Don DeLoach's CEO Blog
In the last few weeks I have had the chance to meet with a number of organizations that I would characterize as "smart energy" companies. They are doing everything from holistic views of large-scale properties where "green initiatives" are implemented through business process changes to companies that are providing smart devices that can be controlled by smart home automation systems for more effectively managing energy from the dishwasher, water heater, and even the light bulb. There are also great university initiatives underway to encourage and develop smart energy solutions, like the one I visited this week at my alma mater, Georgia Tech. Back when I was in school, far too many years ago, I began my professional career as a co-op student working at The Southern Company, one of the biggest energy companies in the U.S. To say that effective energy management has come a long way since then is a gross understatement. I never would have dreamed of software solutions that could not only detect but control computing resources over Ethernet cabling. In fact, at that point I probably didn't even know what Ethernet cabling was! But to reach across and into power distribution resources to determine what should and should not be active in an optimized fashion is an idea that is now on the horizon. To think that light switches, washing machines, garage doors, and TVs can be effectively controlled for more efficient use of energy is not only a possibility, it is an absolute certainty in years to come. That isn't even all that advanced, compared to the fact that your computer can be managed down to the services of your word processor or having a spreadsheet turned on or off within the program itself to conserve processing power. And that, too, is here today.
The more effective world of energy management is indeed here today, like the world of mobile computing was here in the mid 90s. You saw "car phones" and a few "portable phones" here and there (remember the Motorola brick?) but they were by no means widespread...in the mid-90's. Of course, they are now. We at Infobright really love that because all those mobile phones generate loads and loads of machine-generated data which is what we we really care about. But you know what else generates a lot of machine-generated data? Smart energy management systems. A smart energy grid. Smart buildings. Smart houses. And while there is evidence of this today just like there were portable phones in the mid-90's, there will be an overwhelming amount tomorrow. There is no doubt whatsoever.
And just as we embrace a world of exploding amounts of weblog traffic, mobile traffic, call data records, increased sensor data, and network and event data, we are ready to embrace the world of smart energy. For so many reasons for all of us, it cannot come fast enough.
Bring it on.
Several of us from Infobright attended the Mobile World Congress this week in Barcelona. Several of us, along with around 70,000 of our closest friends. I thought I would take just a moment to offer a few views about the conference. To say it was quite an event is an understatement. If you were a "device person", you were in the right place. All the latest and greatest from everyone... except Apple. Their absence was noticeable, and I think unfortunate for them. Everyone else was there. And there were some very, very cool offerings and stands. Samsung was lively, as was the Android area, complete with dancing green character robots. The woman I sat next to on my flight back to London commented that she liked it there because "they made me very happy". Worse had been said, for sure.
The event is comprised of seven buildings, a "courtyard", and an "Avenue". It is huge. A few of the buildings are where many many exhibitors have their stands. Then there are the mega sites, like entire buildings housing the likes of Sony Ericsson, Alcatel Lucent, and Huawei. In the "Courtyard" were individual smaller buildings (with "smaller" being relative, of course) housing Accenture, Juniper Networks, IBM, and a few others. Some of these also had exhibits in other areas as well. Some also came with armies of people. One thing is certain: Barcelona was the big beneficiary. I cannot help but think that the economic impact of a show like this is fantastic.
Then there was Hall 7, which was the "App Pavilion". This had a different vibe altogether which included loads of app vendors, game vendors, a few device suppliers (RIM), and 80% of the conference attendees who were under 30 and wearing jeans. The difference was both obvious and funny. It was a great place to observe, and it also had good wireless access points. That, and the Mozilla/Firefox booth was giving out cappuccino's. Hard to go wrong there.
What struck me though, more than anything, was the common thread that ran through the entire conference. There were over 70,000 people and hundreds upon hundreds of companies exhibiting representing billions and billions of dollars in the market, all of whom were generating, consuming, and analyzing machine-generated data. If movie stars go to South Beach, gamblers go to Las Vegas, wine lovers go to northern California or France, and art lovers go to Paris, then those of us who get up in the morning and go to sleep at night excited about the evolving world of machine-generated data go to Barcelona in late February for Mobile World Congress. The evidence of the importance of machine-generated data is everywhere, from the Machine to Machine (M2M) forums to health care companies feeding biometric sensor data through bluetooth phone links to the amazing amount of records and logs supplying the variety of systems involved with mobile convergence.
