What Big Data means for the Marketing/IT Relationship.

There’s been a lot of hype around big data; what it could mean for businesses. However, one must consider that big data only provides insights, which need to be used to implement changes in order to drive profit. Big data solutions are not cheap, and your company needs to make a return on such investments.

Big data is Expensive.

Marketing teams can unlock ROI.

This is why the relationship between the CIO and the CMO is becoming increasingly important. These two are in charge of making sure that these investments turn into growth and profit for the business.

“Companies that are more data driven are

5 percent more productive and 6 percent

more profitable than other companies”

– Harvard Business Review

The CIO and CMO relationship is one in which we hope that opposites will attract. CIO often has access to IT infrastructure, customer data, and have the technical understanding to be able to access and analyze the data, whereas CMO has a the creative mindset and budget to be able to implement solutions that drive consumer engagement.

However, this relationship can also be a difficult one, as opposites may bump heads. The way to approach business, and the mindset of these two groups is often slightly different. Marketers often have a demand for speed, while IT solution shifts can often be difficult and timely to implement. Marketers may think creatively, while IT needs to be able to provide solutions to help make plans a reality.

Marketing solutions sound nice in theory- but only if you can implement given your infrastructure!

There is often also tension between marketing and IT as there are an increasing amount of digital marketing or cloud marketing solutions available, however not all of them can fit within the company infrastructure! There is a risk of time + money being lost if solution propositions are not properly reviewed by IT as well!

Overall, Big Data is providing tons of potential to unlock new revenue and to have a stronger understanding of your customers. A lot of this insights are useful for marketers, however, the CIO/CMO (IT/Marketing) relationship needs to consist of a happy marriage in order to be able to obtain RIO unlock the full potential of your company!

Using Data Science to Save Lives

Big data is changing the way that we make decisions. We are able to reduce risk, and transform data into intelligence and insights that can be used to optimize operations. I strongly believe that we can also use such insights in order to improve decision making strategies in areas that will make the world a better place, which is what Bayes Impact group strives to do (http://www.bayesimpact.org/). They use Data Science to save lives, utilizing the powers of big data to better communities.

One particular project that they are completing caught my attention which involves a partnership with Youth Villages. Specifically, they are helping by increasing accuracy in predicting programs and interventions that are more likely to help individual children achieve behavioural and educational success. I strongly believe that this is a great initiative, though I do have comments regarding the data available and how many factors will be considered.

Currently, the data available is the following:

1. Demographics (age, sex, race) [Which will likely correlate to program matching, though certainly cannot be solely considered]

2. Assessment info (psychosocial assessment, questionnaire, discharge, 1 yr post discharge) [Which will have a lot of really great data that could be compiled, though I am very interested to see one of these questionnaires to see the complexity of responses and how much variety exists. I would like to see statistics on accuracy and if there is a tendency for misrepresentation within these questionnaires.]

3. Follow up data (6, 12, 24 month follow-up surveys on academic performance, legal, and clinical outcomes) [Which hopefully provide an accurate means for evaluation for success]

4. Youth Villages Staff Data: education, credentials, tenure, job title, and demographics. [Another factor that adds complication, would need to attempt to see how standardized programs are and whether it is the program or educator that has the greatest impact on childhood success]

Having said all of this, if carefully implemented, this will certainly be a great initiative who results I look forward to seeing!

Gradient Descent

I recently learned about a cool way to minimize functions (like the true mathie I am!) and that way is through Gradient Descent. It’s a method, that I personally was never taught in my Math degree, to analyse the classic linear regression problem.

Here’s how it works: say you have a function that is defined by some set of parameters (for example, a typical cost function). If you start at some initial value on that function, Gradient Descent will take “baby steps” (defined by you), iteratively, towards a set of parameters that minimize the function. This happens through the magical methods of calculus! More specifically, “stepping” proportional to the negative of the Gradient of the function at the initial value.

You can also have some fun by using your favourite coding method (Octave is free software that is similar to Matlab that is good for beginners!) and implement the following:


Related links: 



Social entrepreneurship in a landscape dominated by technology ventures

[Re-post from an article I wrote earlier this year]

The way society thinks of business has changed a lot over the past few decades.

In the past, businesses were thought of as existing for the sole purpose of maximizing returns for the investors. However, when one examines how society has responded to things like the BP oil spill, the health effects of fast food, and the environmental damage caused by natural resource companies, it is clear that society expects a lot more from businesses than just profit maximization.

Businesses are, arguably, the most powerful engine of change in society, and we are starting to demand that that engine be driven towards social good in the long run and not just for the wealthy few in the short run.

However, if you look at the entrepreneurs that are on the forefront of these new demands of business — social entrepreneurs — you will find that society is not structured in a way that encourages this shift. In fact, there are many systemic issues facing social entrepreneurs that, until they are addressed, pose a barrier to these entrepreneurs’ development and the associated evolution of the way we do business.

I had the opportunity to meet a panel of four social entrepreneurs to discuss their successes and the challenges they are facing in a space dominated by technological ventures. The panel consisted of:

Emily Peat, EcoPlace Organics: assists small-scale, sustainable and organic farms through marketing, selling and distributing their produce to customers at home or work.

