Why read this book?
Who is the audience?
What is the value?
If you are thinking I'm trying to sell you a book, hang on for just a minute. What I would like to do here is to share a recent experience of an exceptional review of a technical book, or specifically, review of Rob Farber’s CUDA Application Design and Development by Chris Jang.
At the monthly HPC & GPU Supercomputing Group of Silicon Valley Meetup, book reviews are a regular occurrence, and are always placed at the end of the meeting. This tradition started a year ago when NVIDIA gave away two GPU Computing Gems books to the first two volunteers committed to review at least one Chapter in the book and share their learning with the group.
With participants often excitedly talking over pizza and asking question after question to the invited speakers, the meetings always seem to run out of time for book review talks at the end. Thanks to NVIDIA for regular contributions of GPU Computing Gems books, and a continuous flow of volunteer speakers, even with the end-of-meeting rush, reviews of about a dozen chapters have been shared at the meetups thus far.
To clarify, book reviews may sound academic, and it often is the more academic part of the meetings, the materials are mostly based on use cases and have practical examples. For that, most everyone sticks around and maximizes intake of learning at each meeting.
At the Monday April 23rd meetup, the book review was different: granted it was a different book, the review style, content and delivery all stood out. Chris started with the Why-Who-What questions, then shared his observations of three cultures in CUDA Application Design and Development: CUDA technology platform, stream processing on the GPU, and Machine learning, before diving into Acts and Themes, or his way of speaking about different parts of the book.
With this delivery of a comprehensive and fun review, those at the meetup learned that while the book is the whole world of CUDA in one place, it may not serve as a how-to guide, and while the book is helpful to those making technology choices, the various technology cultures may be confusing. The slides are here for those interested.
As this distinct book review talk closed the April meetup on a high note, Jike Chong, the meetup organizer, reminded everyone of the GTC Special meetup on May 15 that is co-located with the GPU Technology Conference. Instead of technical talks, this meetup will feature experience to help Start Your HPC and GPU Supercomputing Meetup Group, followed by What You Always Wanted to Know About GPUs, a Game Show with Raffles!
Since GPU enthusiasts from all over the United States (and even internationally) will be present for the GTC, this meetup will be a great opportunity for people to meet and learn! We also received a tip from a reliable source that there will be a well-known special surprise guest attending! You'll just have to sign up, show up and find out. Seats are filling up fast, so hurry!
Thursday, May 03, 2012
Wednesday, February 29, 2012
Big Data vs. Big Compute, Two Sides of the Same Coin?
With Big Data designated as the next frontier for innovation, competition, and productivity by McKinsey, and Gartner selecting it as one of the top 10 strategic technologies for 2012, Big Data is everywhere in the media, and on top of people’s minds. But are Big Data technologies sufficient in addressing “big data” problems? What about the compute-intensive applications that involve processing significant amounts of data? The Silicon Valley HPC/GPU Supercomputing Meetup Group decided to bring the two topics together for a discussion.
“It wasn't what I expected, which turned out to be a good thing.” Commented by an attendee of the recent panel discussion and debate on similarities and differences of Big Data vs. Big Compute. When multiple reviews on the event run over 150 words each, it is clear that the event had struck a chord, and perhaps, invoked some controversy.
Big Data and Big Compute, specifically using GPUs in this case, are not new concepts. Big Data usually refers to datasets too large for database management tools, and GPU computing leverages the parallel nature of graphics processing unit to perform computation in applications traditionally handled by the CPU.
The Meetup organizer and panel moderator, Dr. Jike Chong, offered several interpretations of Big Data and Big Compute from speaking with the four panelists with diverse backgrounds: constraint-based, relative, scalability and historic. The discussion quickly heated up:
Is Big Data vs. Big Compute a wallet problem in an economic context? Depends. Do we know which data is valuable prior to computation taking place?
What are the differences in priority? For big data, it tends to be to explore things rapidly, where as for big compute, there is more focus on optimization and fine tuning of the hardware.
While the focuses of the two approaches appear to be different, both are concerned with throughput. Some may say these are two different ways of solving the same problem, and others (myself included) advocate these to work together to solve big data compute intensive problems.
Steve Scott, NVIDIA Tesla CTO, one of the panelists, puts it well with a summary on GPUs for Big Data:
If it is all data movement, there’s no need for GPU or CPU.
If there’s some serious computing that needs to be done on that data and the problem can be distributed, GPU can help allow more complex analysis.
If the problem has no locality such as in big graph analytics, GPUs may work well in the future.
So where is the convergence and what are the implications? Lots of big compute problem are also big data: reverse time migration in oil and gas, visual search for example. It also turns out a very critical thing for both is power: how do we get less power per productivity? Both Big Data and Big Compute have to optimize, and will be driving that effort in the next five years.
Big Data and Big Compute are not opposing concepts, and the discussion revealed there is more than a perspective, application, or priority difference, there is underlying culture difference of the two camps using these approaches. Going forward, Big data, as “marriage of ‘database’ with compute”, and Big Compute need to take the other side into consideration, as technologies for each can shine where their priorities and interests aligns.
More information can be accessed at the links to slides.
The four panelists come from diverse backgrounds, and both Aaron Kimball and Tim Child had presented to the group prior:
Aaron Kimball, co-founder of WibiData
Steve Scott, Tesla CTO, NVIDIA
Tim Kaldewey, IBM research
Tim Child, Chief Entrepeneur Officer at 3DMashup
Description of Aaron Kimball's talk, Large Scale Machine Learning on Hadoop and HBase, is here, and Tim Child's talk on Postgres is here and was also mentioned here.
Join us next time on March 26 for another exciting discussion in HPC and GPU Supercomputing!
“It wasn't what I expected, which turned out to be a good thing.” Commented by an attendee of the recent panel discussion and debate on similarities and differences of Big Data vs. Big Compute. When multiple reviews on the event run over 150 words each, it is clear that the event had struck a chord, and perhaps, invoked some controversy.
Big Data and Big Compute, specifically using GPUs in this case, are not new concepts. Big Data usually refers to datasets too large for database management tools, and GPU computing leverages the parallel nature of graphics processing unit to perform computation in applications traditionally handled by the CPU.
The Meetup organizer and panel moderator, Dr. Jike Chong, offered several interpretations of Big Data and Big Compute from speaking with the four panelists with diverse backgrounds: constraint-based, relative, scalability and historic. The discussion quickly heated up:
Is Big Data vs. Big Compute a wallet problem in an economic context? Depends. Do we know which data is valuable prior to computation taking place?
What are the differences in priority? For big data, it tends to be to explore things rapidly, where as for big compute, there is more focus on optimization and fine tuning of the hardware.
While the focuses of the two approaches appear to be different, both are concerned with throughput. Some may say these are two different ways of solving the same problem, and others (myself included) advocate these to work together to solve big data compute intensive problems.
Steve Scott, NVIDIA Tesla CTO, one of the panelists, puts it well with a summary on GPUs for Big Data:
If it is all data movement, there’s no need for GPU or CPU.
If there’s some serious computing that needs to be done on that data and the problem can be distributed, GPU can help allow more complex analysis.
If the problem has no locality such as in big graph analytics, GPUs may work well in the future.
So where is the convergence and what are the implications? Lots of big compute problem are also big data: reverse time migration in oil and gas, visual search for example. It also turns out a very critical thing for both is power: how do we get less power per productivity? Both Big Data and Big Compute have to optimize, and will be driving that effort in the next five years.
Big Data and Big Compute are not opposing concepts, and the discussion revealed there is more than a perspective, application, or priority difference, there is underlying culture difference of the two camps using these approaches. Going forward, Big data, as “marriage of ‘database’ with compute”, and Big Compute need to take the other side into consideration, as technologies for each can shine where their priorities and interests aligns.
More information can be accessed at the links to slides.
