Tag: DMAI

Q4: Can you please describe the current state of analytics in the Philippines? – Part 1

Let me tackle this question in two parts. The history major in me demands we look at how we got to where we are now before we talk too much about where we are going.

To start, both the appreciation for and the use of analytics has grown tremendously over the past few years. When I first started thinking about setting up a business in the Philippines back in 2011, hardly anyone knew much about analytics. Big banks, large call centers, multinational corporations and only the top schools were even talking the concept.

It was a challenge to fill my initial training classes due to lack of general awareness. Even at industry events and conferences it was rare to hear much about the idea of using data to drive business decisions.

Doing a search on the top job board in the Philippines back in 2012 for the jobs with analyst in the title netted about 1,000 job postings on any given day.  The average salary was some here around 30,000 PHP a month. It was a challenge to find good talent and those who could do analytics were all gainfully employed.

It wasn’t until 2013 that I stated seeing other analytics training options and those were just ones being done by IBM to meet the CHED (Commission on Higher Education) requiring the implementation of a six class elective tract in business analytics. The was accompanied by the launching of Analytica, and IBM backed effort to push the Philippines towards being more a viable option for analytics outsourcing.

At this time a job search for analyst would bring back about 1,500 jobs. Salaries were starting to rise for analysts as well with the market average getting closer to 50,000 PHP.  Still not a lot of public training or analytics centric organizations around then.

About the same time I started getting invited to schools on a regular basis to lecture about analytics to IT, CompSci and Management students. For the most part they had no idea of the career opportunities out there for those with analytics talent. I consulted with several schools on how to implement the CHED memo and how to prepare their students for analytics careers.

In 2014, an analyst job search was yielding closer 2,000 open jobs. The average salary climbed north of 50,000 Pesos for an experience analyst. I did a lot more trainings, being able to routinely fill a class of people hungry to learn more about analytics and how it could help them in their jobs.

The most in demand analytics skills up to this point where many centered on management reporting, production analysis and workforce management. Most analysts used some kind on proprietary database to store data and did just about all their analysis in Excel.

By 2015, analytics was finally in the mainstream.  Job posting now routinely called for specific skills sets in programming languages and business intelligence tools. Multiple organizations made up of analytics professionals started coming together. The number of jobs open hit 2,500 on any given day and salaries for really good analysts hit 70,000 PHP a year.  By this time, many outsourcing companies focused on setting up team of analysts to offer analytics as an outsourcing option.  Big data jobs and even data scientist positions started showing up in large numbers.

 

So here, we are now in early 2016. The sky is the limit when it comes to Filipinos with analytics talent being able to enjoy good career growth and make substantial salaries. The schools are now starting to churn out talent with analytics careers in mind. Things look great on the supply side of analytics talent and the market growth opportunity for businesses offering analytics is huge.

An additional complexity in the analytics world is the vast number of tools out there to gather, store, analyze and present data. Although IBM is by far the biggest player in training people, they are not the universal solution when it comes to the methodologies and technologies people use every day.

The biggest challenge today is that the demand for analytic talent dwarves the actual current and near term talent supply. The global need for not just analysts, but also data scientists has quickened to a point where catching up for the Philippines seems almost impossible.

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HR & Recruitment Analytics is the application of talent, technology and technique on business data for the purpose of extracting insights and discovering opportunities. DMAIPH specializes in empowering organizations, schools, and businesses with a mastery of the fundamentals of business analytics.

The recruitment and retention of top talent is the biggest challenge facing just about every organization. You really have to Think Through The Box to come up with winning solutions to effectively attract, retain and manage talent in the Philippines today. DMAIPH is a leading expert in empowering HR & Recruitment teams with analytics techniques to optimize their talent acquisition and management processes.

Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to learn how to get more analytics in your HR & Recruitment process so you can rise to the top in the ever quickening demand for top talent.

Q1: To start can you provide us with a basic overview of what is analytics?

Analytics is simply about looking for patterns in data to help answer questions. Most people use analytics within a business to help ensure more data-driven decision making. Businesses that use analytics are generally much more efficient and much more profitable then ones that don’t.

Analytics is generally employed by analysts who are skilled in using certain technologies and methodologies to identify, inventory and integrate large amounts of data quickly. What separates analytics from statistics and data science is generally the speed of the analysis and the focus on solving business problems.

The most common form of analytics is general business analytics that are used by senior leaders and decision-makers to investigate problems, validate assumptions and to guide strategic planning.  Business analysts are therefore the most common type of analyst. However, analytics can be used in an almost limitless number of business functions in specific areas like HR, recruitment, marketing, finance, and so on.

Analysts have been around a long time, but recent technological advances have both allowed us to produce and capture more data as well as give us the ability to analyze immense data sets quickly. Thus we are amidst a huge boom in the applications of analytics and the need for analytics talent across the globe.

Analytics is something just about every business leader is trying to figure out how to use more effectively in their business. As a result, there is a huge shortage of people who are skilled in working with data to answer questions and solve problems. This why you have seen the number of analyst job postings increasing at an amazing rate.