We went over with high expectations in terms of increased work with current customers (many whom were there), new projects, and new relationships and opportunities. By Tuesday we had exceeded them all. This means we have our work cut out for us in execution, which is a great challenge to have. And even more, if you really plug into what is going on, you can't help but come out with a bit of an education as well. The world is moving at an accelerated pace. The very things that worked so well and were so dependable just five years ago could well be the downfall of some. People and companies are rethinking everything in order to scale and adapt to this new environment.
We find that exciting. I can't wait until next year. But for now, there is much to do!
I love the old saying that "it takes longer to write a short paper than a long one". I can certainly attest to that. My education is in Industrial and Systems Engineering. I never actually thought I would become an engineer, but was very attracted to the extension of engineering, and in particular, the fundamentals of Industrial Engineering to so many other aspects of life. Along the way there were a couple of people in the field that influenced me. One was Dr. W. Edwards Deming. He is in many way is the father of Industrial Engineering, whose overriding philosophy was "fix the process, not the product". In the subtext of this was the notion that less can often be better. A product might be built better, with less errors, and with less cost by having fewer processes and less handling along the way. More doesn't always equate to better. The other figure was Dr. Eli Goldratt. He championed the Theory of Constraints, and pioneered a scheduling algorithm called "OPT", which was controversial when it was introduced. Many organizations who adopted the use of OPT for scheduling would ultimately disregard the result sets and corresponding scheduling imperatives because "it did not feel right". This became so common that he subsequently worked with an author (Jeff Fox) to produce a novel called "The Goal" (which later took on somewhat of a cult status) that served as a backdrop for explaining his theory. Later he would deliver a series of corporate presentations on overheads (for those over 40) that he eventually compiled into the follow-on book called "The Race". The simple underlying principle was that work-in-process is bad, and that it should be limited to as little as possible. Your costs, your delays, and your error rates all went up when you failed to embrace the very simple principles behind this. Dr. Goldratt had a Steve Job's-like quality of abrasiveness, probably born out of his combination of intelligence and focus, much like Jobs. He was known to tell plant managers and company presidents that they were "idiots" who were screwing up their companies.
At Infobright we are guided in many ways by these principles. Our clear focus is to provide the ability to store, retrieve, and analyze machine-generated data. As a central design point, we strive for simplicity in the user experience and a minimalist requirement in terms of computing resources. We touch the data as little as possible by implementing an architecture that is uniquely suited for machine-generated data. Many of our customers have said "I just loaded the data and began working with it" and that "It just works like it says on the tin". This is music to our ears.
The Mac was not a success because of its complexity. And the songs played on an iPod were no different than the songs played on the RIO that came before it. But the appeal, and subsequent massive acceptance of both the Mac and the iPod, was in the elegance and simplicity of the design, delivery, and user experience. We think that's a great thing. Relative to the alternatives for storing and analyzing machine-generated data, we believe we are simpler and more cost-effective. We don't really extend into other areas, but as a result, we gain in terms of this simplicity and cost reduction. We are absolutely OK with that. And while we believe we have a nice level of elegance in our simplicity, we continue to iterate and improve.
Before many organizations invest in technology, especially when it's a new type of technology like a columnar database or a new BI tool, they will run a quick proof-of-concept. I have seen many, many of these. Some are done well, others are not. Here is a quick list of things to do and not to do when running a POC.
Let's start with things TO DO:
- Think through how you really expect to use the technology, and design your POC to reflect that. This includes the type of queries, the amount of data, the number of users and concurrency, the type of data, etc. You may not be able to re-create an exact simulation, but the closer you come the better.
- Make sure you have the right hardware to run the POC. This should be as close as possible to the configuration you would use in production.
- Make sure you have people assigned to conduct the POC. If training is involved, then to the extent you can have your team gain an understanding of the POC environment, that's great. If not, then at least seek help from the vendor in order to have adequate oversight to ensure the POC yields results. Assume your own staff would ultimately need to increase their knowledge of the tools being tested.
- Establish success criteria. How long should the query set run? What kind of ad-hoc performance do you expect? What should the concurrency rates be? What should the compression ratios be? How much DBA time should be needed to establish the environment? What should the load speeds be? All of this can be established going in if the right thought is given to the effort on the front end. This will always map to a productive effort.
- Make sure you are serious about what you will do if the POC is successful. If both sides don't understand that, then the POC can be a great deal of work for both with no real results. For example, if the success criteria is met, will you proceed to negotiating contracts? If met, will the supplier agree to pricing you can afford? Much of this can be worked out up front.
Things NOT TO DO:
- Embark on the effort with the intent of "playing around with the technology". That can be done, but it's not a POC.
- Fail to allocate the proper hardware configuration to adequately test the software.
- Fail to test over a reasonable representation of the system load, i.e. don't test against 20GB of data if the anticipated production will be 15TB.