The four panelists come from diverse backgrounds, and both Aaron Kimball and Tim Child had presented to the group prior:
Aaron Kimball, co-founder of WibiData
Steve Scott, Tesla CTO, NVIDIA
Tim Kaldewey, IBM research
Tim Child, Chief Entrepeneur Officer at 3DMashup
Description of Aaron Kimball's talk, Large Scale Machine Learning on Hadoop and HBase, is here, and Tim Child's talk on Postgres is here and was also mentioned here.
Join us next time on March 26 for another exciting discussion in HPC and GPU Supercomputing!
Sunday, January 01, 2012
Will data analytics be bigger and hotter in 2012? You bet!
While Datameer has been focusing on continuing to deliver end-to-end business intelligence platform on Hadoop, there's been a lot of increased interest in (big) data analytics in the rest of the world. This both validates the market potential and creates challenges for other business aspects. Let's take a look at a few examples:
1). Analytics is dubbed by Inc magazine as one of five most competitive areas for talent, which means data analyst and data scientist roles will continue to be some of the hardest jobs to fill in 2012
Analytics is the science of analysis, and it is the application of computer technology, operational research, and statistics to solve problems in business and industry.
As data becomes more accessible, more decisions are made with insights from the data. "Analytics is becoming a central hub across companies where everything (web, marketing, sales, operations) is being measured and each decision is supported by data."
Analytics professionals are in higher demand than ever: Monica Rogati, a founding member of the data science team at LinkedIn, shared at the Strata Conference a graph of analytics and data science job growth, that is exponential in nature, even when properly normalized.
2). Enterprises are putting more emphasis on data analytics, as they seek to better understand their customers' behaviors.
The benefits are easy to see: “Data analysis will drive Intel's future", "EBay acquires data analysis firm Hunch to boost recommendations", "Visa Europe invests in Beyond Analysis for data analytics". Intel, EBay, Visa, and other companies sit on massive data sets, which can be a very rich source for them to better understand patterns and behaviors, and serve as a basis for predictive analysis.
Companies are working on creating a more intuitive and pleasant user and customer experience, which means they must effectively correlate purchasing and consumption patterns (often structured data) and sentiments around the purchases such as social media comments and response to certain interfaces (often unstructured data).
"Analyzing the sheer volume of transactional data is no small task. It could be very easy to get lost and drown in it all" says an EBay executive. Analyzing unstructured behavior to understand and predict behavior is even more challenging.
3). The significance of analytics is showing up more in entertainment and politics, signifying increased popularity as well as the introduction of the field to the general public.
*CNN’s article “How Obama's data-crunching prowess may get him re-elected”
discusses how the Obama campaign is taking data analytics seriously, as predictive modeling/data mining and data-crunching may not just give an edge, but may make the winning difference in a tight race. With 23 million Facebook likes, and 10 million twitter followers, the Obama data crew may know and learn a lot about these “fans”, cater to them, and win their votes.
*In the movie Moneyball, Oakland Athletics GM Billy Beane turned the baseball industry upside down by “using objectivity and data to help pick a baseball team” rather than trusting on gut feels of “experts”. Beane was able to manage the Oakland As to accomplish 5th best regular-season record with player salaries at 24th of 30, using sabermetric principles to run the team cost-effectively.
*The CBS series “Person of Interest” where an ex-CIA hitman partners with a scientist to prevent crimes before they occur by collecting and analyzing data. Unlike the previous two examples, which are from or based on real life, this series exposes the importance of data analytics to solving crimes to the general audience.
What these have in common is data and analytics are becoming popular with non-traditional high-tech, finance, retail industries, as people find easier ways to correlate different types of data, whether structured and unstructured. In doing so, they can answer important and interesting questions that they could not have before to solve real problems: what algorithms can I use to find the best talent? Has there been a rogue trader in house? Which store should be closed and which should be expanded to achieve the best revenue?
These three examples feed off of each other: as more emphasis on analytics drives a higher demand of talent in that field, more activities take place in the media, entertainment, and even politics.
Being able to perform data analytics is one thing, successfully implementing analytics-based strategies is another. I learned from “Money ball” that: 1). Billy Beane and Peter Brand's carefully laid out strategy didn't work when not executed by Art Howe, the Oakland field manager, so Billy had to eliminate some possibilities for Art by trading some players away to "force" Art to follow the strategy on the field. 2). Data analytics and statistics didn't help in finding the help needed and aligning incentives: analytics can detect trends in historic information, but is limited when looking at team dynamics in terms of the team's "state" when winning and when losing.
Luckily as data is collected for the implementation stage, there would be an opportunity to use analytics to identify the issues, and form a solution for the new problem. I consider the examples above indicators that data analytics are getting "even bigger, hotter in 2012", and companies better be armed with the right tool to face this reality… and yes, Datameer can help.
1). Analytics is dubbed by Inc magazine as one of five most competitive areas for talent, which means data analyst and data scientist roles will continue to be some of the hardest jobs to fill in 2012
Analytics is the science of analysis, and it is the application of computer technology, operational research, and statistics to solve problems in business and industry.
As data becomes more accessible, more decisions are made with insights from the data. "Analytics is becoming a central hub across companies where everything (web, marketing, sales, operations) is being measured and each decision is supported by data."
Analytics professionals are in higher demand than ever: Monica Rogati, a founding member of the data science team at LinkedIn, shared at the Strata Conference a graph of analytics and data science job growth, that is exponential in nature, even when properly normalized.
2). Enterprises are putting more emphasis on data analytics, as they seek to better understand their customers' behaviors.
The benefits are easy to see: “Data analysis will drive Intel's future", "EBay acquires data analysis firm Hunch to boost recommendations", "Visa Europe invests in Beyond Analysis for data analytics". Intel, EBay, Visa, and other companies sit on massive data sets, which can be a very rich source for them to better understand patterns and behaviors, and serve as a basis for predictive analysis.
Companies are working on creating a more intuitive and pleasant user and customer experience, which means they must effectively correlate purchasing and consumption patterns (often structured data) and sentiments around the purchases such as social media comments and response to certain interfaces (often unstructured data).
"Analyzing the sheer volume of transactional data is no small task. It could be very easy to get lost and drown in it all" says an EBay executive. Analyzing unstructured behavior to understand and predict behavior is even more challenging.
3). The significance of analytics is showing up more in entertainment and politics, signifying increased popularity as well as the introduction of the field to the general public.
*CNN’s article “How Obama's data-crunching prowess may get him re-elected”
discusses how the Obama campaign is taking data analytics seriously, as predictive modeling/data mining and data-crunching may not just give an edge, but may make the winning difference in a tight race. With 23 million Facebook likes, and 10 million twitter followers, the Obama data crew may know and learn a lot about these “fans”, cater to them, and win their votes.
*In the movie Moneyball, Oakland Athletics GM Billy Beane turned the baseball industry upside down by “using objectivity and data to help pick a baseball team” rather than trusting on gut feels of “experts”. Beane was able to manage the Oakland As to accomplish 5th best regular-season record with player salaries at 24th of 30, using sabermetric principles to run the team cost-effectively.
*The CBS series “Person of Interest” where an ex-CIA hitman partners with a scientist to prevent crimes before they occur by collecting and analyzing data. Unlike the previous two examples, which are from or based on real life, this series exposes the importance of data analytics to solving crimes to the general audience.
What these have in common is data and analytics are becoming popular with non-traditional high-tech, finance, retail industries, as people find easier ways to correlate different types of data, whether structured and unstructured. In doing so, they can answer important and interesting questions that they could not have before to solve real problems: what algorithms can I use to find the best talent? Has there been a rogue trader in house? Which store should be closed and which should be expanded to achieve the best revenue?
These three examples feed off of each other: as more emphasis on analytics drives a higher demand of talent in that field, more activities take place in the media, entertainment, and even politics.
Being able to perform data analytics is one thing, successfully implementing analytics-based strategies is another. I learned from “Money ball” that: 1). Billy Beane and Peter Brand's carefully laid out strategy didn't work when not executed by Art Howe, the Oakland field manager, so Billy had to eliminate some possibilities for Art by trading some players away to "force" Art to follow the strategy on the field. 2). Data analytics and statistics didn't help in finding the help needed and aligning incentives: analytics can detect trends in historic information, but is limited when looking at team dynamics in terms of the team's "state" when winning and when losing.
