Product Lesson : Get out the door, quickly and so often

One week ago, I’ve learnt a marketing lesson, the hard way. I wanted to write it and may be posting it on my office’s wall.

So, let me start with a little bit of background.

The story started with me and my fellows building a high-tech product on top of open-source platform. The product has a R&D nature and it took us about 6 months to get our first proof-of-concept. It all started when we have been approached by a Tech Savvy from a Major Company (Let’s refer to him as Mr. X) to expand our technology to serve his needs as we have a niche expertise in this very specific field. Out of the definitions of Geoffrey Moore for customer types, I would call Mr. X a Technology Enthusiast/Savvy and an inventor, he’s very keen to try out new technologies at very crazy high frequency. And the visionary decision makers in his company (The Early Adopters Visionaries) would definitely refer to him to make investment decisions in technology and product in this field (That’s my own assessment).

So, what was the hard lesson ?

After we spent those first 6 months building our first most proof-of-concept, we took a decision that it’s not ready to show off to Mr. X, simply because it’s not perfect. And the hypothesis we had at that time, is that Mr. X (A corporate guy), won’t like a half baked solution. So, we spent another 8 months (Yes, way more that the first phase), trying to get our solution more into mass production, perfect, deployable shape. But after those 14 months spent, the product wasn’t ready to be consumed by public or even to be beta-released, and it’s still a proof-of-concept. So, now it’s 14 months with us working inside a lab, closing a door on ourselves, without giving or receiving any feedback from the initiator of the project idea. Then we decided, well, let’s just show him what we have. and we did.

So, here comes the lesson, we figured out that he went a long way past that idea, and he doesn’t need our solution anymore. And guess what, our proof-of-concept was a very good story for him that he got excited about it, and willing to reference us for other folks who are interested. 

The lesson here is clear, we should have approached him 6 months ago, he’s a Tech Enthusiast, and those guys doesn’t care if you have a half baked solution, as long as you’re giving them first hand on your technology, and give them the truth. They’re just willing to accept bugs and shortcomings if this will enable them to be atop of the ride. And the good part, is that they’re willing to give constructive feedback that could drive your product in a good way.

Not only going early to market would have been a good chance to get his hands on the tools and getting a quick feedback. But, also going early to market has the benefit of putting the team under market’s fire, and get them working at a light speed to satisfy the immediate customer needs. Instead of working at leisure with no direct pressure.

The take home message here, don’t be shy from showing your progress to Tech. Savvys, They’ll just help you for better steering, and may introduce you to visionary decision makers (Who usually use them for that purpose). And may get your product co-developed, or introduced to Market faster. Get out of the door, more often, and never shut your doors.


Focused Learning Plan

I had always an issue with focusing on reading one certain book and finish it before moving to the next, that doesn’t only make reading books takes longer, but it also reduces my ability to grasp the knowledge from each of those.

Another problem I’m facing also, is deciding what to read, and I tend to add huge number of books to my shopping cart, then ordering them later, only to actually read fraction of those.

But, now that I’m preparing for a Product Management position, I’ve decided to create a focused reading and learning plan to span the following categories :

  1. Technical (Coding Interviews)
  2. Marketing
  3. Entrepreneurship
  4. Management
  5. Design

Over a duration of 6 months, a total of 28 books to read and 10 online courses to take, with estimated total time requirement of 900 hours, beside a full-time Product Management job, that means a nightmare and a need for tight and efficient plan.

So, I’ve followed the following strategy :

  1. Breaking down the needed tasks in Trello board
    1. Book Reading Tasks (1 task of 10 hours/book)
    2. Book Summarizing Tasks (1 task of 5 hours/book)
    3. Course Following Tasks (1 task of 10 hours/course)
  2. Then to visualize my progress and my ideal burndown of those tasks, I’ve linked my trello account to

So, this is how my burndown chart looks like, right now.

Learning Burndown Chart 11 Nov 2015

And this is the list of books on my next 6 months plan :

Books to read, 11 Nov 2015

Now, let’s see how it goes. I’ll keep you posted  🙂

BigData Trends and opportunities

Should I even care ?!
If you’re reading this article, then there does exist a high probability that, you’re one among those who have heard a lot the trending Buzz Words “Data Science” & “BigData”.

In fact those areas are expanding at a crazy speed, and according to some studies, the demand for Data Scientists will continue to grow, as in the following infogram from a report for SAS, on Data Analytics adoption and trends between 2012-2017, on UK market, they forecasted an increase of 243% in demand.


From SAS report, on Data Analytics adoption and trends between 2012-2017


And the following chart from a wikibon’s article shows the trend of revenue for BigData Continue reading

Who should learn about “Data Science” , and how ?

So, if you heard enough about “BigData” & “Data Science” and is eager to be a data scientist, we’ll go through laying out a map of the available tools and required skills, and what you can do to be a data scientist. If you don’t know why you should learn Data Science review our post :

BigData Trends and opportunities

So, there’s a HUGE number of resources online there to learn about data science, and there exist nobody who can leverage all this amount of information, so what we’re trying to do here, is discussing what’s the possible path, that someone could take to reach his goals, which takes us to these questions :

“What areas does exist in the field of data science ?”

“What types of professionals are there in Data Science field, and who’s the Data Scientist?”

“What’re you goals to learn about Data Science ?”

“Do you believe that it’s fulfilling ? are you thrilled to learn about it ?”

After answering that question, a natural question would be : Continue reading

BigData Evolution From MapReduce To Infinity….

In this article I’ll highlight the history of BigData since Google’s MapReduce till current trends and tools.

It’s debatable what BigData means, or where the boundaries lies, there is no standard way to define it, but generally the following diagram is quite popular :

other figures will use only 3 Fronts (Variety, Volume and Velocity) , generally the more far from the center, the more close you’re to what is treated and called now “BigData”.

Continue reading

Hadoop Mapper output Compression, Optimization Trick

So, today I’ve experienced a nice experience with Hadoop’s Mapper output compression, where I had the output of the mapper as structured data (to simplify later-on calculations), but to my surprise, I’ve found that the data shuffled, way too much (about 3x) the original data size, although I’ve enabled map output compression, then I decided to try to encode the Mapper output value in text object, and to my surprise, I got about 100x improvement regarding the size of the shuffled data (because my data was easy to compress in textual format, as the entries was similar to far extent).

So, the reason here was that the custom object, I’ve created at first was serialised to binary format, which make us lose the advantage of the similar nature of the data, and didn’t compress well.

So, next time you decide to use custom object as Mapper output, and marshal it, think twice about your data nature, and experiment with encoding it in Textual format instead of custom objects.