- Fail to allocate people to do the testing.
- Go into the test without a defined success criteria (as specific as possible).
- Expect the vendor to do everything.
- Expect the vendor to do nothing (as you will often make assumptions that may lead you down incorrect or inappropriate paths).
- Allow the "high priority" POC to get stopped and interrupted several times, because it turns out it isn't really a priority. This happens all the time, but it helps both the buyer and the seller to be as honest as possible about this up front.
- Overtest. It's a POC, not a full development project. Don't assume you are going to run a POC that can be flipped into production at the end, unless this is truly contemplated alongside and with the agreement of the vendor. Otherwise, there will be a significant gap in expectations.
- Do not treat the person or people from the vendor as servants. Most really like their work and are there to help, but they should treat you with respect and vice versa. This is obvious, but it is amazing how often this is a problem.
All in all, a Proof-of-Concept can be a very valuable exercise in determining whether a new technology is right for you. But it's work on both sides. If done right, it doesn't have to be a ton of work, but it can be very, very rewarding for everyone with just a little planning and thought going in.
I drive a Saab. This is because I really like my car, and because I really like the support I get from the Saab dealership. I am on my fourth in my family right now. My first was not so good. I swore it would be my last. But Dan, the service manager at the dealership, took the time to understand what was important to me, and to get my car fixed well and without overcharging. When it came time to get a new car, I went back there because of Dan, mainly as a courtesy, but to my surprise, ended up loving the 9-5 Turbo in 2001, so I stuck with them. And so the story goes. I would not have ever purchased the second, or third, or fourth had it not been for the great customer service I received. I have flown hundreds of flights on British Airways. Same thing exactly. Judy and Marcia on the ground in Chicago are the best I have ever seen. They are the face of BA, and they are good because they are very, very competent, and because they genuinely care.
Now caring without competence is not so great. The caring part may be nice, but everyone wants results. That's absolutely reasonable. But competence without caring is not so great either. Because you CAN do something does not necessarily equate to your willingness to ACT. It takes both. And again, you might be willing to take action, but incapable of taking the right action. When I am in a pinch I know Judy knows what to do, and cares enough about me to get it done. She has both. Same with Dan.
Technology vendors are seldom great at this. This is true for two reasons. First, depending on the technology itself and the size of the company, it may be difficult to keep a consistently trained and talented team in support. If the company is too small, a departure of a key support person can leave a dent in the organization. If the company is too large, the ability to keep a constantly high quality team engaged is challenging. And the more complex the technology is, the more difficult the challenge. Second, the support team for technology suppliers is often called on to go above and beyond. There is a specific patch that needs to be out tonight. Strap in, we are working late. There is a deadline a key customer has involving a high production rollout... so much for those weekend plans. Smaller companies often have an advantage here, as small teams can often be the ones who feel a greater sense of ownership. The people being supported are not "customers using our company's products" they are "our customers" or even "my customers".
Often, but not always, the challenge of the smaller but growing companies is to ensure that they CAN do what needs to be done, and seldom that they are WILLING to do it. The challenge with larger companies is often the reverse. At Infobright it is not uncommon at all to find teams working nights and weekends to help out a customer when the constraints of the agreement allow for far less. As we grow, we are incorporating new processes to allow us to scale and to ensure high quality support when we are three, five, ten times larger than we are today. We have to constantly evaluate our processes and infrastructure to be sure we accommodate our growth. But along the way, we have to very deliberately ensure that our culture will prevent us from evolving into an organization that CAN do many things, but lacks the passion, will, or political support to ACT. We have to stay passionate about our customers' success, and ensure we scale in that context specifically.
And in this light, we are never there, but always on the journey.
All the best,
We are hiring. In fact, we are hiring in a pretty big way. As companies grow and begin to really hit their stride, sometimes the culture of the company gets diminished along the way. Sometimes standards are compromised. We are hiring salespeople, sales engineers, lead development people, and engineers. We go to great lengths to convey our core values: we deal with integrity; we look out for the customer's well-being; we treat each other with respect (albeit with a few lively battles from time to time); we execute with discipline; and we love, love, love machine-generated data because it is changing the world. We are not a cult, but I confess there are a few cult-like qualities. I think that's OK.
The most difficult positions to fill are salespeople. The reason is that there are some who are bad, many who are fair, and very, very few that are truly good. The majority of salespeople, whom I consider to be fair, tend to be somewhat money-driven, sociable, reasonably smart, and reasonably happy. They also tend to be less organized ("I'll wing it"), a tad bit narcissistic, and over time tend to substitute the "value of their years of experience" for good, solid work ethic. Don't get me wrong, I know many people who fit this exact mold, including some who are good friends, but they are not what I consider to be truly good salespeople. They are good people in their own right, but the truly good salespeople are few and far between.