Luckily as data is collected for the implementation stage, there would be an opportunity to use analytics to identify the issues, and form a solution for the new problem. I consider the examples above indicators that data analytics are getting "even bigger, hotter in 2012", and companies better be armed with the right tool to face this reality… and yes, Datameer can help.
Sunday, November 13, 2011
Wrong Place at the Wrong Time...
Exactly a week ago, I was at the wrong place at the wrong time (intersection car accident in NYC).
It was near the JFK airport in NY, I had just finished facilitating a workshop at Stony Brook, and got a suggestion for dinner from the hotel concierge.
The expressway north heading toward Flushing was slow to a crawl, so I exited and filled up the tank, then was ready to re-enter the expressway.
Sitting in the middle lane waiting for the green light at the intersection of the Van Wyck Expressway (687 north) entrance and Hillside, I was content: it's ~6pm on Sunday in NYC and the weather is cooperating, I might even get a little work done and get to sleep early after dinner!
The green light came, and cars in the lanes to my left and right started moving. I put my foot lightly on the gas pedal. Then in my peripheral vision, I saw a car coming from the right and thought "huh? is this possible?" and within that second, I felt the impact of being hit somewhere in the front of the car. Within the next few seconds, my car spun to the left 90 degrees toward the bridge, while the other car spun 180 degrees, returning to hit my car's left and driver side. My car was getting dangerously close to the concrete pole and the voice in my head kept repeating: "don't hit the pole, don't hit the pole!"
Things appeared to be happening in slow motion as I saw my life flashing by and thought:"I'm going to die". When the cars stopped moving, I returned to reality. I moved my feet, my arms, my legs and my head, everything appears to follow command.
At this time, a man was speaking to me outside of the car: "Are you okay? Get out, your car is leaking, it may blow up!" Well, my driver door is molded to the other car's driver door (with all the turns, the other car is now pointing to the opposite side of its original direction of traveling, while my car was 90 degrees off from the original course), and the passenger door is less than a foot from the concrete pole I was desperately avoiding. I yelled back:"I can't! I'm stuck." "Climb out of the back!"
My knee was hurting and I was shaking all over. The same man walked up to the driver of the other car, and said "What were you doing? she had the green, I was behind her."
Long story short, after informing the appropriate authorities, waiting for the police, and getting the car ready for towing, taking a taxi to JFK, and getting a replacement rental car (thank you, Hertz, for making things easy, I've been and will continue to be a loyal customer), I was exhausted, hungry and phone battery was drained.
Shortly after 10pm when I finally walked into the hotel lobby after dinner, I was greeted by the lady at the front desk saying urgently:"Your husband has been trying to reach you, please call him back."
"They can't find the car that needs to be towed, it may be impounded or stolen."
Is this really happening? Do I really need to file two police reports within three hours? I caught myself from self pity and dialed 911 again.
Life happens, and you just have to deal with it.
Close to 11pm, I got a call of relief while still with 311 on the phone: "AAA located the vehicle."
I relaxed and tears started flowing down my cheeks. Through this ordeal, I had forgotten to nurse my sore knee and pay attention to what else that may need attention.
I have often had the luck or planned to be at the right place at the right time, to capture opportunities to advance or to help others. Being jerked into life's realities gives me different perspectives:
- You can do a lot of planning but sometimes things just happen outside of your control.
- I need to treasure each day and live it to the fullest so I don't have regrets if things do happen
- If I am a witness to an accident (or something else) I will also provide my account of the event (which I hope the man driving the vehicle behind mine would come around and do so), as the parties involved may not be able to fully account what has happened
- I have a new appreciation for the work processes and compassion of emergency workers: it helps to hear words of comfort: are you safe? do you need medical attention? Have you contacted family?
With Thanksgiving coming up, I'm especially thankful to be around friends and family, having come out of that accident with these new perspectives.
It was near the JFK airport in NY, I had just finished facilitating a workshop at Stony Brook, and got a suggestion for dinner from the hotel concierge.
The expressway north heading toward Flushing was slow to a crawl, so I exited and filled up the tank, then was ready to re-enter the expressway.
Sitting in the middle lane waiting for the green light at the intersection of the Van Wyck Expressway (687 north) entrance and Hillside, I was content: it's ~6pm on Sunday in NYC and the weather is cooperating, I might even get a little work done and get to sleep early after dinner!
The green light came, and cars in the lanes to my left and right started moving. I put my foot lightly on the gas pedal. Then in my peripheral vision, I saw a car coming from the right and thought "huh? is this possible?" and within that second, I felt the impact of being hit somewhere in the front of the car. Within the next few seconds, my car spun to the left 90 degrees toward the bridge, while the other car spun 180 degrees, returning to hit my car's left and driver side. My car was getting dangerously close to the concrete pole and the voice in my head kept repeating: "don't hit the pole, don't hit the pole!"
Things appeared to be happening in slow motion as I saw my life flashing by and thought:"I'm going to die". When the cars stopped moving, I returned to reality. I moved my feet, my arms, my legs and my head, everything appears to follow command.
At this time, a man was speaking to me outside of the car: "Are you okay? Get out, your car is leaking, it may blow up!" Well, my driver door is molded to the other car's driver door (with all the turns, the other car is now pointing to the opposite side of its original direction of traveling, while my car was 90 degrees off from the original course), and the passenger door is less than a foot from the concrete pole I was desperately avoiding. I yelled back:"I can't! I'm stuck." "Climb out of the back!"
My knee was hurting and I was shaking all over. The same man walked up to the driver of the other car, and said "What were you doing? she had the green, I was behind her."
Long story short, after informing the appropriate authorities, waiting for the police, and getting the car ready for towing, taking a taxi to JFK, and getting a replacement rental car (thank you, Hertz, for making things easy, I've been and will continue to be a loyal customer), I was exhausted, hungry and phone battery was drained.
Shortly after 10pm when I finally walked into the hotel lobby after dinner, I was greeted by the lady at the front desk saying urgently:"Your husband has been trying to reach you, please call him back."
"They can't find the car that needs to be towed, it may be impounded or stolen."
Is this really happening? Do I really need to file two police reports within three hours? I caught myself from self pity and dialed 911 again.
Life happens, and you just have to deal with it.
Close to 11pm, I got a call of relief while still with 311 on the phone: "AAA located the vehicle."
I relaxed and tears started flowing down my cheeks. Through this ordeal, I had forgotten to nurse my sore knee and pay attention to what else that may need attention.
I have often had the luck or planned to be at the right place at the right time, to capture opportunities to advance or to help others. Being jerked into life's realities gives me different perspectives:
- You can do a lot of planning but sometimes things just happen outside of your control.
- I need to treasure each day and live it to the fullest so I don't have regrets if things do happen
- If I am a witness to an accident (or something else) I will also provide my account of the event (which I hope the man driving the vehicle behind mine would come around and do so), as the parties involved may not be able to fully account what has happened
- I have a new appreciation for the work processes and compassion of emergency workers: it helps to hear words of comfort: are you safe? do you need medical attention? Have you contacted family?
With Thanksgiving coming up, I'm especially thankful to be around friends and family, having come out of that accident with these new perspectives.
Tuesday, September 06, 2011
When GPU Computing meets Advanced Analytics
In August the HPC/GPU Supercomputing Meetup Group featured a talk that generated much interest in both the GPU and the advanced analytics communities.
As an effort to expand readership, I posted the blog at NVIDIA's blog site as a guest author. Thanks to Will Park of NVIDIA for his help and suggestions.
We would love to hear your experience using GPUs to accelerate analytics: What are the challenges and how did you overcome them? How viable do you find GPUs accelerating advanced analytics? How much of the BI analytics market can GPU effectively address?
