The Analytics Training Opportunity of a Lifetime

Over the past 5 years I have worked hard to become one of the more established analytics brands in the Philippines.

My company provides 24/7 service via both home based and office based analytics staffing solutions.

As an analytics expert with over 20 years of experience I am confident we can handle just about any kind of analytics requirement.

We offer publics trainings quarterly, conduct in house analytics trainings regularly and I am consistently being invited to be a resource speaker.

The need for analytics is booming. Big data and technological innovation has made analytics one of the hottest needs on the planet.

There are only a few, probably less then a dozen actually, training companies offering analytics training in the Philippines.

The need is high for companies in the Philippines to get this specialized training.

The number of analyst jobs is projected to continue to grow almost exponentially for the foreseeable future.

U.S. companies will continue to look to the Philippines as a source for analytics talent and outsourcing options regardless of the political winds blowing across the Pacific.

Although machine learning and artificial intelligence may limit some of analytics jobs in the future, that is not of the near term horizon for most Filipino companies.

So, when I survey the analytics landscape in the Philippines, I am convinced DMAIPH is on the right path and even great success lies ahead.

Back in 2011, setting up an analytics company in the Philippines seemed like an idea ahead of its time.

Now, is 2016, my belief in the Philippines being a place to champion analytics and foster a culture of more data-driven decision-making has proved to be right on target.

As we look to 2017, the opportunity to empower even more Filipinos to be analysts and use analytics in their business looks even brighter. It is indeed the opportunity of a lifetime!

Which Analytics Training Is For You?

From my perspective analytics training options fall into the following categories:

Introduction to and/or Overview of Analytics
Technical Training on Specific Analytics Topics
Data Science/Advanced Analytics Training

Knowing which type of training you are selecting is super important as people just starting to get comfortable with analytics will probably be lost in a data science training.

On the flip side, a seasoned data geek will get bored in a introduction or overview class.

SO how can you tell which is which?

Here are a few suggestion on how to separate the intro classes from the technical classes from the data science classes .

First, most people who train on predictive analytics, using lots of math, statistics and building data models are probably talking data science. To get your bang for your buck in these classes you need to have a lot of exposure to the science side of analytics and be completely comfortable finding, analyzing and reporting data.

Second, if you are already working with data and you have specific tools you are working with for specific data functions, then you might be best served by going to a technical centric training. Like if you are using a tool like Tableau or Qlik or IBM Cognos to do marketing analytics or sending workforce management reports.

That leaves people who are either new to the idea of analytics or are just not sure where to start. Then you need an overview of analytics to figure out what you need in your business. Once you have a handle on your data, then you can really focus on certain technical aspects and get into data science.

The training I am conducting on November 22 is of the third kind. I will be giving an overview of various analytics techniques and technologies and introducing you to a variety of concepts to make the idea of using data to make decisions a reality.

On February, 21, 2017 I will be hosting a training on Data Analytics. E-mail us at analytics@dmaiph.com to register or get more info.

As a bonus, all attendees will also get a copy of my new book, Putting Your Data to Work. It’s a guidebook specifically designed for Filipino professionals looking to up their analytics games.

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 on which of our DMAIPH analytics training solutions is best for you.

Learn How to Turn Your Data Into Insightful and Actionable Analysis

Data Analytics Seminar

February 21,2017

9:00am- 5:00pm

Discovery Suites, ADB Drive, Ortigas Center

Objectives

We will start with a basic overview of analytics, current trends in the field and how analytics is being used here in the Philippines.
Through a couple of hands on exercises, we will practice finding data, analyzing it and reporting our findings.
We will go in depth understand several key components of analytics including business intelligence, competitive landscaping, data visualization and business dashboards.
We conclude the day by taking an assessment of each of our own business and starting to develop strategies to enhance the analytics culture in our business.
Learn more about Big Data and Data Warehousing

Key Topics

What is Data Analytics?
Overview of Data Analytics in the Philippines
Self- assessment of your own Analytics
Finding Data, Mining and Presenting Data
Internet Research Tips
Management Reporting
Reporting Using Excel
Big Data and Data Warehousing
Discussion about Descriptive, Predictive and Prescriptive Analytics
Business Intelligence and Business Dashboards
Using Data Analytics to Drive Decisions

At the end of this course you will learn:

How to do public data mining
How to provide data for Business Intelligence
How to build better reports in Excel
How to manage data for a business dashboard

Requirements: At least basic knowledge of Microsoft Excel

Who should attend?

People who make countless decisions every day!