The best salespeople are defined by a clear focus on helping people and companies solve problems. They are less interested in selling a product than they are in finding solutions. They are usually very, very smart. They have an ultra-strong work ethic, and generally start their day very early. They are more apt to be understated than the life of the party. They are not only aware of others around them, but generally bring a sincere concern for others' well-being. They are organized and meticulous. They read people and situations well. And most, while very dedicated and very focused, bring a sense of balance to their work. They proceed in many instances with a sense of purpose and even urgency, but seldom if ever with a sense of panic.
Great companies are built with great people. Of this I am certain. We invest in our team, with constant training and ongoing management support. We don't get everything right, not by a long shot. But I will say that people on our team know they are expected to have a strong work ethic. They know that high integrity is not a negotiable trait. They know that actions speak louder than words. And they know that they all play a part in instilling this very culture into the company so we can grow and scale properly as a result.
And they know that as much as they love machine-generated data today, the advances and progress in the market will have them loving it more tomorrow.
THAT is who we are.
And we are looking for good salespeople who will thrive in that environment.
Interested? Then contact us here.
I spend a great deal of time with our customers. I love hearing their stories of how they use Infobright. Not only does it often intrigue me, but it helps inform the direction of the company. Yesterday I attended the Infobright Customer Advisory Council meeting for precisely that reason. I spend a good amount of time with our new prospects. I love that as well. When with prospects, I usually am hearing about their intentions with us. More and more they are around utilization of Infobright for storing and analyzing machine-generated data. Since this is my favorite topic, I always welcome this conversation. I usually am asked about how we are doing as a company. Since that is an increasingly positive story, I enjoy that all the more. Ask away.
I also really like spending time with our partners, especially those solution providers who embed Infobright in their offerings. This is the fastest growing part of our business. These are customer meetings on steroids, as the discussions generally shine a light on their customer outreach, which is sometimes unbelievable but always helpful and welcomed. And sometimes I have the hard and candid conversations about areas where we need to improve. There will always, always be those areas. All vendors have them, though some either do not admit this or are legitimately in denial. I wish to be neither. While I do love the positive feedback, and I especially love the great anecdotes that provide depth and color to specific use cases I would otherwise miss, what I welcome with open arms is the chance to continually improve.
I think it's important to leverage all the good and positive results you have, but that must always be done in the context of looking at all aspects of the business with an eye to ongoing improvement. For me there is no substitute for a large amount of interaction with customers, prospects, and partners to gain that perspective. That brings me to the turkey. Thanksgiving is a time to, well, be thankful.
I am. I have a great deal to be thankful for. A good family. Good friends. A good job, that keeps getting better, in no small way due to good customers, prospects, and partners.
Now it's time for the turkey. Happy Thanksgiving.
I spent the day today at the AdTech conference in New York. While it is not a mega-conference like Mobile World Congress in Barcelona (55,000 people), it was considerable nonetheless. It filled up a good part of the Javits Center and most of the day the aisles in the exhibition area were packed. What struck me, though, was the incredible buzz. It's one thing to have a big conference where the mood is dour, like the wholesale banking conference Sibos was in Vienna in 2008 in the wake of the banking crisis. But this is on the other extreme. This is an industry on the move. People are happy. People are engaged. People are young and energetic. The conversations you hear are intelligent and often marked by clear excitement. It's, well, really cool.
And because it is, it is also getting really crowded. There are many email marketers, mobile advertisers, online advertisers, and more, and more and more. I am sure each year there will be a noticeable growth in the cottage industry around AdTech, including lawyers, bankers, and of course, technology firms. After all, there is a thin line between an AdTech firm and a technology firm. From an Infobright standpoint, we are a platform supplier. We enable many of these companies to do what they do so well. But today I spent time in particular having discussion after discussion trying to understand what was really driving many of these companies, what was holding them back, and how we could help. What a good use of time. There are three main factors that seem to be almost universal in this market. They are:
These firms all store and analyze loads of machine-generated data. The information that is the fuel for the industry are weblogs, mobile logs, and other auto-generated data that stream in continuously and need to be stored and analyzed easily and quickly. It is common for a firm to store 10, 20, 50 terabytes of data that they must dice and slice with speed and precision. An inability to do this is often a limiting factor for the firm.
