Category: Fundamentals of Business Analytics

Five Year Plans – What Analytics Do You Use?

As the 5th year of my original business plan comes to a close, it seems like a good time to reflect on how things have played out.

There are plenty of data points to look at to determine how sound my original plan was and if the course changes made along the way proved to be the right ones to take.

The single most important metrics in my 2012 business plan where # of Filipinos trained to be analysts, # of schools I have worked with and $ of revenue I have generated.

Looking first at the revenue, because if you cant make a profit after 5 years then you are doing something seriously wrong. I started making a profit I year 3, which is pretty typical of business startups.

I made my most money in year 4, but had a more diversified revenue stream in year 5. Revenues have been closer to my actual target as year 4 was one of almost too much growth.

Originally just making money from public trainings, over the years I have added paid speaking engagements, consulting, outsourcing and most recently publishing a book.

SO based on $, I have achieved my original plans and am able to comfortably move on to the financial goals of my next 5 year plan.

When it comes to working with schools, who represent the future of analytics in the Philippines, I have consistently given talks, been part of activities and mentored interns/OJT.

When I check off the list of schools I have worked with in the past 5 years I can definitely say I have met this metric.

The third data point I look at is number of Filipinos trained.

When talking about public trainings we are about 1000 persons over the past 5 years. When we add the number of attendees of public speaking engagements, the number gets closer to 5,000. And that’s paid events.

If I add the number of students and free events we are getting close to 10,000.

SO, I have fall surpassed my expectations from 5 years ago on that metric.

When assessing the success of a business plan you need to measure data over time to make sure you are making progress.

You also need to be able to make course corrections.

Before the training business started taking off, I did some consulting. To generate consistent revenue, I got into outsourcing.

Both course changes allowed me to continue pursuing my original goal of training Filipinos to use more data in their decision making and to empower analytics centric cultures.

So what are the key metric of your business plan? How do you measure them and make sure you are making progress. Do you have a threshold that you set to make course changes if you are not meeting that threshold?

To effectively execute a business plan, you need good analytics in place.

Dr. Data_Analytics in the Philippines

Analytics in the Philippines – The Philippines is at the center of the action when it comes to solutions to the global need for analytics. Blessed with a solid foundation of young, educated and English speaking workforce, companies around the world are look for Filipino analytics talent to fill analytics positions. DMAIPH was set up to facilitate these solutions and bring the talent and the business together. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly so we can help you take advantage of this unique global opportunity.

 

 

It’s No Longer Just Enough To Know

In a recent conversation about using more analytics in the measurement and evaluation of public policies and programs, one of my colleagues said that in today’s world, “It’s no longer just enough to know.”

The point being if you aren’t using data and analysis to enhance your efforts and empower decision-makers with actionable insights, then you are not serving the public to the best of your ability.

A lot of government programs, non-profits and philanthropic organizations are what he called, “Information Rich, but Data Poor.”

Check out my upcoming webinar on Feb 15, 2017! https://dmaiph.com/2017/01/14/analytics-and-data-driven-decision-making-webinar-on-feb-15/

Just because you gather massive amounts of information in the form of data points, does not mean the data is adding value. In fact one of the biggest challenges the corporate world has been dealing with the past few years is how to optimize Big Data.

We live in a world where so much data is produced and captured, then analyzed and published in reports and article, yet the data and analysis alone is often not having the impact our policies and projects were intended to have.

In effect, we might know things, but we aren’t able to influence decisions because our data is not compelling enough.

To this end, I have advocated importing some analytics themed best practices from the corporate world to educate more on what to do with the data and how to put the data to use. To in short, be Information Rich, Data Rich to move towards more Data-Driven Decision-Making.

Starting backwards, I will first focus my training on the How. How do we make more data-driven decisions?

The I will focus on the Why. Why do we need to make more data-driven decisions?

From there we will go into several business analytics concepts like Data Visualizations, Public Data Mining, Data Lakes, Demographic Profiling using Big Data, and Data Blending.

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A final topic of interest that I will bring to the discussion is the Plus Minus Implications for Unstructured and Qualitative Data. Things that at first can be hard to assign a number too, but are just important as any piece of traditional data used in decision-making.

At the conclusion of my work, public policy and project reporting will be much more data rich, influence will improve and decision-making enhanced.

Now we won’t just know, we will be able to champion what we know in ways that will make a difference.