Managers
Supervisors
• Business Owners / Leaders
Team Leads
• Accountants
• Analysts
• Students Enrolled In Related Courses of Study
Human Resources and Recruiting

This innovative and one of a kind workshop will provide you with easy to implement strategies to increase your effectiveness in decision- making.

While most people have an idea of what analytics is: data, analysis, metrics, and business intelligence are just the start… it is an abstract concept that is difficult to summarize in a sentence or two. Most business leaders know that they need more analytics based decision making in their operations, however few have figured out how to obtain it as analytics software or engaging high priced consultants doesn’t suffice.

This is where we come in. Daniel Meyer spent 15 years as an analyst with Wells Fargo Bank in the US, has combined that practical experience with his educational background; has a master’s degree in education, and developed an innovative training approach to analytics. DMAIPH specializes in a variety of analytics training solutions including ones designed for call center managers, recruiters, HR professionals, fresh grads, and analysts.

Learning Investment

Exclusive Offer!!

P 5,800.00 + VAT

This offer includes:

An Analytics Book especially designed for Filipino Professional

(Pay the full amount on or before January 20, 2017)

Group Rate (Minimum of 5)

P5,400.00

Regular Rate:

P 6,600.00 + Vat

(starting January 21, 2017)

All rates includes: Training Modules, AM/PM Snacks, Lunch and Certificate of Completion.

Registration

Kindly email us your Name, Company, Job Title and Phone Number. With the Subject: Data Analytics Seminar

info@sonicanalytics.com | analytics@dmaiph.com

You may contact us at (0917)799-2827 | (02) 959-8017

Terms and Conditions

Seminar Registration shall be carried out via Sonic Analytics’ Website or the link provided by Sonic Analytics or DMAIPH, by entering the necessary information into the relevant online application form.
After registration, the following will be e-mailed to the registrants: A) Confirmation email; and B) the Invoice
Contract for the seminar shall be deemed to be completed upon the receipt of the confirmation email. If a registrant’s application cannot be accepted due to lack of vacancies or for any other reasons, he/she will be informed immediately
Cancellation by the delegate will be subject to cancellation charges as follows: More than 15 days prior to commencement of the course: No penalty.6 to 14 days prior to commencement of the course: 25% of course fee.5 days prior to commencement of the course: 100% of course fee.Failure to attend course without prior notice being given: 100% of course fee.

Sonic Analytics and DMAIPH reserves the right to cancel or reschedule a Public Course and in these situations every effort will be made to accommodate delegates on an alternative course or refund payment in full.

Payment of the full course fee is required within 7 days of receipt of invoice. Failed to do so, the reservation shall be forfeited
The course fee covers training, venue, training materials, am/pm snacks, lunch and certificate of completion.
All stated fees are exclusive of VAT

Mode of Payment

DMAI accepts Cash and Cheque only
You may deposit the amount on our BPI Account:
Account Name: DMAIPH DATA ANALYTICS
Account Number: 3553-3662-74

About the Speaker

Daniel Meyer

Analytics Expert and Author

-President and Founder of DMAIPH and Sonic Analytics

-15 years of experience in the banking industry.

-Masters’ in Education

-5 years college teaching experience

-Published an Analytics Book titled “Putting Your Data to Work”

Having spent 15 years as an analyst in Wells Fargo Bank, Mr. Meyer gets analytics. With the combination of his practical experience and his educational background; Mr. Meyer has developed a unique and innovative training approach to analytics.

P600.00+ Shipping Fee

Putting Your Data to Work by Mr. Daniel Meyer is designed to be an analytics guidebook for the Filipino Professional. The primary aim of the book is to acquaint everyday professionals with a working knowledge of the key concepts of analytics. Whether you are an analyst, do analysis in your job or manage someone who does analysis, this book will help you get started with using more data in your decision-making.

To avail the book or get a free short version of the book, kindly email us your details:

Name, Company, Job Title, Full Address (for shipping) and Phone Number

For inquiries please call us at (02) 959-8017 and (0917) 799-2827

analytics@dmaiph.com | info@sonicanalytics.com

Testimonials

“I really learned a lot especially in terms of how to maximize the wealth of talent-related information that we have in PMFTC. I am pleased to inform you that I am downloading tableau as i type this message. I am also currently outlining a report that i want to present to my boss by Monday. I am also thinking about ways to improve our team’s regular reporting to HR Managers, being that none of the HR Business Partners seems to read the weekly report that we publish. I am looking at making it more like an infographic rather than just a collection of pivot tables that it is today. I can go on and on about the things that i want do to with everything I learned today. Thanks again for today’s learning-filled session.”

