Of all the lessons I have learned this past year, one that definitely rings truest is that people who use data in their decision-making always come out on top. Having spent 15 years in an amazingly successful company, it became obvious to me that almost everything being done in the bank has a lot of planning and thought behind it. And much more often than not the planning was both strategically and tactically guided by mountains of data. When I left Wells, there are 30-40 analytics postings on any given day, I just looked recently and there were 120 job postings requiring analytics skills.
Now having spent close to two years working with a wide range of other businesses as a consultant, its clear to me that few businesses have the same will to use data in decision-making. It takes a lot of foresight, tons of planning, and huge amounts of discipline to really get a handle on the data in your business, and very few smaller business are able to develop an analytics culture.
That the 2nd reason behind founding BPO Elite. I identified that the talent gap growing quickly when it comes to analytics training (the first) and I also identified the lack of strong analytics cultures in most businesses (the second). So we set up BPO Elite to train and place talent with these companies in dire need to better analytics.
I am helping a friend prepare a new product he is going to launch for his consulting business. On the surface it seems like a great idea with a decent sized market that should fairly easily make a decent revenue stream. But what does the data say? How big is the market really? What is the ideal price to make the product profitable? How best to market it to the target demographic? Most business leaders take a few hours to conduct actual research and then dive in and start spending money on marketing and product development. And this is where so many go wrong. They never looked deep enough to find the data to answer these questions with a more scientific certainty. So that is where I come in.
Empowering small businesses to make more data-driven decisions is where it all started!
As most of you know, I moved here one year ago from the United States. I left behind a 15 year career as an analyst with Wells Fargo to set up a business here in the Philippines to train analysts. Over the past year, my path has diverged and expanded to encompass several different analytics solutions including social media outsourcing, recruitment analytics training for corporate HR professionals and speaking engagements at schools promoting analytics careers in the IT-BPO industry. I have trained close to 200 people from a large cross section of schools and companies.
This morning I started thinking though about why I came here in the first place. Are there more analyst jobs out there then their is talent available for them? When I first started looking at the demand side, I analyzed things like looking at postings in job street with the term analyst in them… I got back over 1000 postings. A year later I do the same thing, but am now getting back 1300 postings.
My analysis has always been that there are several factors which make a training program like I have developed not only necessary, but imperative.
First off there is not a lot of analytics related education being taught at the college level. You see it in some programs at some schools, but overall higher education is not producing analytics talent ready to fill the jobs.
Secondly, there is such a dichotomy of skills required for the job postings… soft or people skills like communication and cross-department project work combined with the technical skills in specific programming languages or experience with certain types of analytics tools. It is very hard to find people who can balance the art and science of analytics and no one here is training people on both… its all one or the other.
The third reason why a training program like mine is important is the job requirements are getting increasingly complex in both quantity and quality. Traditional methods of recruiting don’t work well for analyst positions because most recruiters are focused almost exclusively in the technical skills and not of the soft skills. It is very hard to assess someone for curiosity or the ability to conceptualize big data schemes in a way that can be explained both to techie developers and people skill focused managers. To make things more challenging, few companies are trying to retain and train up analytics talent within, they instead turn to recruiters to pirate or poach talent from somewhere else.
The need for training approaches that are innovative and effective is growing much, much faster than most people are able to grasp. The massively overwhelming amount of data we have to analyze in our businesses each and very day is mind numbing.
Trying to bring an analytics approach to real estate sales is something that is starting to pick up steam in the U.S. How long until someone here in the Philippines figures this out? Hmmm…. sounds like an intriguing opportunity!
Here is an infograph on Data Engineers, something one of my trainees came up with at the direction of my assistant.
I love it! So much information wrapped into an eye catching visual. I’m proud of you Alvin. This is really good stuff! Anyone looking for top-notch analytic talent who gets both big data (the science) and data visualization (the art), look no further. We have them here at DMAI!
For those following me, you know I am Guy’s number one fan, so I was in heaven when I cam e across this post. I’m doing a lot of this, but need to amp things up a little to get closer to where I want to be…. which is the Analytics Expert of the Philippines!!!
Several key bullet points:
- People who wield computers to analyze large amounts of digital information are in high demand.
- Businesses today control massive and growing streams of information that flow from cash registers, patient records, smartphones, warehouses, the sensors in your Nikes, databases, Facebook and good old-fashioned loyalty cards.
- The challenge is finding people who can put it all together and make better strategy. Everyone from the Central Intelligence Agency to Gander Mountain is on the hunt.
- “I would challenge you to describe to me an organization of any size in any industry or not-for-profit setting that will not be leveraging this,” said Isaac Cheifetz, a headhunter working to find the Mayo Clinic a head of information management and analytics. “Name one. I can’t.”
- Businesses have the data to keep sale racks thin, streamline shipping and get more people to click ads. What they need are better analysts. It’s a new kind of job, and it’s coming to your workplace if it’s not already there.
- The McKinsey Institute predicted in 2011 that a big-data boom would create up to 190,000 new deep-analytics positions in the United States, and demand for 1.5 million data-savvy managers.
- Fifty-five percent of big data analytics projects are abandoned.
- The most significant challenge with analytics projects, according to the survey? Finding talent. Most (80%) of the respondents said that the top two reasons analytics projects fail are that managers lack the right expertise in-house to “connect the dots” around data to form appropriate insights, and that projects lack business context around data.
- “A popular approach is to hire for skills,” said Roberts. “You’re going to have a lot of failures if you just say ‘I need SPSS, R, SAS’ or some other skill. Business and technology are evolving so fast now. You need someone [who] is compelled to learn and keep up with what is new. So, it’s the curiosity to learn the skill that is the fingerprint. Not the skill itself.”
- Creativity and curiosity, she says, are far more important than established skills.
- Another misstep is not recognizing the difference between candidates being curious or just detail-oriented — both very different attributes. The way to determine the difference? Asking questions that get at curiosity.
- Finally, HR managers should be aware that analytical professionals are just that — analytical. As a general rule, they are not likely to be charismatic and may not present well in an interview.
These bullet points are very similar to the section of my Introduction to Analytics PowerPoint about who are analysts and why we need more of them!
Sometimes you just have to keep it simple.