Analytics Education – Facilitating a mastery of the fundamentals of analytics is what DMAIPH does best. All across the world, companies are scrambling to hire analytics talent to optimize the big data they have in their businesses. We can empower students and their instructors with the knowledge they need to prepare for careers in analytics. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly so we can set a guest lecturer date, On-the-Job Training experience or other analytics education solution specifically tailored to your needs.

Big Data Analytics: Interpretation and Assessing Results > 2/21/17

I will be speaking on  February 21, 2017 at Discovery Suites, Ortigas Center, Pasig City on Data Analytics.

With that in mind, I wanted to share a little more detail about each section, next up…

Enabling Your Business to Make Smarter Decisions Section 3:  Interpretation—Assessing Results

Participants will be able to Articulate the Importance of Accurately Interpreting Data. Having the right data at your fingertips is essential to being successful with analytics.

We will also be able to Determine and Analyze Risk, Uncertainty, and Probability. With so much data, you need to know what data to analyze when to stay ahead of the game.

I will also talk about how to Spot Patterns, Trends, and Fluctuations Through Correlation, Regression, and Descriptive Statistics. Analytics techniques like these will keep you on the cutting edge.

Attendees will be able to Understand when to employ Descriptive, Predictive or Prescriptive Analytics. Each type has a specific use, make sure you know when to use each one.

And finally we will discuss how to Build Data Models. You don’t need to have high priced, complicated software to do some basic data modeling. I’ll show you some examples.

That’s section three… I’ll go over the last section in the next few days.

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.

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My Blog Post on the Analytics of Measurement and Evaluation

I recently had the honor of writing a blog post for American University’s Measurement & Evaluation program.

The post is about using a business analytics approach to “effectively evaluate projects, programs and processes.” This is in a response to the fact that it is becoming increasingly essential to use big data and analytics to ensure organizational success.

Here is the link: http://programs.online.american.edu/msme/resource/measurement-and-evaluation-analytics

It is my hope that I can inspire readers to look for ways to bring new data into their projects, programs and processes, blend it with current data, provide more dynamic analysis and share more impactful results.

I will also be doing a webinar early next year entitled Its Not Longer Just Enough To Know. Where I will highlight some techniques and technologies that I use to empower more data-driven decision-making.

Facilitating a mastery of the fundamentals of analytics is what I do best.

All across the world, companies are scrambling to hire analytics talent to optimize the big data they have in their businesses. Though my company DMAIPH, I can equip students and their instructors with the knowledge they need to prepare for careers in analytics. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly so we can set a guest lecturer date, internship, on-the-job training experience or other analytics education solution specifically tailored to your needs.

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The 3 Pillars of Small Business Analytics

When I consult with small business owners, there are 3 areas where my guidance generally has the most impact. I call these areas the 3 Pillars of Small Business Analytics.

The first pillar is a Competitive Landscape. I have found that very few small business owners really have a handle on the competition.

A competitive landscape analysis will reveal threats and opportunities that generally are not obvious to a business owner who focuses most of his/her energy on running the business itself.

Some of the data points you can capture and analyze include pricing, location, business size, quality, scope of business, diversity of product offering and of course revenue.  You would be surprised to find how easy it is to gather all this info.

Knowing where your products and services stack up against your competition is a key to prosperity. To achieve this understanding you need to use analytics.

The second pillar is a Demographic Profile. I have also found that very few small business owners really understand the demographics around their business.

A demographic profile analysis will illustrate how closely your customer base mirrors the actual population around your business. In many cases small businesses are not positioning their services correctly based on the opportunity in their market.

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Data to include would be traditional demographic markers like age, race, sex, family status, financial status, economic state, etc. There is a ridiculous amount of data on the internet that can be mined free and easy.

Making sure your business is properly positioned to take advantage of your arket will ensure more long term success. The data is out there; you just need to know how to bring it into your analytics process.

The third pillar is Customer Insights. With the boom in social media, most small businesses have not figured out how to capture and analyze all the information being published and shared about their business.

Customer Insight analysis allows a business owner to stay on top of problems and identify how customers feel about their business quickly.

We all know how quickly things can go viral and having a good tool to capture customer sentiment in social media is generally the most overlooked aspect of running a small business.

Positive and negative reviews, trending items, number of likes, follows and shares, are all items that can be rolled into customer insights. You can combine this with surveys, focus groups and loyalty programs among other things to get a full picture of your business.

If you are a small business owner, decision-maker or analyst then focusing on these analytics pillars will make all the difference in the world.

And the best part, is they are all free and easy to bring into your business.