These firms run with a lean staff. Going into an AdTech firm is great. They are usually mostly in one big room, and there is almost a trading-room-like buzz to it. The drive, the sense of purpose is palpable. That said, you don't get the idea that the day starts at 9:00, and it certainly doesn't end at 5:00. Moreover, nobody ever seems to be sitting around. When it comes to technology staff, they are all generally lean. Growing the IT staff is not a goal, it is a limitation which, if it can be addressed, is. That doesn't equate to no staff, by any means. It just means no extraneous staff. Very efficient.
Last, money seems to really matter. These all seem to be very capital-efficient organizations. They grow quickly, and the good ones gain value in impressive fashion. But Total Cost of Ownership is not something that needs to be taught in these firms, it comes out everywhere. How IT resources are chosen and deployed reflect a cultural desire to do as much as possible with as little as possible.
There are, of course nuances to every firm. That's why some are more successful than others. And too, the differences track the various permutations in the market. All good. All expected. But the common traits naturally made me think about the success we are having here, and why. My conclusion came easily. Specifically:
These firms all store and analyze loads of machine-generated data. This is what we do, all day, every day. We have unique technology that allows us be an exceptionally compelling offering if this is your need. We are happy to show anyone why this is.
These firms run with a lean staff. We require far less administrative overhead than the alternatives. Really. And not coincidentally, we hear from our AdTech customers all the time that one of the biggest things about us they find appealing is that we don't require a big IT staff.
Last, money seems to really matter. We price fairly. Not expensive, but not "cheap", per se. But we also require far less hardware, and far less administrative overhead. So the combination of licensing, people, and hardware expenses associated with us compared to the alternatives is usually an impressive comparison. We simply offer more for less.
The ethos of this market seems to be all about doing more with less. We find it exciting, and we find that we are a dead-on fit for what most firms in this market want. And that, by extension, has us excited as well.
My father was in advertising from the late 1940's to the late 1990's. When I watch "Mad Men" it basically showcases my life growing up. In the advertising world there was the creative side and the account side. The suits, the hats, the lunches, the "creative guys" were all there. What wasn't there? There were no weblogs or hash tags. The fuel that drove the market was creative ads and martinis. Make no mistake, the creativity is still there, but the mix is now first and foremost creativity and data. The discussion at lunch is less about the third martini than it is the third terabyte. The industry has morphed into a colossal business that thrives on delivering, monitoring, measuring, and calibrating billions of advertisements efficiently and effectively delivered on a mass-personalized basis to your Web browser and, more and more, your mobile device.
This is an industry that thrives on machine-generated data. In the last several weeks I have met with several customers and a number of prospects that are online advertising firms. The online advertising space has a cottage industry that includes the underlying technology to consume the fuel and the mountains of machine-generated data that drive this business. From firms like Bango to TradeDoubler, from adMarketplace.com to Yahoo!, we are providing a purpose-built engine for storing, retrieving,and analyzing this data. Moreover, we do it in an extremely cost-effective manner, where the administrative requirements are negligible, especially compared to most alternatives.
We are adding new online advertising firms as Infobright customers at an accelerating rate. They all want to get up and running quickly, be able to effectively store and analyze terabytes of this data, and do it cost-effectively. We deliver that. No smoke. No martinis. But lots of data.
In the world most of us know, weather forecasts are basically the domain of the TV weather people. They served two, sometimes three purposes. First, they let you know if it is going to rain. Second, they often fill the role of the attractive person in the mix of news people over a half hour period. Last, they provide material for us all to complain about when they are wrong, which we all think is most of the time. More recently, we have begun to also look to sources on the Internet and new mobile apps to get weather information. Fundamentally, all weather predictions come from the same data points, though. They are the various satellites and other deployed instrumentation that services like NOAA and various news agencies and research institutions deploy. That data is then interpreted by weathermen (meteorologists, to be more accurate) and then conveyed on to us in more simple terms, like "bring an umbrella". Easy concept.
Enter the brave new world, where we can all contribute to forecasting by pitching in with the data collection. As new deployed mobile devices bring more and more information to bear, the latest development is the barometer on your phone. Check out the article on the new Android device now being deployed that does this. And as it points out, that opens the door for new weather-related applications that collect and distill this information into forecasts that are ostensibly the beneficiary of many, many more collection points resulting in (hopefully) more accurate forecasts.
We love that for several reasons. First, it is furthering the progress of the new world of technology which reaches into both new and old avenues in compelling new ways impacting all walks of life. Second, and more specific to us at Infobright, it underscores the vast explosion of machine-generated data. Vast. That's what we do and we do it very, very well. And last, we do it because we would like to know when and when not to bring along an umbrella.
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