About the HPC/GPU Supercomputing Meetup Group:
As this is just one of many stimulating talks and discussions at this Meetup group, here is some background: Dr. Jike Chong initiated the Silicon Valley group in February this year, the group has attracted 200+ members, many of them pioneer parallel software practitioners who are passionate about high performance computing and GPU supercomputing. If you find topics in these areas interesting, join the discussions on Monday September 12!
As an effort to expand readership, I posted the blog at NVIDIA's blog site as a guest author. Thanks to Will Park of NVIDIA for his help and suggestions.
We would love to hear your experience using GPUs to accelerate analytics: What are the challenges and how did you overcome them? How viable do you find GPUs accelerating advanced analytics? How much of the BI analytics market can GPU effectively address?
About the HPC/GPU Supercomputing Meetup Group:
As this is just one of many stimulating talks and discussions at this Meetup group, here is some background: Dr. Jike Chong initiated the Silicon Valley group in February this year, the group has attracted 200+ members, many of them pioneer parallel software practitioners who are passionate about high performance computing and GPU supercomputing. If you find topics in these areas interesting, join the discussions on Monday September 12!
Monday, August 08, 2011
Top 10 Mistakes in Demo Pitch (by Demo Coach Nathan Gold)
This can be quite useful as Plug and Play Startups gear up for their pitches to VCs (go Krowder!). Thanks to Nathan Gold for sharing at http://democoach.com/
1. Weak opening
2. Slides abuse (don't ever use dense slides)
3. Similarity & analogy metaphors
4. Power thieves (use pauses)
5. Clickfest demo (TMI/long/deep... count the # of clicks)
6. Terrible online ettiquette
7. lack of enthusiasm
8. Cultural unawareness
9. poor Q&A
10. Toooo many slides
Many of these may sound trivial, but it's easier said than done.
Earlier this summer, I started working with the guys who started Krowder, an early stage startup that is building a community supported delivery platform revolutionizing the way packages will be picked up and delivered locally by taking advantage of the economies of crowd-sourcing.
As demo day approaches, we need to get our audience excited about what we are excited about, in a mere few minutes. We'll have to have a good story, keep it very short, show a killer demo, and close with a call-to-action that flood people our way.
One of my all time favorite quotes is "If I have to make a two-hour speech, I can prepare it in 10 minutes. If it is a 10-minute speech, then it can take me two hours." (Winston Churchill). Let the preparation begin!
1. Weak opening
2. Slides abuse (don't ever use dense slides)
3. Similarity & analogy metaphors
4. Power thieves (use pauses)
5. Clickfest demo (TMI/long/deep... count the # of clicks)
6. Terrible online ettiquette
7. lack of enthusiasm
8. Cultural unawareness
9. poor Q&A
10. Toooo many slides
Many of these may sound trivial, but it's easier said than done.
Earlier this summer, I started working with the guys who started Krowder, an early stage startup that is building a community supported delivery platform revolutionizing the way packages will be picked up and delivered locally by taking advantage of the economies of crowd-sourcing.
As demo day approaches, we need to get our audience excited about what we are excited about, in a mere few minutes. We'll have to have a good story, keep it very short, show a killer demo, and close with a call-to-action that flood people our way.
One of my all time favorite quotes is "If I have to make a two-hour speech, I can prepare it in 10 minutes. If it is a 10-minute speech, then it can take me two hours." (Winston Churchill). Let the preparation begin!
Sunday, June 26, 2011
Market Validation
In this and the next few entries, I will share some learning from a series of startup workshops. I will start with marketing sizing and segmentation.
Imagine a VC sees 2000+ business plans a year, schedules 200+ meetings, puts ~20 term sheets together, and closes <10 deals, there is no question that the first meeting is very important. One of the things to do well to stand out in that first encounter is to show that you've carefully thought through your addressable market, and that big markets with high growth rates are in the horizon.
There are six areas to consider, six T's:
Theme: what is the product you are selling (e.g. independent third party verification for ads)?
Team: who are in the founding team (two or three people, their perseverance, domain expertise)? VCs like opportunity and shy away from risks. The more experienced the team is, the clearer the market, the better. Experienced teams plan for the what Ifs? They perform SWOT analysis. A players hire A players and people they trust. Trust among team members is very important.
Terrain: what is the total available market and the addressable market? The first second and third players in the market get most of the shares, about 65%. Where are you going to be?
Timing: Is the market too early too late?
Technology: How will your technology work?
Terms: What is the right exchange for a part of the company? What can the VC firm contribute with beyond money?
Market estimations:
Bottom up: Start with a user, see how much that customer would pay after year one.
Top down: Look at the size of your market.
Next time, a few different paths around making money.
In this and the next few entries, I will share some learning from a series of startup workshops. I will start with marketing sizing and segmentation.
Imagine a VC sees 2000+ business plans a year, schedules 200+ meetings, puts ~20 term sheets together, and closes <10 deals, there is no question that the first meeting is very important. One of the things to do well to stand out in that first encounter is to show that you've carefully thought through your addressable market, and that big markets with high growth rates are in the horizon.
There are six areas to consider, six T's:
Theme: what is the product you are selling (e.g. independent third party verification for ads)?
Team: who are in the founding team (two or three people, their perseverance, domain expertise)? VCs like opportunity and shy away from risks. The more experienced the team is, the clearer the market, the better. Experienced teams plan for the what Ifs? They perform SWOT analysis. A players hire A players and people they trust. Trust among team members is very important.
Terrain: what is the total available market and the addressable market? The first second and third players in the market get most of the shares, about 65%. Where are you going to be?
Timing: Is the market too early too late?
Technology: How will your technology work?
Terms: What is the right exchange for a part of the company? What can the VC firm contribute with beyond money?
Market estimations:
Bottom up: Start with a user, see how much that customer would pay after year one.
Top down: Look at the size of your market.
Next time, a few different paths around making money.
Monday, May 16, 2011
The World of Startup Equity
Startups are hot, and those looking to join startups should be aware of a few things. Thanks to a couple of friends who are startup veterans / serial entrepreneurs for sharing their experience:
First read up on the basics of startup equity for employees.
Next with the knowledge of the startup's current funding position, assess how the options may get affected with another funding event, and get a copy of the perspective company's stock option plan to review, if you can.
Next read up on 83b election and how that you should organize your decisions around vesting schedules.
Finally be aware of different clauses and events so no big surprises take place. Ask the startup founders/executives questions. Experienced founders/executives are often open about the share info and the valuation. It may be a red flag when they are not willing to divulge that information.
Startups are hot, and those looking to join startups should be aware of a few things. Thanks to a couple of friends who are startup veterans / serial entrepreneurs for sharing their experience:
First read up on the basics of startup equity for employees.
Next with the knowledge of the startup's current funding position, assess how the options may get affected with another funding event, and get a copy of the perspective company's stock option plan to review, if you can.
Next read up on 83b election and how that you should organize your decisions around vesting schedules.
Finally be aware of different clauses and events so no big surprises take place. Ask the startup founders/executives questions. Experienced founders/executives are often open about the share info and the valuation. It may be a red flag when they are not willing to divulge that information.
Wednesday, April 27, 2011
Much to Learn from a Marketing Analogy
Being in the technology space, I've seen my share of solutions marketing messaging. A recent visit to Pragmatic Marketing webpage shed some light on why technology-based companies' approach to marketing might not be working:
Instead of a tech firm, let's say they were KFC, the message might look like this: "Would you like to buy some packaged dead chicken parts? We’re an end-to-end solution for the killing, chopping, freezing, cooking, and packaging of chicken.”
Does your companies do this?
Ever wonder why your prospects are bored by your messaging?
This certainly gets me thinking about how I market Parasians...
Being in the technology space, I've seen my share of solutions marketing messaging. A recent visit to Pragmatic Marketing webpage shed some light on why technology-based companies' approach to marketing might not be working:
Instead of a tech firm, let's say they were KFC, the message might look like this: "Would you like to buy some packaged dead chicken parts? We’re an end-to-end solution for the killing, chopping, freezing, cooking, and packaging of chicken.”
Does your companies do this?