Stephen Amoah, MyCareerCity: connects students and recent graduates to start-ups looking for talent, combatting youth unemployment by providing their users with work opportunities and allowing them to develop their resumes.

Mark Kryshtalskyj, The RockStar Café: the student hub gone social and sustainable; a place where students can openly connect to one another in an inclusive setting, discover their passions, and express themselves.

Hannah Furlong, EverBloom Smart Design: integrates environmental science principles into urban garden and urban lawn space to make them more environmentally sustainable and teaches people better ways to garden through hands-on workshops.

I learned quickly that, contrary to popular belief, a social venture does  not place profitability lower on its list of strategic priorities. Rather, it builds social purpose into the foundations of its business model.

“Profit has needlessly become a dirty word. We want to be profitable so that we can give back more to the community, employ more people, and take on bigger/better projects,” Peat said.

There is an inherent strategic belief among this group that doing social good can drive profits because people want to support good causes.

Kryshtalskyj said, “Having worked in a non-profit setting for eight months, there is a different atmosphere than in a business. In a non-profit you are entirely focused on the cause and lose that business framework in a lot of senses. Social ventures are somewhere in the middle. You have the purpose drive of the non-profit, but the rigor of a business.”

Though they are similar in their drive for profit, social entrepreneurs face the challenge of not having access to the same opportunities as technology ventures.

An example of this is the exclusion that social ventures receive in funding opportunities and start-up resources, as one panelist  who wanted to remain anonymous shared.

“Velocity is a prime example of an excellent program with awesome resources and a lot of visibility on campus. The Velocity venture fund has $25,000 only open to tech businesses. I was very fortunate that I was able to find the funding in a different way, but I applied and was not eligible.”

Even when competitions are focused on social ventures, they ask for an element of technology, as another panelist, who also wished to remain anonymous, shared.

“I have seen a social enterprise competition that was exclusively for tech-based companies out of Communitech. They will ask for something tech-based to accompany your social enterprise. I have been tempted towards tech-based social start-ups because there are much more competitions and much more funding and have had to keep pulling back and remember where my original path was.”

The result of this exclusion is, in the mind of some panelists, suboptimal competition.  Their reasoning is that passion-driven social entrepreneurs have often spent years developing skills relating to their cause. They know the issues, they know their customers, and they are bona fide experts in their field.

This depth of expertise makes social entrepreneurs tough competitors in terms of understanding and serving their customers, especially in the early stages when tech-based ventures may not be developed or may be opportunistic.

Another challenge specific to social ventures is that social products and services typically have an associated price premium and, as Peat said, clearly communicating the value of that premium to consumers can be challenging.

The message needs to be framed in a way that is not overbearing or forceful, but emphasizes the products’ ability to create positive change.

Related to this is the challenge many social entrepreneurs also face of establishing metrics that allow them to sell their idea to investors. “Measuring how much impact you have on the economy is a challenge. One measure I use is how many jobs we have created, but going beyond, and having a more rigorous analysis in terms of how much impact you have is difficult to quantify,” Amoah said.

Despite these challenges, social ventures are gaining popularity. The panel expressed excitement for the recent increase in people who are engaging in social entrepreneurship, the growth in social organizations like Enactus, the increase in resources UW is beginning to offer, and ultimately for the growth in their own businesses.

In order to move forward, however, people need to be more willing to get involved with social ventures, schools need to offer more support, and investors need to be willing to endure slightly lower monetary returns for greater social ones. Ultimately, increasing the number of success stories is what will inspire other people break into this field and make an impact on their communities.

“Being an entrepreneur, it is kind of a scary path, but it is an exciting one as well. I am excited to hear more successful stories about social entrepreneurship,” Kryshtalskyj said.


What is Machine Learning?

So as a math student, I’ve always had an interest in Big Data. So I decided to take a Stanford course online on Machine Learning!

This first question, what is Machine Learning?

The definition is “The computer program is said to learn from experience E with respect to some task T and some performance measure P, if its performance on T, as measured by P, improves with experience E.”

In other words…Machine Learning is the ability for computers to learn without explicitly being programmed. You can split this learning into categories of Supervised and Unsupervised learning.

For Supervised learning, we observe a “right answer” using some form of regression analysis.

For Unsupervised learning, we give an algorithm a bunch of data, and ask the algorithm to find structure in the data.

Cool Start-up: GoldieBlox

Did you know that of the engineers world wide, only 14% are female? Even though I had no idea that was the number, I certainly saw this first hand when I went to the University of Waterloo- which has one of the strongest engineering programs in the country. However, I have always wondered, why are more girls not interested in technical careers and studies? It would be extremely beneficial for companies to have more female engineers in order to improve diversity on engineering teams, but the truth is that there simply aren’t enough females that are interested in engineering. However, today, I stumbled upon GoldieBlox, whose mission is simple:

“We’re a toy company out to inspire the next generation of female engineers.”

They use toys to help girls develop the skills and way of thinking required to succeed as engineers. They ALSO have an app that features Goldie- the girl inventor who loves to build. Absolutely brilliant. These are exactly the types of products that our children should be engaging in and teaching values of brains and not only beauty to our future female leaders.

Check them out here: http://www.goldieblox.com/