If you are not actively trying to surround yourself with analysts and if you are not infusing an analytics centric culture in your business, you will most likely soon see your business fail.

The Fundamental of Business Analytics – Business Analytics is the application of talent, technology and technique on business data for the purpose of extrating inights and discovering opportuniites. DMAIPH specializes in empowering organizations, schools,  and busiensses with a mastery of the fundamentals of business analytics.  Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to find out how you can strengthen your business analytics fundamentals.

20 Questions with Dan Meyer about the Fundamentals of Analytics.

Recently I was asked to put together an FAQ about analytics. Based on my experiences from training people how to better use analytics, these 20 questions are the ones I most commonly get asked.

  1. To start can you provide us with a basic overview of what is analytics?
  2. Can you tell us what makes you an analytics guru?
  3. What are some of the current trends in analytics?
  4. Can you please describe the current state of analytics in the Philippines?
  5. What are some basic strategies an analyst can use to find the right data at the right time?
  6. Can you provide some tips on how to manage data?
  7. What exactly is data science and why the rapid rise of data scientists?
  8. Here something a lot of us are wondering, what exactly is big data and how can we use it?
  9. Can you please describe the concepts of storing data in a data ware house?
  10. Please talk about how, when and why we use should descriptive analytics?
  11. Can you next describe how to best use predictive analytics?
  12. Next please explain when and how we can use prescriptive analytics?
  13. A lot of us want to know what is business intelligence and how does it add value to analytics?
  14. What is data visualization and how does it help drive better decision-making?
  15. What is a business dashboard and how is it used in a business?
  16. Can you tell us more about current trends and hot new tools in social media analytics?
  17. Many of us work in recruitment or HR. What are some best practices and technologies used in HR and recruiting?
  18. Can you please talk about recent developments in higher education on how to train more analysts?
  19. How would you describe your approach to teaching analytics?
  20. So in conclusion can you explain a little more about your own method for using data to drive better decision making?

Each day for the next several days, I will take each question and elaborate and share with you my own personal FAQ on the Fundamentals of Analytics.

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The Fundamentals of Business Analytics – Business Analytics is the application of talent, technology and technique on business data for the purpose of extrating inights and discovering opportuniites. DMAIPH specializes in empowering organizations, schools,  and busiensses with a mastery of the fundamentals of business analytics.  Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to find out how you can strengthen your business analytics fundamentals.

 

The Philippines An Emerging Center For Analytics

There has been a lot discussion the past several months about the relative pros and cons of outsourcing analytics. The biggest perceived con are that an outsourced analyst might not have the necessary business knowledge to pose the right questions or to clearly identify threats and opportunities.

However, the reality is that with the global analytics talent gap expanding at a rapid pace, many business have no choice but to explore outsourcing options for some if not most of their analytics.

Having worked with several businesses who have successfully outsourced analytics projects and even whole teams to the Philippines, I can say that the pros far outweigh the cons. Here are a few of the pros that I can testify to:

1. Speed and Focus. Once optimized, detached team can often get more done and get it done faster as they are able to mono task.

2. Fresh Set of Eyes. Given enough time to get up to speed on things, an “outsider” to the business often can see the forest through the trees.

3. Scalability. The savings based on things like having a team that can be quickly grown or shrunk based on business need and access to labor pools with a lower cost ratio can often make a big difference when it comes to covering all the bases.

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There are countless other reasons why business in the U.S. are increasing looking across the Pacific for analytics talent including an American style of English, an affinity for the American business practices and a firm commitment from higher education to produce analysts.

In fact, the number of academic courses and corporate training programs offering business analytics is growing rapidly here in the Philippines.

As key players in the BPO industry here in the Philippines look to meet many of the analytics needs of companies abroad, the pros will continue to outweigh the cons.

And that is exactly why I founded DMAI.

Give Me A Young, Hungry And Curious Person And I Will Teach Them How To…

Businesses want analysts who can dig into a question and not only get to the root cause but also come up with multiple solutions.. this is not something that generally is taught in schools.

Unleashing a young, hungry and curious mind on complex business challenges is not generally considered, as most companies tend to assign newbies to remedial task and assign tire, narrow thinking, veterans to handle the big stuff.

Companies that see past these challenges and can select talent, empower them and turn them lose with cutting edge analytics technology are the ones succeeding.

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Dont give me an excuse, give me a solution. Don’t come with just a problem, also come with a suggestion on how to fix it.

How many people do you have in your business that can do that?

All The Tools And All of The Talent but none of the Technique… Where Good Analytics Intentions Go Bad

I have seen so many examples of this. A majority of companies throw money at analytics in the form of buying new technology, but don’t spend a fraction as much on the people who need to make the technology work.

A good analyst using Excel is much more powerful then a mediocre analyst using a cutting edge BI tool. Without the innate curiosity, knowledge of the business and ability to communicate discoveries that come with a good analyst, your analytics plans will fall short no matter what the sales reps from the analytics companies promise you.