Ever wonder why your prospects are bored by your messaging?
This certainly gets me thinking about how I market Parasians...
Wednesday, March 02, 2011
Parallel, Concurrent, and/or Distributed Computing?
First there's a bit of confusion (or lack of clarity) in the computing space with the terms "concurrent computing", "parallel computing", and "distributed computing". They do overlap, and there are some distinctions.
Concurrent computing describes the process with which multiple workloads get operated on at the same time. For example, your computer maybe burning a DVD, browsing the web and doing virus checking at the same time. All these workloads are running concurrently - making visible progress from the user's perspective during any given second. But underneath, the workload may be time multiplexing sequentially on the same core in the same processor in the same system, or running on multiple cores or multiple processors or multiple systems at the same time.
Parallel computing is a subset of concurrent computing, where the multiple workloads really are operating on different hardware resources at the same time. The different resources could be different cores or different processors or different systems.
Distributed computing is a subset of parallel computing where the execution takes place on computer systems that are distributed. This is usually motivated by the distributed nature of the location of data, where the computation can take place close to where data is located.
Why should we care about the similarities and differences?
Highly parallel processors such as the modern GPUs are providing the same general-purpose computation capabilities to run business-critical applications at only 1/20th the power and 1/10th the cost.
Development environments for parallel computing have become more accessible. For example, development environments for the GPUs (CUDA and OpenCL) are based on the C/C++ development environment, which allows GPUs’ computational capabilities to be easily accessed by those seeking acceleration solutions for compute-intensive applications.
Distributed computing is easier with availability of Linux and Hadoop, both excellent examples of free and open source software collaboration. Hadoop, a software framework, enables reliable, efficient, and scalable distributed manipulation of large amounts of data (think in TBs and PBs). Hadoop runs well on Linux as a production platform, which can be widely installed on commodity hardware.
The increased capabilities, flexibility, and accessibility of GPUs and Hadoop are fueling the next level parallel and distributed computing innovations to solve compute intensive and/or data intensive problems faced with both increasing throughput and reducing latency requirements.
What new opportunities do you see?
First there's a bit of confusion (or lack of clarity) in the computing space with the terms "concurrent computing", "parallel computing", and "distributed computing". They do overlap, and there are some distinctions.
Concurrent computing describes the process with which multiple workloads get operated on at the same time. For example, your computer maybe burning a DVD, browsing the web and doing virus checking at the same time. All these workloads are running concurrently - making visible progress from the user's perspective during any given second. But underneath, the workload may be time multiplexing sequentially on the same core in the same processor in the same system, or running on multiple cores or multiple processors or multiple systems at the same time.
Parallel computing is a subset of concurrent computing, where the multiple workloads really are operating on different hardware resources at the same time. The different resources could be different cores or different processors or different systems.
Distributed computing is a subset of parallel computing where the execution takes place on computer systems that are distributed. This is usually motivated by the distributed nature of the location of data, where the computation can take place close to where data is located.
Why should we care about the similarities and differences?
Highly parallel processors such as the modern GPUs are providing the same general-purpose computation capabilities to run business-critical applications at only 1/20th the power and 1/10th the cost.
Development environments for parallel computing have become more accessible. For example, development environments for the GPUs (CUDA and OpenCL) are based on the C/C++ development environment, which allows GPUs’ computational capabilities to be easily accessed by those seeking acceleration solutions for compute-intensive applications.
Distributed computing is easier with availability of Linux and Hadoop, both excellent examples of free and open source software collaboration. Hadoop, a software framework, enables reliable, efficient, and scalable distributed manipulation of large amounts of data (think in TBs and PBs). Hadoop runs well on Linux as a production platform, which can be widely installed on commodity hardware.
The increased capabilities, flexibility, and accessibility of GPUs and Hadoop are fueling the next level parallel and distributed computing innovations to solve compute intensive and/or data intensive problems faced with both increasing throughput and reducing latency requirements.
What new opportunities do you see?
Tuesday, February 08, 2011
Creating Value from Social Media – Captive Reach from Friends of Parallel6
If you are interested in a new way of using social media and mobile technologies to create value, read on…
Imagine a scenario where a family walks into San Francisco Centre, receives a welcome message and a promo for Gymboree on mom, dad and junior's mobile phones. This event then leads them to purchase, and a sharing incentive in a reward point structure motivates them to share with friends… and more sales take place.
Welcome/promo -> purchase -> share -> friends purchase -> friends share…
As of 3pm PDT, 1/24, Gymboree had 176,862 connections on Facebook, and 6349 followers on Twitter.
If only Gymboree could break into the second degree of their fans' connections (1:200), that would be reaching 35,372,400(!) more people on Facebook alone.
What if Gymboree stores can target shoppers in the vicinity, to welcome, remind, and perhaps incent them to stop by and make a purchase?
...
I’m not a social media super user myself, but the patent-pending Captive Reach Rewards technology with Geo Location that powers this is pretty cool stuff. Social Media is (still) hot, but there aren’t a lot of real innovation that create value with it for organizations.
If you are in retail/hotel/golf or other industries with some kind of member-based structure looking to grow business with the help of social media, take a look at this on parallel6.com. This file gives a good idea of the power of this technology, but is no where close to their demo, which shows (in real time) so many opportunities for businesses to reach their “fans” and friends when they are in the market!
I've now known David, the CEO of Parallel6, for several years, and this is one of the most (if not the most) exciting offer he and his team have created. This technology not only turns fans to ambassadors while getting businesses to generate more revenue, it also turns friends to ambassadors: I'd be happy to make introduction for you and Parallel6 if this can help your business grow.
If you are interested in a new way of using social media and mobile technologies to create value, read on…
Imagine a scenario where a family walks into San Francisco Centre, receives a welcome message and a promo for Gymboree on mom, dad and junior's mobile phones. This event then leads them to purchase, and a sharing incentive in a reward point structure motivates them to share with friends… and more sales take place.
Welcome/promo -> purchase -> share -> friends purchase -> friends share…
As of 3pm PDT, 1/24, Gymboree had 176,862 connections on Facebook, and 6349 followers on Twitter.
If only Gymboree could break into the second degree of their fans' connections (1:200), that would be reaching 35,372,400(!) more people on Facebook alone.
What if Gymboree stores can target shoppers in the vicinity, to welcome, remind, and perhaps incent them to stop by and make a purchase?
...
I’m not a social media super user myself, but the patent-pending Captive Reach Rewards technology with Geo Location that powers this is pretty cool stuff. Social Media is (still) hot, but there aren’t a lot of real innovation that create value with it for organizations.
If you are in retail/hotel/golf or other industries with some kind of member-based structure looking to grow business with the help of social media, take a look at this on parallel6.com. This file gives a good idea of the power of this technology, but is no where close to their demo, which shows (in real time) so many opportunities for businesses to reach their “fans” and friends when they are in the market!
I've now known David, the CEO of Parallel6, for several years, and this is one of the most (if not the most) exciting offer he and his team have created. This technology not only turns fans to ambassadors while getting businesses to generate more revenue, it also turns friends to ambassadors: I'd be happy to make introduction for you and Parallel6 if this can help your business grow.
Thursday, January 06, 2011
Dreamforce: yes the force is powerful, and yes there are alternatives
Here’s a belated short post on Dreamforce (12/6-9). I guess I’m not the only one slacking off as first-time followups from booths that I had stopped by are still coming in.
My immediate reaction walking into the conference expo was that force.com has evolved to become such a powerful platform: just about anything can be “plugged” into the force platform. If there are things customers might want to do with the information that may already exist in SFDC, there is likely a company that offers such vertical integration so the customers can do what they want to do, on a platform they are familiar with.
While force.com is considered to be PaaS, Salesforce.com is well positioned in all three new segments of the cloud space totaling $113B (as BofA’s paper: 2011, it’s the year of the cloud, points out). Salesforce.com has been positioning itself well on collaboration, database and more (again more integration).