-Patricia

PMFTC

“The training was informative. Learning the fundamentals of recruitment analytics will really help me in providing quality work to the team”

-Raine

Convergys

“Dan’s pretty good. Can’t wait to do something more practical in forms of the application of training lessons.”

-George

Accenture

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Why Analytics Projects Fail – #12: New Technology

Occasionally one of the problems that can doom an analytics project is a new technology that emerges and makes the project obsolete before it is even implemented. This happened to me once when we were using an older and heavily modified version of Business Objects and then we got access to Tableau.

At the time, the flexibility of Tableau made our Business Objects business dashboard obsolete before we even completed the design phase of the project. The data visualization and the ease of use of Tableau Desktop at that time was miles ahead of anything our IT team could build around Business Objects. As a result, countless hours and dollars were lost, but in the end at least the business requirements we had established could be done by end users in Tableau.

Another example of how a new technology might impact your project is when a new version of the database you are using comes out. One that requires some much QA and/or testing to meet internal guidelines, that when it is finally approved it is hardly useful any more. This can often be the case with big companies that have long vetting processes to use new version of software. You’d be surprised how many Fortune 500 companies are still running internal version of Windows XP because using 8 or 10 has not been approved yet.

Modifications done in house to off the shelf solutions can also make new versions incompatible. I have seen this happen with both Cisco and Teradata databases, where internal development of data flows and data structures to be so rigid, it was impossible to use updated versions of the same databases.

You can also come across situations where developers and IT teams are ordered to use something else because changes in a vendor relationships or a new strategy from the CTO. In the end you have to adapt and either sacrifice, lose, or give up on what you have put into the project so far.

As the number of data collection and storage options grow, the complexity of data models surge and the types of business intelligence solutions increase, the likelihood of a big analytics projects being impacted by new technology. A good analyst has to stay up to date on what’s hot and new, in order to not advocate the use of something that is on its way to being a dinosaur.

To help me stay current, I follow several blogs and belong to a dozen analytics themed LinkedIn groups. I also try and attend at least one big industry conference a year as an attendee as well. And finally I read a lot. I end up going through 3-4 analytics themed books a month. If you are facing a situation where you are worried your project might fall victim to a new technology, let’s talk about it. I can help you figure out a solution to keep you and your project on the cutting edge.

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.

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.

Why Analytics Projects Fail – #9: Bad Data

In my experience, most of the time analytics projects fail its generally traceable back to a purely human problem. However, sometimes you see things fall apart because of technology, the misuse of technology and/or just bad technology. This is the case when projects fail because of bad data.

There are a lot of ways bad data can happen.

One common way you end up with bad data, is the data was not captured correctly. Perhaps the data was manually input with lots of error. Or maybe your data is not consistently collected so it has gaps. Knowing what exactly goes into capturing your data and being able to understand how it is collected is extremely important.

Another cause of bad data is that you are not getting all the data or you are getting data that has been altered. A lot of times when data passes from the collection point to you, it might be being truncated, or blended, filtered or converted. Lots of databases are structured for optimal data storage, not usage. A lot of database admins who don’t really know the data will add data flow shortcuts. Or maybe the fall under the datakeepers category and partition or cut out some of the data you need.

Bad data also comes in the form of old and out of date data. When you are making decision on data that just not recent enough, it can lead to a lot of problems. Keeping data fresh is something some companies just don’t value. If that’s the case, you will likely see your analytics initiatives come up with analysis that points you in the wrong direction.

In all three of these examples, one solution I suggest to mitigate the chance you have bad data is to build a data map. Learn about every point in a data flow that touches your data. Talk to the ones in charge of each touch point to make sure your data is not being impacted in any way that can result in bad data. Even if you cannot fix the problem, understanding it can help you set more realistic expectations of what your analytics project can achieve.

I have found using Visio to build data flow visuals is the best way to explore, document, and report how the data being used in my projects is being impacted by the environment it lives in. Knowing Visio is a valuable skill for an analyst. If you don’t use it, I promise you that once you do you’ll be sending me a thank you.

Analytics Culture – The key to using analytics in a business is like a secret sauce that fuels Data-Driven Decison-Making. 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.

Why Analytics Projects Fail – #6: Lack of Funding

Of all the reasons an analytics project can fail, one of the hardest to fix is lack of funding.

There are numerous causes for funding issues with an analytics project, 3 of the most common being unexpected budget cuts, shift in strategy, and lack of understanding.

When you are faced by unexpected budget cuts, which has happened to me several times, the best thing you can do is try and reconfigure your project so that as least pieces of it can still be completed. The idea here is to do what you can until more money is made available.

