One Of The Key Differences About The AAP… Our Strong Ties to Academia.

It’s not a coincidence that the Analytics Association of the Philippines has such a strong focus on skills building and talent development.

In fact the majority of our founding board members either are currently or have in the past taught in higher education.

The reality of the current analytics landscape in the Philippines is that we need large scale initiatives to both upskill the existing workforce as well engage with the government and with academe to ensure a steady stream of analytics savvy graduates.

Some of the initiatives we have in the works include:

  • Upskilling training as many as 500,000 Filipinos currently working in the IT-BPO sector whose jobs are at risk do to AI
  • Facilitating a series of academic conferences to empower analytics educators with more tools and resources
  • Conducting train the trainer classes to build up the necessary number of analytics experts who can assist in both the massive upskilling and the teacher conferences
  • Working with a wide range of associations and organizations to offer targeted analytics training for their members
  • Bringing together analytics training providers, academic programs, industry leaders and government officials to unify the analytics ecosystem.

To meet the founding board members of the AAP, interact with many of the 30+ companies already working with the AAP, and to learn more about Big Data Analytics here in the Philippines, check out the following event:

https://conferences.enderunextension.com/conferences/big-data-analytics-summit-2017

It’s a holiday for many of us, but learning about analytics never stops.

See you there!

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Analytics Leadership – DMAIPH is a founding member of the Analytics Association of the Philippines (AAP.PH) and specializes in arming the Data-Driven Leader with the tools and techniques they need to build and empower an analytics centric organization. Analytics leadership requires a mastery of not just analytics skill, but also of nurturing an analytics culture. We have guided thousands of Filipino professionals to become better analytics leaders. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to discuss a uniquely tailored strategy to ensure you are the top of your game when it comes to Analytics Leadership.

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Data Science and Big Data Analytics For Finance

Was recently asked to do a one hour talk on data science and big data analytics for Finance… so I created A Step By Step Process To Get More Value Out Of Your Finance and Accounting Data.

To get started, we will discuss at a high level what is analytics, big data and data science and how it can be used in Finance and Accounting to get more value out of all the numbers you have in your business.

Per Deloitte, “In today’s highly competitive business environment, companies need more from Finance than accurate financial statements and reports. They need forward-looking, predictive insights that can help shape tomorrow’s business strategy and improve day-to-day decision-making in real time. “

New IT applications and infrastructure such as big data technologies, predictive analytics, as well as modern mathematical methods are opening up new possibilities for gathering and processing large amounts of data and opportunities for generating value.

They keys to a sound data science and analytics approach to Finance include the following:

  • A Process for Using Big Data to Answer Business Questions
  • A Well Mapped Data Lake of all the Data Finance Needs
  • The Right Mix of Analytics Talent, Technique and Technology
  • A Top Down Embrace of an Analytics Centric Culture

By translating data into insights around financial statements and operations, the finance team can unlock and create new value. Being able to identify unrealized and often unexpected potential as well as quickly and decisively mitigating risk, data science and analytics can take your team to a new level of insight and performance.

This in turn supports the finance function to make better decisions by being able to understand what has happened and why, and then predict what may happen next. The end result is a strategy built on data and one with a much higher rate of success then ones based on intuition or gut feel.

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The Fundamental of Business Analytics – Business 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. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to find out how you can strengthen your business analytics fundamentals.

APEC Data Science & Analytics Key Competency #4: Domain Knowledge and Application

According to the APEC (Asia Pacific Economic Cooperation) Advisory Group, Domain Knowledge and Application is one of the key competencies of a Data Science & Analytics professional working in the region.

By definition, a DSA professional can apply domain-related knowledge and insights to effectively contextualize data, achieved by practical experience (e.g. apprenticeships) and exposure to emerging innovations.

In my own experience, I knew Wells Fargo data like the back of my hand, but my domain knowledge would have easily allowed me to the same great things with other big banks. When I toyed with the idea of moving into the health services industry, it was obvious my skills would be useful but I had a lot ot learn about the domain knowledge of healthcare data.

Since, domain knowledge represents knowledge and insight that is unique to the organization or industry and that analysts need to consider when conducting any data project. Without this knowledge, analytics solutions may not entirely address the real business problem.

In my experience, domain knowledge about the data being analyzed can sometimes be acquired through exploration of the raw data.  Often, good analysts become subject experts just by playing with the data and asking questions to domain experts about the data.

Given the dearth of analytics talent in many areas, reality will dictate that a lot of data projects will have to be done without sufficient domain knowledge. However, most experts would agree the best results come when the ones using the data, know the data.

So, it behooves companies to invest more in educating and enabling internal resources then looking outside for DSA talent. My solution to this is to introduce apprenticeship programs where subject matter experts train current staff with high DSA affinity who are currently working in other roles.

As an example, there are likely thousands of current call center agents who have the aptitude to be analysts an data scientists, but never had the opportunity to of into DSA. Given they are already employees with proven track records of success, they would be much more likely to have the domain knowledge needed.