Now we have the 2016 Presidential Election results to analyze. Most predictive models had Clinton winning. Most of the polls had Clinton winning.

So where did the analytics go wrong? Well, its definitely not the technology. And I don’t think it was the talent.

In the coming days, I am pretty sure we will find it was the technique.

It was not getting deep enough data.

It was looking at the data and seeing what you expected to see.

Curiosity was lost.

Finding new perspectives to make sure we have the right data next time.

Hillary Clinton’s campaign will be a case study in where good analytics where not good enough.

Analytics Culture – The key to using analytics in a business is like a secret sauce. It is a unique combination of analytics talent, technology and technique that are brought together to enrich and empower an organization. A successful analytics culture is not easy to create, but DMAIPH can show you how. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly so we can build a strategic plan to turn your company into analytics driven success story.

 

When What Is New Is Actually Old

I saw this quote and thought it was worth sharing… often I remind people that most problems have already been solved by someone else. One of the keys to being a good analyst is having a network that you can go to when you are stuck and ask around to see if anyone else has already figured it out.

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DMAI has been blessed with a very successful year so far in 2015 and is starting to look towards 2016 planning. Let’s see if there is some more opportunities out there for us to teach some people to rediscover things again using analytics!

Another Chance To Start Over

http://sethgodin.typepad.com/seths_blog/2015/09/another-chance-to-start-over.html

Sharing Seth’s blog… another well timed post that seems to be directed at my life specifically.

Another chance to start over

Every day that you begin with a colleague, a partner, a customer… it might as well be a fresh start.

There’s little upside in two strikes, a grudge, probation. When we give people the benefit of the doubt, we have a chance to engage with their best selves.

If someone can’t earn that fresh start, by all means, make the choice not to work with them again. Ask your customer to move on, recommend someone who might serve them better.

But for everyone else, today is another chance to be great.

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Fundamentals of Business Analytics > Taking A Big Step Towards Implementation

Working on a training power point for a week long Fundamentals of Business Analytics class I will be teaching in two weeks.

A full week of training on business analytics is a new challenge and will serve as a precursor to a full blown semester long class. The audience here is made up of faculty who will be teaching classes as prescribed by the 2013 CHED Memo on infusing business analytics into the business administration curriculum.

I will break the class down into 5 section, each covering some of the course and learning objectives outlined in the memo.Here are the topics:

Day One: Introduction to Business Analytics

Day Two: Big Data & Data Warehousing

Day Three: The Three Type of Analytics   (Descriptive, Predictive & Prescriptive)

Day Four: Business Intelligence, Data   Visualization & Business Dashboards

Day Five: Analytics & Decision-Making

Whether you dream of being an analyst, aspire to be a better analyst or hope to surround yourself with people skilled in analytics, you have to strive to be different.

You have to look at data as having the answers and analytics as the key to determining which answers are the ones you need.

Working from this starting point, we will build a knowledge base that will give us a solid grasp of the Fundamentals of Business Analytics (FBA).

That is the core message I will inpart on the audience as no amount of skills based training along will make a successful analyst. You have to have a context to work within and that will be the biggest challenge of all, as the students will not have any experience at all.

Looking forward to seeing how this goes… its a laboratory for testing out how to train the trainer to train analysts out of a population of 3rd year college students.

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BI Professionals Spend 50-90% of Their Time ‘Cleaning’ Raw Data for Analytics

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BY ON AUGUST 26, 2015 • ( LEAVE A COMMENT )
Last year, the NYT shined a light on big data’s “janitor” problem – that data scientists and business intelligence pros spend too much time cleaning, not evaluating data. But how big of an issue is it, really?

Xplenty just wrapped a commissioned study of +200 BI pros and found that a third spend 50-90% of their time just cleaning raw data. This is one of the first reports to tie an actual # to the ETL process.

Source: bigdataanalyticsnews.com

From my days at Wells Fargo being an analyst I know how hard it was to maximize your analysis and communication time and minimize time spent finding and cleaning data. This was especially true for me as I was using more unstructured data to do things like competitive intelligence then structured data.

I see it being even more of a challenge now because the % of unstructured data in any business has exploded the past few years. Being able to mine valuable insights from unstructured data is a time consumer, at least until you get a process in place to extract and refresh the data using some kind of technology.

In addition, businesses continue to find new data points to bring into their data warehouses, dramatically increasing the amount of structured data.

What this means is a lot of analysts are spending a lot more time looking through mountains of data to figure out exactly which data to use. Its not going to get easier.

Good data gathering methodologies and nimble BI tools can help cut down on some of the workload, but in the end we just keep making data faster then we have the ability to truly process it.

There is just no replacing the human factor of someone knowledgeable about the business who can interpret the data and decide what data to use and what not to use.

Which makes life even more challenging, because once we determine what data we want to use, we still often have to take the raw data and clean it up so it is valid and so it will fit nicely into our BI tools.

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If you have having trouble figuring out what data to use in your business and if you find yourself spending far too much time cleaning the data, perhaps DMAI can help. We have a Data Science team ready to assist your organization with just these types of challenges.