Having a well thought out plan that is scalable will help you tremendously. One time when I had a million-dollar dashboard project cut because of budget cuts, I peeled back some features and redesigned others to come up with a new plan for 10% of the original cost. That was approved. And over the next year I had pretty much added everything cut back piece by piece. Bottom line, if the company needs a new analytics tool, its up to the analyst to make sure they get it by being flexible and smart.

A shift in strategy happens a lot in business. So many internal and external forces are at play, a lot of times what once seemed a priority, can quickly become an afterthought. With analytics this can happen a lot when people fall back the we can just get by with what we have for now mentality. In today’s business world where success is driven by data, this can be crazy but it still happens everyday.

The best way to react to strategy shifts are for you to adapt your project to the new strategy and keep it both relevant and necessary. A good analyst can always find a way to offer analytics solutions for any part of the business. Use this adaptability to show your project can evolve with the needs of the business and you will likely still get funding, albeit for a new set of users.

The third reason lack of funding can happen, is actually a lack of understanding. Often finance decisions are made based on assumptions and predictive modeling… highly susceptible to being wrong if some important variables are missed. This has happened to me a number of times. But after conversations and educational moments with the finance team, the true value and ultimate savings of my analytics projects led to the lack of funding being mitigated.

Some things you can try when your project is impacted by a lack of understanding will take us back to the concept of enchantment. Make sure they like you and understand what value you and your analysis adds to the team. Often this can be a hard thing to quantify in a budget. Make sure you are showing how this project benefits others and helps the business as a whole… build trust. Third, make sure the project you are championing will make a difference, show that difference and educate on the need for that difference, in short show them you are doing this for a great cause.

There are countless reasons for lack of funding to become a roadblock for your analytics project, and countless ways to remedy this. If you are faced with one and need some help getting things back on track, connect with me and we can come up with a way to get your project funded again.

Why Analytics Projects Fail – #5: Organizational Politics

One of the biggest hindrances to the success of analytics projects is something most of us have experienced, organizational politics.

Organizational politics are informal, unofficial, and sometimes behind-the-scenes efforts to sell ideas, influence an organization, increase power, or achieve other targeted objectives. This is what happens when you find yourself being thrown under the bus… taken a fall for someone else’s mistake.

If you are lucky to have escaped organization politics for the most part and wondering just how they can lead to the downfall of an analytics project, let me share with you an idea what that looks like.

Data is horded. People don’t like sharing because its not encouraged or rewarded. In some cases people can be outright mean about it. Keeping data that they know can have a positive impact for others just to hold power over someone. It’s nasty.

This generally comes because senior leaders don’t really see the big picture and don’t share much themselves. This trickles down to the ones with the data and they build castle walls around their information and act as gatekeepers.

Projects can also be hindered, stalled or killed for no reason other than your boss lost to another boss. I once had a million dollar analytics project shelved because my boss got in trouble with the big boss. Nothing to do with me or my project or its cost or its benefits, it was completely because of something out my control.

When asking around you might hear of an experience like this as well. People hoard, manipulate and/or alter data not because it is being rewarded or encouraged, but because they are afraid being caught red-handed. A good analyst has to be willing to report the good with the bad.

One area of organizational politics you can control though is your likability. I make the comment a lot, that you have to be likeable to be an effective analyst. If people like you they share data with you, they advocate for analytics, they support you in a multitude of ways.

If they don’t like you, then its gonna be hard to be seen as an asset to the organization. An analysts job is to educate, illuminate, and inspire… you can’t do that with a bad reputation. This is a lesson many of us have to learn the hard way, but once we learn it we can see opportunities to increase our likability factor and actively use them to push our projects forward.

So the outcome of an analytics project you are working with is in jeopardy if you are in an organization rife with office politics. SO short of updating your resume, what can you do to turn the boat around?

Here are 3 things I suggest:

Get buy in from the top. Make sure what you do feeds its way up the food chain. Make sure the top dog’s analytics needs are being met and if they are not show how they can be.
Use your data to show win-wins. Find examples of where if we combined data from one source with data from another source you would have the makings of something even greater.
Buy lunch for the ones hording the data. Extend the olive brand, multiple times if need be. If you don’t stating being the catalyst for data sharing, who will?

If you can start impacting some of the negative consequences of your organization’s internal politics then your analytics projects will start seeding positive change. And that will eventually make all the difference in your success or failure.

If you need help combating some of the office politics in your organization that are hindering you analytics projects, connect with me and we will figure it out.