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Analytics Training – DMAIPH offers a wide range of analytics centric training solutions for professionals and students via public, in-house, on-site, and academic settings. We tailor each training event to meet the unique needs of the audience.

If you need empowerment and skills enhancement to optimize the use of analytics in your organization, we are here to help. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to set up a free consultation to learn which of our DMAIPH analytics training solutions is best for you.

Quick Data Science Survey

If you are in the Philippines and work with data everyday in your job, I’d like to invite you to take my survey.

Next week I will be speaking about data science in the Philippines, specifically trying to answer the question, “Just How Many Data Scientists Are There In The Philippines Anyway?”

It’s a short 7 question survey that will help me validate some of my research.

Here’s the link:

https://www.surveymonkey.com/r/WKG9VJ5

Thanks for taking a few minutes to help address on of the biggest questions facing the Philippines today.

Analytics Survey – DMAIPH conducts quarterly analytics surveys to collect data on current trends in analytics. We specialize in surveys that assess analytics culture and measuring how aligned an organization is to using data and analytics  in its decision-making.

Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to find out more about how DMAIPH can conduct surveys to help you assess the analytics culture in your business.

Most Analysts Are Spending Only 20% of Their Time on Reporting

In many cases reporting is either something that is set and stone and just needs to be filled or there is a time crunch forcing quick and dirty reporting.

Little time is devoted to using the data for storytelling, maximizing data visualization and really providing the audience exactly what its needs.

% Finding Analyzing Reporting
10 12% 6% 33%
20 14% 10% 39%
30 20% 31% 24%
40 6% 14% 2%
50 31% 16% 2%
60 14% 18% 0
70 0% 0% 0
80 0% 2% 0
90 0% 0 0
100 0% 0 0
       

Ideally, at least a third of the time should be spent post data gathering and analysis to really give the end user of the data the things they need for intelligent decision-making.

A full one-third only spend 10% of their time on reporting, which to me means that there is a lot of the waste in their analytics process.

If you take a full 40 hour week to complete a high priority, high value report but only have Friday afternoon to boil down your finding into a report, it is highly unlikely that your report will fully capture the fruits of your labor.

However, if the time frame is even shorter… you have to do all this in one day, you are just getting to the reporting phase at around 3:30pm.

You have less than an hour and a half to summarize you methods and boil your findings into a few points.

Making sure you craft a compelling story to really influence decision-making based on intelligent data analysis is likely impossible.

Data is based on a survey I sent to 3,000 of my LinkedIn connections who are either analysts or work closely with data and analysis.

Analytics Survey – DMAIPH conducts quarterly analytics surveys to collect data on current trends in analytics. We specialize in surveys that assess analytics culture and measuring how aligned an organization is to using data and analytics  in its decision-making. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to find out more about how DMAIPH can conduct surveys to help you assess the analytics culture in your business.

 

 

Survey Results: Devote More Time For Data Analysis

Most Analysts Spend 50% of Their Time Finding Data

% Finding Analyzing Reporting
10 12% 6% 33%
20 14% 10% 39%
30 20% 31% 24%
40 6% 14% 2%
50 31% 16% 2%
60 14% 18% 0
70 0% 0% 0
80 0% 2% 0
90 0% 0 0
100 0% 0 0
       

Most analysts spend most of their time finding data.

Among other thing this can mean they are setting up data mining or data gathering process to look for the data or it can mean they reviewing their data for relevancy.

My experience is that when you spending this much time on the finding the right data phase it reflects a poorly structured data environment or a unfamiliarity with the data needed.

Dirty data is also a big time waste.

Experience is the best solution for challenges with finding data. The fact the finding phase % is so high speaks to both the explosion in the 3 V’s of Big Data (Velocity, Volume and Variety)  as well as the number of analytics newbies.

To me this should be no more than 20% of your time.

I expected finding data would be the biggest chunk, but was surprised that over 50% of my analyst connections using at least 40% of their time finding data.

If you have one day to answer a key business question, this means you are using your entire morning just finding the data.

When you get back from lunch you haven’t even started the actual analysis yet and the clock is ticking.

Data is based on a survey I sent to 3,000 of my LinkedIn connections who are either analysts or work closely with data and analysis.

Analytics Survey – DMAIPH conducts quarterly analytics surveys to collect data on current trends in analytics. We specialize in surveys that assess analytics culture and measuring how aligned an organization is to using data and analytics  in its decision-making. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to find out more about how DMAIPH can conduct surveys to help you assess the analytics culture in your business.

Quick Analytics Career Question

Greetings to You My Valued LinkedIn Connection,

I was talking with a young professional just getting started in his analytics career. During our conversation we discussed what is most important to being a great analyst. With that in mind, I’d ask you to share your thoughts.

In your opinion, of the following ways to learn about analytics, which one has been the most important in your career path?