The companies integrating well with force.com (often selling as “native”) aren’t forgoing other potential markets, either. Most (if not all) offerings connect with an open API, and about half of the people asked if I use SFDC as CRM before talking about their product/service. This was prudent as potential clients are using or looking at alternatives for cost, integration, or other reasons. A recent question on a SaaS LinkedIn group asking for alternatives to Salesforce.com drew 80+ responses offering more than a dozen suggestions (many appear to have come from genuinely happy users).
If all the predictions about strong balance sheets fueling M&A become reality, how will the landscape of CRM look like in 12 months? How will this play out for the companies that built up their businesses on a platform such as force.com? Will this model look similar to that of apps on mobile platforms?
Here’s a belated short post on Dreamforce (12/6-9). I guess I’m not the only one slacking off as first-time followups from booths that I had stopped by are still coming in.
My immediate reaction walking into the conference expo was that force.com has evolved to become such a powerful platform: just about anything can be “plugged” into the force platform. If there are things customers might want to do with the information that may already exist in SFDC, there is likely a company that offers such vertical integration so the customers can do what they want to do, on a platform they are familiar with.
While force.com is considered to be PaaS, Salesforce.com is well positioned in all three new segments of the cloud space totaling $113B (as BofA’s paper: 2011, it’s the year of the cloud, points out). Salesforce.com has been positioning itself well on collaboration, database and more (again more integration).
The companies integrating well with force.com (often selling as “native”) aren’t forgoing other potential markets, either. Most (if not all) offerings connect with an open API, and about half of the people asked if I use SFDC as CRM before talking about their product/service. This was prudent as potential clients are using or looking at alternatives for cost, integration, or other reasons. A recent question on a SaaS LinkedIn group asking for alternatives to Salesforce.com drew 80+ responses offering more than a dozen suggestions (many appear to have come from genuinely happy users).
If all the predictions about strong balance sheets fueling M&A become reality, how will the landscape of CRM look like in 12 months? How will this play out for the companies that built up their businesses on a platform such as force.com? Will this model look similar to that of apps on mobile platforms?
Friday, December 03, 2010
How are SaaS and Enterprise Software Sales Different?
You might have come across SaaS sales job descriptions stating “x years quota achieving sales success, preferably/ideally in enterprise software sales (and SaaS sales)”. For anyone who has done or at least has familiarity with both SaaS and enterprise sales, there are clearly some differences… or are they clear?
In an attempt to clarify without “stereotyping” too much, here’s my quick take on some key differences:
* What is being sold:
SaaS: A relationship (long-term to get the recurring revenue)
Enterprise Software: A product (relationship is also important so more products can be sold)
* Sales mode:
SaaS: Sell over the phone/web, sometimes in person for large or strategic deals
Enterprise Software: Mostly sell in person. Meetings can also take place on the phone/web
* Sales productivity:
SaaS: More deals/rep, sales cycles tend to be days to weeks
Enterprise Software: More revenue per rep, higher cost for sales. Sales cycle can be weeks but more often are months
These differences may not keep over time. With proliferation of mobile computing and Web 2.0, end users / software customers have become more comfortable with and increasingly demand more SaaS offerings. Channel partners are also looking to get in the SaaS wagon as their businesses face narrower margins on current offerings. Software vendors, to stay competitive, continue (and for some, start) offering more with a SaaS model. The gap between SaaS and enterprise software selling are narrowing, driven by the three parties’ shift to SaaS. Would you be surprised to see in the not-so-distant future, that all software sales are done on the low-risk, pay-as-you-go model?
You might have come across SaaS sales job descriptions stating “x years quota achieving sales success, preferably/ideally in enterprise software sales (and SaaS sales)”. For anyone who has done or at least has familiarity with both SaaS and enterprise sales, there are clearly some differences… or are they clear?
In an attempt to clarify without “stereotyping” too much, here’s my quick take on some key differences:
* What is being sold:
SaaS: A relationship (long-term to get the recurring revenue)
Enterprise Software: A product (relationship is also important so more products can be sold)
* Sales mode:
SaaS: Sell over the phone/web, sometimes in person for large or strategic deals
Enterprise Software: Mostly sell in person. Meetings can also take place on the phone/web
* Sales productivity:
SaaS: More deals/rep, sales cycles tend to be days to weeks
Enterprise Software: More revenue per rep, higher cost for sales. Sales cycle can be weeks but more often are months
These differences may not keep over time. With proliferation of mobile computing and Web 2.0, end users / software customers have become more comfortable with and increasingly demand more SaaS offerings. Channel partners are also looking to get in the SaaS wagon as their businesses face narrower margins on current offerings. Software vendors, to stay competitive, continue (and for some, start) offering more with a SaaS model. The gap between SaaS and enterprise software selling are narrowing, driven by the three parties’ shift to SaaS. Would you be surprised to see in the not-so-distant future, that all software sales are done on the low-risk, pay-as-you-go model?
Friday, November 19, 2010
How is your -aaS unique?
When I saw a company advertising Infrastructure as a Platform (crossing out IaaS and PaaS in the process) at the Cloud Computing Expo (http://cloudcomputingexpo.com/) earlier this month, it occurred to me that -aaS has become well accepted (and crowded) that cloud providers, builders, and integrators are looking to differentiate themselves in less familiar ways to stand out in front of customers.
Speaking with vendors at the expo, it appears many try to differentiate with price, security, scaling, and integration: more hosting services are competing on rates and promotions, cloud security, provisioning, monitoring are getting better defined, FUD on scalability, uptime, and performance are all around, and integration (blurring) of public and private clouds are discussed/debated as the current and future trends.
Though the world is becoming flatter with the internet, only a few speakers made mentions of cloud computing outside of north America. In October Beijing unveiled a five-year plan for cloud computing with a market estimated at $30B: a translation of this page http://www.hdcatv.com/hdyzk/html/2010-10/14/content_23662.htm?div=-1 can give a better idea of what this is. The market shift is taking place quickly, and this will be a huge public cloud as it takes shape. Some leaders are developing capabilities in China: EMC already built 13 sites and grew to 1000 people working on cloud in different cities there, while most people don't see the cloud computing being relevant there in the next 2-3 years.
Are you a -aaS innovator? How are you differentiating from the "imitators"?
When I saw a company advertising Infrastructure as a Platform (crossing out IaaS and PaaS in the process) at the Cloud Computing Expo (http://cloudcomputingexpo.com/) earlier this month, it occurred to me that -aaS has become well accepted (and crowded) that cloud providers, builders, and integrators are looking to differentiate themselves in less familiar ways to stand out in front of customers.
Speaking with vendors at the expo, it appears many try to differentiate with price, security, scaling, and integration: more hosting services are competing on rates and promotions, cloud security, provisioning, monitoring are getting better defined, FUD on scalability, uptime, and performance are all around, and integration (blurring) of public and private clouds are discussed/debated as the current and future trends.
Though the world is becoming flatter with the internet, only a few speakers made mentions of cloud computing outside of north America. In October Beijing unveiled a five-year plan for cloud computing with a market estimated at $30B: a translation of this page http://www.hdcatv.com/hdyzk/html/2010-10/14/content_23662.htm?div=-1 can give a better idea of what this is. The market shift is taking place quickly, and this will be a huge public cloud as it takes shape. Some leaders are developing capabilities in China: EMC already built 13 sites and grew to 1000 people working on cloud in different cities there, while most people don't see the cloud computing being relevant there in the next 2-3 years.
Are you a -aaS innovator? How are you differentiating from the "imitators"?
Monday, October 18, 2010
Are Your Customer Relationships Driving Business Success?
The word customer derives from "custom," meaning "habit," and typically refers to a current or potential buyer or user of a product or service: someone who "frequents" a "shop" to make it a "habit" to "purchase" there rather than elsewhere.
Earlier this year I spoke to some MIT Leaders of Global Operations (LGO: lgo.mit.edu) students about the difference between "customers", “clients", "buyers", and "purchasers”, who they think their customers are and how understanding their customers can be pivotal for their roles and careers.