Why Analytics Projects Fail: #3 – Lack of Management Support

Nothing sucks more for an analyst than taking on an analytics project without support from above. Great analysts are generally only great if they have bosses who advocate for more analytics.

If no one at the top really understands the benefits of implementing your project, if the leadership will continue to use their gut in decision-making regardless of what your project achieves, then start updating your resume. This outcome happens often when the company does not have a business culture supportive of data-driven decision-making.

In this day and age, good analysts are hard to come by…. You can make more money and be happier somewhere else. Trust me. The chances of you being able to turn analytics naysayers into big data believers is highly unlikely.

That said, if you chose to give it a try… here are a few thoughts on how to get management to become more supportive of your analytics project.

Watch the Brad Pitt movie Moneyball. It will inspire you. Read the book Enchantment by Guy Kawaskai. It will empower you. Im not joking. You cant do this on your own.

After that, then you need to do a few things.

First find the person in upper management most likely to get on board. Ask them to help you. Show them data that will outline the better new world after your project is complete. Tell them about analytics success stories (like Moneyball). Let them see your passion for data-driven decision-making. You need Brad Pitt.

Next, using the concept of Enchantment, determine what is it about you and your project that will build trust. Will it create more transparency? Will it mitigate risk? Something that demonstrates how this project will increase the level of trust between everyone.

You also need to be likeable. Your project needs to be likeable too. What is it about the project that will make people happy? Who gets a better report, faster and with more useful data? Who gets to start using a business dashboard to make quicker and better decisions? What will each of the stakeholders like about this project.

And then you roll out the great cause. The monetary value generated from implantation. The level of risk mitigated. The better intelligence on competitors or about your market. What will be that great cause?

So now you are in a better position to be Jonah Hiil and go start changing minds and swinging opinions about your analytics project.

Finding The Time To Talk About Analytics Strategies

One of the biggest frustrations I hear from people when we are talking about how empower more data-driven decision-making in an organization is that no one has enough free time to get serious about analytics.

When facing this kind of challenge, a short presentation full of useful data can be used to start the ball rolling. When people say they are too busy then they are often actually saying I have too many things to keep track of and I am not as organized as I should/could be.

There are indeed times when there is more work than can be done in 40 hours a week, but that is actually not the case in most situations. Most corporate cultures reward those with the “I’m so busy I don’t have time to waste on reports” badge of honor.

To counter this you need to do some research into what are the potential time and cost savings that come from fixing the reports and getting better data to decision-makers. It wont take long to find a lot of numbers to use in your business case after a quick Google search. LinkedIn is also a good place to find lots of supporting documentation.

Once you have that info, you can add it to your own assumptions about what KPIs are not being used or what KPIs are missing from current reporting or which KPIs are miss reporting. This can all be turned into a short, compelling case for others taking the time to talk about broader reporting across the organization.

To really add some punch to your argument, ask one of the too busy people to give you a few minutes of time to ask them what more they want/need out of their reports. Hardly anyone is truly happy with the reports they get. Gain a few allies in your crusade.

Most people think that using analytics effectively is all about the technology, but the real secret to success is getting the people on board and on the same page. True analytics centric cultures are based on engagement and that engagement needs a facilitator.

Once you have your story and a few key advocates it will be a lot easier to get closer to the data-driven decision-making you are looking for. If you need help polishing your story or advice on how to get the engagement of a really tough “I’m too busy” co-worker, let me know. I’m sure I can lend a hand.

Who Is Best In Your Organization When It Comes To Analytics?

I am currently sharing a survey asking my LinkedIn connections about what part of their business is the most successful when it comes to using analytics to drive decision-making.

If by chance you follow my blog, but don’t get my LinkedIn e-mails. Here is the survey:

As you may know, I have been working on a book about analytics and the data-driven cultures of companies who successfully use analytics. I have a quick question to ask you that will help me in my research.

1508982_603376689807778_4892012849582809050_n

Of the following business lines, which one is the business line in your organization that in your opinion best uses analytics when making key business decisions? (Pick One)

Sales & Business Development
Marketing
Operations
Supply Chain/Inventory
Legal, Risk & Compliance
Customer Service
Human Resources/Recruitment
Strategic Planning
No one really uses analytics in decision-making effectively.

Thanks for taking the time to reply, it will be really helpful.

Sincerely,

Daniel Meyer, Analytics Guru

danmeyer@dmaiph.com

I’d like to validate what my experience tells me are the areas who generally best do analytics. I’m also looking forward to finding out there people see as general weak spots.

I’ll be happy to share the overall results of the survey once it is complete.

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