  • Formal Education – A degree or certificate in an analytics related field.
  • Self-Learning – Using trial and error and online resources.
  • Subject Matter Experts – Being trained/mentored by an expert.
  • Seminars/Workshops – Attending events to acquire new knowledge.
  • Technical Training – Attend training on specific technical areas.

Thanks for sharing. As always I will roll up all the replies I get and blog about it.

Dan Meyer, Analytics Champion, http://www.dmaiph.com

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Analytics Survey – DMAIPH conducts quarterly analytics surveys to collect data on current trends in analytics. We specialize in surveys that assess analytics culture and measuring how aligned an organization is to using data and analytics  in its decision-making. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to find out more about how DMAIPH can conduct surveys to help you assess the analytics culture in your business.

Most Analysts Spend 50% of Their Time Finding Data

Most analysts spend most of their time finding data.

% Finding Analyzing Reporting
10 12% 6% 33%
20 14% 10% 39%
30 20% 31% 24%
40 6% 14% 2%
50 31% 16% 2%
60 14% 18% 0
70 0% 0% 0
80 0% 2% 0
90 0% 0 0
100 0% 0 0
       

In fact, most analysts I know spend 50% of their time finding data.

Among other thing this can mean they are setting up data mining or data gathering process to look for the data or it can mean they reviewing their data for relevancy.

My experience is that when you spending this much time on the finding the right data phase it reflects a poorly structured data environment or a unfamiliarity with the data needed.

Dirty data is also a big time waste.

Experience is the best solution for challenges with finding data. The fact the finding phase % is so high speaks to both the explosion in the 3 V’s of Big Data (Velocity, Volume and Variety)  as well as the number of analytics newbies.

To me this should be no more than 20% of your time.

I expected finding data would be the biggest chunk, but was surprised that over 50% of my analyst connections using at least 40% of their time finding data.

If you have one day to answer a key business question, this means you are using your entire morning just finding the data.

When you get back from lunch you haven’t even started the actual analysis yet and the clock is ticking.

Data is based on a survey I sent to 3,000 of my LinkedIn connections who are either analysts or work closely with data and analysis.

Analytics Survey – DMAIPH conducts quarterly analytics surveys to collect data on current trends in analytics. We specialize in surveys that assess analytics culture and measuring how aligned an organization is to using data and analytics  in its decision-making. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to find out more about how DMAIPH can conduct surveys to help you assess the analytics culture in your business.

DMAIPH Quick Data Survey

A few months back I sent a quick survey to 3,000 of my LinkedIn connections who are either analysts or work closely with data and analysis.

Here is the question I asked.

Greetings!  I’m hoping you can help me gather some data for a book I’m working on. If you had to breakdown the work you do into 3 buckets; finding data, analyzing data and reporting data, what would the % of each be? A quick reply with your breakdown would be hugely helpful in my research. Thanks!   Dan Meyer, Analytics Champion, www.dmaiph.com

I got back over 400 replies.

Here is how they broke down.

 

% Finding Analyzing Reporting
10 12% 6% 33%
20 14% 10% 39%
30 20% 31% 24%
40 6% 14% 2%
50 31% 16% 2%
60 14% 18% 0
70 0% 0% 0
80 0% 2% 0
90 0% 0 0
100 0% 0 0
       

The higher the %, the more each analyst spent time doing that particular phase of analytics.

Here are some of my takeaways from this simple (and very nonscientific survey)

  • I was surprised to see 45% spend half their time or more on finding data. To me this is one of the telling signs that Big Data has led to a shortage of top analytics talent.
  • Only 1 out of 4 analysts are spending 20% of less of their time finding data. These are generally senior analysts, well established in their company.
  • Only half of my analyst connections are spending 40% of more of their time on conducting analysis. With significant time spent on finding and/or reporting data you can imagine a lot of important discoveries are being missed and opportunities lost.
  • Only 1 out of 3 analysts are getting spend my recommended 50% or more of their time actually doing analysis work.
  • Based on my survey, reporting gets shortchanged a lot. All in, 96% of respondents spend 30% of their time of less on reporting.
  • My recommendation is that you spend about 30-40% of your time on the reporting aspect, and sadly only 4% of my analytics connections are able to do that.

In an ideal world, I would expect an analyst to spend no more the 30% of their time on finding data, and at least 30% on reporting their findings, leaving more or less 40% to do the actual analysis.

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This breakdown is based on my own experience as an analyst as well as seeing how analyst working for data-driven companies work.

Only about 30% of my 400+ analytics focused LinkedIn connections come close to meeting my recommended breakdowns.

Which means I have a lot of work to do.

Analytics Survey – DMAIPH conducts quarterly analytics surveys to collect data on current trends in analytics. We specialize in surveys that assess analytics culture and measuring how aligned an organization is to using data and analytics  in its decision-making. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to find out more about how DMAIPH can conduct surveys to help you assess the analytics culture in your business.