About a month ago I was reminded by Prakash Balebail of Estuate (www.estuate.com), a business partner I had the pleasure of working with while at IBM, how relationships with customers not only can indicate and drive the success of a company, but can be an identity differentiator (how others remember them with).
"All you need to remember are two things about my company," says Prakash contently, "every customer is reference-able and every customer is a repeat customer."
Isn't that something?
For Estuate to achieve this, the Estuate team has to bring significant value to their customers. Customers “value” what is different (be it service, be it product, and be it price if nothing else), and Estuate stays true to its motto: Extreme service.
Of course building an identity (of Extreme service) is not about what you say, but about what you do and the assessments that is triggered. It is about how customers perceive how they are greeted at the first meeting, about how their issues and problems are handled with professionalism, and about how they feel the door is still open for future business even after they decided to go with someone else for the time being... and throughout this journey, the customer needs perceive and value your difference. All of this assumes there is a compelling offer: in Estuate's case, partnerships with Oracle (http://solutions.oracle.com/partners/kini) and IBM (http://www.ibm.com/software/data/db2/lowerdatabasecosts/estuate.html), as well as team's deep experience form the Estuate edge.
The perceived difference that is valued (by the customers) is referred to as marginal utility in economics. Marginal utility doesn’t stay… competitors are there to neutralize marginal utility all day long. So to stay competitive in the game (to continue to have customers "frequent" your shop), one has to continue to identify the new marginal utility, perhaps instead of trying to figure out why something that used to work no longer works.
So... what is your Marginal Utility to your customers? How do you plan to continuously improve it to drive success?
The word customer derives from "custom," meaning "habit," and typically refers to a current or potential buyer or user of a product or service: someone who "frequents" a "shop" to make it a "habit" to "purchase" there rather than elsewhere.
Earlier this year I spoke to some MIT Leaders of Global Operations (LGO: lgo.mit.edu) students about the difference between "customers", “clients", "buyers", and "purchasers”, who they think their customers are and how understanding their customers can be pivotal for their roles and careers.
About a month ago I was reminded by Prakash Balebail of Estuate (www.estuate.com), a business partner I had the pleasure of working with while at IBM, how relationships with customers not only can indicate and drive the success of a company, but can be an identity differentiator (how others remember them with).
"All you need to remember are two things about my company," says Prakash contently, "every customer is reference-able and every customer is a repeat customer."
Isn't that something?
For Estuate to achieve this, the Estuate team has to bring significant value to their customers. Customers “value” what is different (be it service, be it product, and be it price if nothing else), and Estuate stays true to its motto: Extreme service.
Of course building an identity (of Extreme service) is not about what you say, but about what you do and the assessments that is triggered. It is about how customers perceive how they are greeted at the first meeting, about how their issues and problems are handled with professionalism, and about how they feel the door is still open for future business even after they decided to go with someone else for the time being... and throughout this journey, the customer needs perceive and value your difference. All of this assumes there is a compelling offer: in Estuate's case, partnerships with Oracle (http://solutions.oracle.com/partners/kini) and IBM (http://www.ibm.com/software/data/db2/lowerdatabasecosts/estuate.html), as well as team's deep experience form the Estuate edge.
The perceived difference that is valued (by the customers) is referred to as marginal utility in economics. Marginal utility doesn’t stay… competitors are there to neutralize marginal utility all day long. So to stay competitive in the game (to continue to have customers "frequent" your shop), one has to continue to identify the new marginal utility, perhaps instead of trying to figure out why something that used to work no longer works.
So... what is your Marginal Utility to your customers? How do you plan to continuously improve it to drive success?
Tuesday, August 31, 2010
Good Time for Investment Opportunities?
Recently a friend reached out with an opportunity to invest in a social media company that impact business metrics. It is time for interested investors to help expand their footprint and offers to the market.
Some questions come to mind: what's the current valuation of the company? Any plans for series X financing? What about terms of conversion for any convertible note? Discounts? Caps?
http://www.startupcompanylawyer.com/category/convertible-note-bridge-financing/
Is there a "pivot" - refocusing the company based on the description now and description of it at the beginning?
So a loaded question would be is this good time to invest in such opportunities (is there a good time)?
Recently a friend reached out with an opportunity to invest in a social media company that impact business metrics. It is time for interested investors to help expand their footprint and offers to the market.
Some questions come to mind: what's the current valuation of the company? Any plans for series X financing? What about terms of conversion for any convertible note? Discounts? Caps?
http://www.startupcompanylawyer.com/category/convertible-note-bridge-financing/
Is there a "pivot" - refocusing the company based on the description now and description of it at the beginning?
So a loaded question would be is this good time to invest in such opportunities (is there a good time)?
Saturday, July 31, 2010
For Friends Who are Job Searching
Over the past few months several friends and former colleagues reached out to talk about job searching. These often turn from a 10 minute conversation to 30 minutes or much longer. This entry intends to provide a few pointers I have been sharing with each person so that a bit of work can be done up front by the job seekers and save some time for everyone. Keep in mind that I'm not a professional career adviser and face challenges myself whenever I'm in that situation.
First answer a few questions for yourself:
1). Where (physically and career wise) would you ultimately like to be, and what immediate goals are you trying to accomplish?
2). Given those goals, what are the type of jobs that will get you there (you may have to do some search... the roles don't have to resemble your current title/role)?
2). What skills or strengths do you have that will have you stand out with your potential competition, and what gaps/challenges are there?
Now you know the types of role you are going after, check the "general" pay to ensure you want to spend time/energy to polish your resume, write the cover letter, and network to get that first interview. A couple of resources I like are:
http://www.glassdoor.com/ and http://salary.com/
Job searching nowadays often involve the internet as well as your network... LinkedIn has become a popularly used tool... a few articles on this topic would give you a good idea on this (if these links don't work, just do a search on your browser with "LinkedIn job search":
How LinkedIn will fire up your career http://money.cnn.com/2010/03/24/technology/linkedin_social_networking.fortune/
Improving the Odds For Changing Jobs http://online.wsj.com/article/NA_WSJ_PUB:SB10001424052748704913304575371212488670790.html
Within LinkedIn, I suggest people first build out their profiles (start by searching for a few people in the same industry with profiles that look good and model after those). From there, search for jobs that may be of interest. An easy way is to select "jobs" on the upper right and click on "advanced", then isolate the search criteria to <100 jobs to browse through. With each job, you can look for people you may know who work at that company, or people you know who may know someone there. This helps increase your chances of getting your resume to the hiring manager.
Often people complain that they never get a call back, or any kind of response. There may be many reasons for that, but often the hiring manager never even got to the resume because there are so many people applying for it... and a strong candidate who is referred (you may be just as strong) got the interview. Take one example... when I applied to an earlier role via LinkedIn and at the company's job site, I also asked a former classmate who worked at that company to pass my resume to the hiring manager. I was later told that first day the posting went up on LinkedIn, there were 30+ applications, and the fact that I was a referral helped getting my resume looked at, and getting a phone interview within the same week.
Having a strong network on LinkedIn is key for online job search, as the search results are based on your connections. A friend (<100 connections) and I (~1000) did the same query where ~10 postings showed up for her and ~200 showed up for me.
Finally, after some of the prep work is done, make sure your resume and cover letters are crisp and relevant to the job... yes, you need a different cover letter for each application. Resources can help include professional career counselors/coaches, and websites that show samples... and yes, friends, too, but again, they are not professionals the help you receive may not help you get that job you want, and the ROI of hiring a coach may be worth it.
Over the past few months several friends and former colleagues reached out to talk about job searching. These often turn from a 10 minute conversation to 30 minutes or much longer. This entry intends to provide a few pointers I have been sharing with each person so that a bit of work can be done up front by the job seekers and save some time for everyone. Keep in mind that I'm not a professional career adviser and face challenges myself whenever I'm in that situation.
First answer a few questions for yourself:
1). Where (physically and career wise) would you ultimately like to be, and what immediate goals are you trying to accomplish?