Small Business Analytics – The field of small business analytics is just starting to blossom as companies are looking for more data-driven decision-making to prosper in the age of Big Data. DMAIPH is at the fore front of providing analytics training, consulting and outsourcing options to small businesses. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to set up a free consultation on how to get more analytics in your small business.

 

 

 

 

Big Data Analytics: Using Business Intelligence Tools – 7/11/17 in Ortigas

A good analyst uses Business Intelligence Tools like Batman uses devices stored in his utility belt.

Per Wikipedia, business intelligence (BI) tools are “a type of application software designed to retrieve, analyze, transform and report data for business intelligence. The applications generally read data that have been previously stored, often, though not necessarily, in a data warehouse or data mart.”

Knowing what business intelligence tool to employ to what data set in order to conduct analysis and present your findings requires a thorough understanding of what tools are available and what they can do.

The key general categories of business intelligence applications include:

  • Spreadsheets
  • Reporting and querying software: applications that extract, sort, summarize, and present selected data
  • Online analytical processing (OLAP)
  • Digital dashboards
  • Data mining
  • Process visualization
  • Data warehousing

By far the most common business intelligence tool used is MS Excel. Having at least a intermediate masterly of Excel is a good start in understanding how business intelligence tools work.

Learning to run formulas, insert pivot tables and produce simple visualizations using charts and graphs give a foundation in how to take data and do something with it to inspire analysis.

Using Excel also teaches you how data needs to be structured, formatted and managed. You can’t run even basic analysis activities if your data is not encoded in a way that your tools can make sense of.

Once you have mastered the use of Excel then the logical next step is using BI tools that pull data from Excel. For example, Tableau is a BI tool that can extract data from Excel to build more powerful data analysis and visualizations.

BI tools can also be used to mine data from large data storage systems like data warehouses, data lakes and data marts. Again, understanding how data is structured in important. Knowing how queries are written (for example in SQL) to extract data is important.

If you are looking to get a better understanding of what tools you should be using to analysis the data in your business, you can join my next training seminar (July 11, 2017) in Ortigas.

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

The Analytics of Project Measurement

Peter Drucker perfectly summed up why big corporations rely so heavily on analytics when he said “What gets measured, gets managed.”

A successful analyst is able to remove the noise when analyzing data and isolate what matters to his or her organization.

With most companies collecting large amounts of data, you need to be both talented and disciplined to pinpoint key insights that can yield value.

In the corporate world, business analytics is widely use to track, analyze and report Key Performance Indicators (KPIs).

KPIs are rolled up to senior leadership to drive business strategy, identify and mitigate risk and to optimize operational productivity.

This approach is very similar to the way projects in the Measurement and Evaluation are tracked, analyzed and reported.

I would define measurement simply as the act of measuring to ascertain the impact, size, level of success, etc. of a specific data set.

There are many components to measuring projects making sure the project is on schedule, stays in scope, is not over budget, the quality of work is up to par, the end goal of the project remains relevant, and finally if the project is ultimately deemed a success.

A foundation in analytics will contribute to a more optimal and efficient process of measurement. Like businesses do with KPIs, you should start will identifying that are the key measurements your project will be judged on.

Once you know those data points, then figure out how to collect them, analyze them, and report them.

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At each step you can look for new data, validate existing data and blend data from other sources to add value to your measurement efforts.

Once you get to the reporting phase you can look for cutting edge techniques in data visualization and interactive reporting like dashboards to help educate and empower your audience.

That is how it is done in the corporate world where business analysts boil down massive amounts of big, often unstructured data into a few bullet points that allow decision-makers to take action.

When it comes to the Measurement of Project Evaluation, understanding various analytics solutions can make all the difference.

Analytics Education – Facilitating a mastery of the fundamentals of analytics is what DMAIPH does best. All across the world, companies are scrambling to hire analytics talent to optimize the big data they have in their businesses. We can empower students and their instructors with the knowledge they need to prepare for careers in analytics. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly so we can set a guest lecturer date, On-the-Job Training experience or other analytics education solution specifically tailored to your needs.

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.

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.

The Analytics of Measurement and Evaluation

By taking inspiration from the way corporations use business analytics to optimize their Big Data, our Program Measurement and Evaluation processes can be greatly enhanced.

To understand the connection, let’s start with the mission of the Measurement & Evaluation program.

