselves with detailed customer intelligence before an account call – based on actual machine reported data. Everything can be logged and should be logged – machine usage, performance metrics, specific configuration and customer specific settings, various events across all the components that make up the storage box. Glassbeam’s customers are realizing the power of data by capturing machine chatter and mining the data for to make better decisions on support models, account management, product roadmaps and licensing.