2). Given those goals, what are the type of jobs that will get you there (you may have to do some search... the roles don't have to resemble your current title/role)?
2). What skills or strengths do you have that will have you stand out with your potential competition, and what gaps/challenges are there?
Now you know the types of role you are going after, check the "general" pay to ensure you want to spend time/energy to polish your resume, write the cover letter, and network to get that first interview. A couple of resources I like are:
http://www.glassdoor.com/ and http://salary.com/
Job searching nowadays often involve the internet as well as your network... LinkedIn has become a popularly used tool... a few articles on this topic would give you a good idea on this (if these links don't work, just do a search on your browser with "LinkedIn job search":
How LinkedIn will fire up your career http://money.cnn.com/2010/03/24/technology/linkedin_social_networking.fortune/
Improving the Odds For Changing Jobs http://online.wsj.com/article/NA_WSJ_PUB:SB10001424052748704913304575371212488670790.html
Within LinkedIn, I suggest people first build out their profiles (start by searching for a few people in the same industry with profiles that look good and model after those). From there, search for jobs that may be of interest. An easy way is to select "jobs" on the upper right and click on "advanced", then isolate the search criteria to <100 jobs to browse through. With each job, you can look for people you may know who work at that company, or people you know who may know someone there. This helps increase your chances of getting your resume to the hiring manager.
Often people complain that they never get a call back, or any kind of response. There may be many reasons for that, but often the hiring manager never even got to the resume because there are so many people applying for it... and a strong candidate who is referred (you may be just as strong) got the interview. Take one example... when I applied to an earlier role via LinkedIn and at the company's job site, I also asked a former classmate who worked at that company to pass my resume to the hiring manager. I was later told that first day the posting went up on LinkedIn, there were 30+ applications, and the fact that I was a referral helped getting my resume looked at, and getting a phone interview within the same week.
Having a strong network on LinkedIn is key for online job search, as the search results are based on your connections. A friend (<100 connections) and I (~1000) did the same query where ~10 postings showed up for her and ~200 showed up for me.
Finally, after some of the prep work is done, make sure your resume and cover letters are crisp and relevant to the job... yes, you need a different cover letter for each application. Resources can help include professional career counselors/coaches, and websites that show samples... and yes, friends, too, but again, they are not professionals the help you receive may not help you get that job you want, and the ROI of hiring a coach may be worth it.
Sunday, May 02, 2010
Schedule Changes: Annoyances and Opportunities
Parents-in-law's visa delays meant a whole slew of changes: change of their international flight tickets, domestic flight tickets upon their arrival, changes to moving logistics...
Could others airlines afford the Southwest model? As long as one does not take the flight(s), those remain as credits for them? Given the recent hikes in random fees, perhaps not... the bigger question is does the Southwest model work in long haul flights, if people just cancel or change their flights without paying that penalty whenever they please? I fly Southwest when I can because I love the flexibility. Is it good business?
Parents-in-law's visa delays meant a whole slew of changes: change of their international flight tickets, domestic flight tickets upon their arrival, changes to moving logistics...
Could others airlines afford the Southwest model? As long as one does not take the flight(s), those remain as credits for them? Given the recent hikes in random fees, perhaps not... the bigger question is does the Southwest model work in long haul flights, if people just cancel or change their flights without paying that penalty whenever they please? I fly Southwest when I can because I love the flexibility. Is it good business?
Monday, March 29, 2010
Where do You Spend Your Time and Money?
Not surprisingly, many people spend lots of money on "E"... education, entertainment, eating, enjoying, earning, etc. Recently I came across a friend spending quite a bit of money on a personal coach, and another friend spending time recruiting others to join a financial investment group. Whatever happended to plain food, shelter, and clothing? Do we all have enough money saved up (our balance sheet) to ensure sufficient basic needs should something happen to our income?
Most don't think about retirement until retirement is here. This can be an ugly transition if not enough is saved up. With the economy still fragile, more and more articles on retirement and savings have popped up lately, including this WSJ article: http://online.wsj.com/article/SB126912089798665247.html?mod=WSJ_RetirementPl
I smiled when I checked my numbers as they appear to be on-track for retirement (assuming I keep working and saving), then frowned when I realized that I had to divide the number by two to account for both my husband and I... and subtract more if and when we have children.
Friends, before you make the next big purchase, or spend a large chunk of your time doing something, check your numbers and see if you still want to go ahead.
Not surprisingly, many people spend lots of money on "E"... education, entertainment, eating, enjoying, earning, etc. Recently I came across a friend spending quite a bit of money on a personal coach, and another friend spending time recruiting others to join a financial investment group. Whatever happended to plain food, shelter, and clothing? Do we all have enough money saved up (our balance sheet) to ensure sufficient basic needs should something happen to our income?
Most don't think about retirement until retirement is here. This can be an ugly transition if not enough is saved up. With the economy still fragile, more and more articles on retirement and savings have popped up lately, including this WSJ article: http://online.wsj.com/article/SB126912089798665247.html?mod=WSJ_RetirementPl
I smiled when I checked my numbers as they appear to be on-track for retirement (assuming I keep working and saving), then frowned when I realized that I had to divide the number by two to account for both my husband and I... and subtract more if and when we have children.
Friends, before you make the next big purchase, or spend a large chunk of your time doing something, check your numbers and see if you still want to go ahead.
Sunday, February 28, 2010
Buying New Car in 72 Hours
Did the dealer take a loss on our new car transaction? I guess there may be an element of truth as the price (before taxes) was below invoice and according to some claims out there (http://blog.truecar.com/?p=107).
While sitting at the Berkeley library waiting for the car brakes to be checked for the nth time (the stubborn high pitch noise just would not go away) last Sunday (2/21), J and I chatted on Skype and realized that at the rate I'm driving, I'm super accelerating the repairs/maintenance schedule for the car. We decided to buy a new car at that moment, and agreed to do it fast. It's last week of Feb, so there's got to be some promotion going on. After some web research on Edmunds.com, kbb.com and test driving at a dealership that very night, we were down to a couple of models, with the occasional light hearted comment of "should we consider xyz model as well?"
By Wednesday early morning, I was half heartedly trying to convince J to consider mini cooper while we were looking at accessories we'd like on a Honda Insight. By 3pm, we had an offer accepted and were ready to get on our way to pick the car up. Note all this was done via the phone and web, during breaks/evenings while not missing a beat at work and school!
Come to think of it, our house buying processes were just as fast and efficient, though there were more elements outside of our control in that case. The learning from these: decide whether to buy, perform focused research, talk self out of regretting later by understanding how prepared I am financially for this decision, and the conditions that would not be acceptable (and be willing to walk away from something) and go at it.
In the mean time, I'm off enjoying my Insight!
Did the dealer take a loss on our new car transaction? I guess there may be an element of truth as the price (before taxes) was below invoice and according to some claims out there (http://blog.truecar.com/?p=107).
While sitting at the Berkeley library waiting for the car brakes to be checked for the nth time (the stubborn high pitch noise just would not go away) last Sunday (2/21), J and I chatted on Skype and realized that at the rate I'm driving, I'm super accelerating the repairs/maintenance schedule for the car. We decided to buy a new car at that moment, and agreed to do it fast. It's last week of Feb, so there's got to be some promotion going on. After some web research on Edmunds.com, kbb.com and test driving at a dealership that very night, we were down to a couple of models, with the occasional light hearted comment of "should we consider xyz model as well?"
By Wednesday early morning, I was half heartedly trying to convince J to consider mini cooper while we were looking at accessories we'd like on a Honda Insight. By 3pm, we had an offer accepted and were ready to get on our way to pick the car up. Note all this was done via the phone and web, during breaks/evenings while not missing a beat at work and school!
Come to think of it, our house buying processes were just as fast and efficient, though there were more elements outside of our control in that case. The learning from these: decide whether to buy, perform focused research, talk self out of regretting later by understanding how prepared I am financially for this decision, and the conditions that would not be acceptable (and be willing to walk away from something) and go at it.
In the mean time, I'm off enjoying my Insight!
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