“The ability to effectively evaluate projects, programs and processes is becoming increasingly essential to organizational success today. American University’s online Master of Science (MS) in Measurement & Evaluation provides you with the knowledge to lead these evaluation efforts and the technical skills needed for analytically demanding roles in upper management.” 1

A good analytics solution constructs a universal framework for collecting, analyzing and utilizing data to determine project effectiveness and efficiency.

Likewise, an efficient measurement and evaluation of projects, programs and policies using analytics should ensure success. An analytics centered approach will likely work with corporate, non-profit and governmental organizations across various sectors and industries.

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We can look specifically to two key business analytics concepts I have used in my twenty plus years of analysis work; Key Performance Indicators (KPIs) and Data Visualization. The key to my success was my ability to answer important business questions using analytics.

Analytics is generally defined as the discovery of patterns in data that provides insight and identifies opportunities. As Carly Fiorina, former CEO of HP said about analytics, “The goal is to turn data into information, and information into insight.” 2

Organizations that invest in analytics generally make much better business decisions then one’s that don’t. In fact, IBM found that organizations who use analytics are up to 12x more efficient and 33% more profitable. 3

In the corporate world, business analytics is widely use to track, analyze and report Key Performance Indicators (KPIs).

KPIs are rolled up to senior leadership to drive business strategy, identify and mitigate risk and to optimize operational productivity.

This approach is very similar to the way projects in the Measurement and Evaluation are tracked, analyzed and reported.

So we need to ask ourselves, what are the KPIs for the project, program or process we are measuring? What points of data need to be captured, analyzed and reported to determine success?

A successful analyst is able to remove the noise when analyzing data and isolate what matters most to his or her organization. That is what is at the heart of measurement, knowing what data is important and what is not.

Once we have the right data, we can measure what the data tells us to determine success, causality, impact… whatever the outcome may be.

A quote often attributed to management guru Peter Drucker perfectly sums up why big corporations rely so heavily on analytics when he said “What gets measured, gets managed.”

Similarly, policy decisions can be made based on what is measured. Project funding can be impacted by what is measured. Process optimization can be directed by what is measured.

Once we are able to measure what is truly important to policy-makers, managers and decision-makers, we need to make sure we present the data in a compelling way.

This is where data visualization comes in.

I often make the analogy that if a picture is worth a thousand words, then a good pie chart is worth a thousand rows of data.

We all know that most people learn more by seeing something then by reading or hearing it. Data visualization takes that a step further.

Data visualization is not only important to presenting our insights but also for exploring the data for insights. Most people find it easier to process information when it is in the form of a picture then a collection of data.

Chip & Dan Heath, Authors of Made to Stick, found that, “Data are just summaries of thousands of stories – tell a few of those stories to help make the data meaningful.”

The ability to take all of the data gathered in the measurement phase and use it in the evaluation phase will make a significant difference in the success of the project, program or process you are working on.

According to the Office of Planning, Research and Evaluation, “Program evaluation is a systematic method for collecting, analyzing, and using information to answer questions about projects, policies and programs, particularly about their effectiveness and efficiency”. 5

Data Visualization can be used to paint a picture of a program, project or policy that influences outcomes based on the KPIs. And by appealing to the basic human fascination with stories, a persuasive graph, chart or infographic can make all the difference in the world.

By adopting the business analytics concepts of KPIs and Data Visualization, and applying them to the world of programs, policies and projects, you can find the same level of success I found in the corporate world.

  1. American University, “Certificate in Measurement & Evaluation” http://programs.online.american.edu/online-graduate-certificates/project-monitorin Accessed October 20, 2016
  2. Carly Fiorina Speech from December 6, 2004 http://www.hp.com/hpinfo/execteam/speeches/fiorina/04openworld.html . Accessed October 20, 2016
  3. Simon Thomas, Senior Analytics Consultant for IBM https://youtu.be/Zi8jTbXnamY . Viewed October 20, 2016
  4. Chip & Dan Heath, Authors of Made to Stick, http://heathbrothers.com. Accessed October 20, 2016
  5. OPRE, http://www.acf.hhs.gov/opre/resource/the-program-managers-guide-to-evaluation-second-edition. Accessed October 20, 2016

Analytics Education – Facilitating a mastery of the fundamentals of analytics is what DMAIPH does best. All across the world, companies are scrambling to hire analytics talent to optimize the big data they have in their businesses. We can empower students and their instructors with the knowledge they need to prepare for careers in analytics. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly so we can set a guest lecturer date, On-the-Job Training experience or other analytics education solution specifically tailored to your needs.