The 10 Analytics Essentials of Entrepreneurship

A good friend of mine, Boom San Agustin, recently blogged about the essentials of entrepreneurship. Boom listed the 10 things most essential to be successful in setting up and running your own business.

This inspired me to put an analytics spin on each of the 10 points, showing how you can use data to augment each point.

  1. Have passion for what you do. One way to measure how much of your time you are devoting to your passion is to set a schedule and track how much time is devoted to everything you do each day. If you are happy with the % spent on passion projects then you are doing the right thing. But if too much of your time is spent on things you don’t like doing, then you need to make some changes.
  2. Pursue excellence first, money second. Here you need to do a lot of research and ask a lot of questions. You need a clear idea of what excellence in your chosen business looks like. How can you measure excellence with your products, your service, your team’s performance and engagement? Putting some key metics in place will allow you to make more informed decisions.
  3. Be open and honest with others and yourself. Get feedback. See what % of your client, customer, partner, team member, interactions are honest and endure honesty in others. Come up with a way to measure the trustworthiness of what you do.
  4. Have a “can-do” attitude. Keep a project list of all the things you need to accomplish. Update it every day. Be able to show yourself and others your progress towards getting things done. This will ensure that people see the work behind the words.
  5. Be the leader your team needs. Devote significant amounts of your time to your team. Keep them informed by blogging. Build tools for communication like newsletters. Be visible in person and in social media. Track the frequency of your engagements and correlate them to employee satisfaction surveys.
  6. Learn to communicate well. Get in front of an audience whenever possible. Engage the audience. Ask for feedback. Identify challenges and opportunities and then follow up. If your team doesn’t know what is going on in your head, then it is a problem. Gathering data on your communication strengths and weaknesses is key.
  7. Be a teacher and a learner. Facilitate as much on-site training as possible. Get involved in it. Train people yourself on areas you are good at. And then sit and listen to other experts in areas you are not. Track the time put into training and come up with a cost justification. Its easy to cut training when times are tough because its hard to assign a value to it. Make this a priority now so you always know the valued of training in your business.
  8. Have your ear to the ground. Stay engaged in person and on social media. Keep updated on trends affecting your business and your employees. Use a social media tool like Hootsuite to manage your social media messaging to get feedback all in one place. Lots of data points can be created and tracked to measure how close you are to the pulse of your business.
  9. Be dynamic and open to change. Set a check-in schedule. Encourage one on ones and team meetings that are not just one sided but empower sharing. If you are open minded and listen, you will be able to make changes to your business that keep things on the cutting edge. Use a timeline to show where you have been, where you are and project out where you are going.
  10. Know when to quit. We all fail. Businesses will all fail at some point. Winners know when its time to fail and walk away to do something else. Losers stay the course until they go down with the ship. Figure out what is the most important metric in your business. Sales, profit, engagement, risk potential… whatever it is. Figure out what is the lowest acceptable number, once you get close to it, be prepare and exit plan. If you pass it, face facts and pull the plug. Always have that data point at your fingertips.

If you are able to build in analytics like these, you will be able to manage your business well. You will set a tone among the leadership that uses data, not just the gut, to make decisions. One of your first hires should be a data guy who can build a business dashboard and deliver impactful reports. Someone who can help you identify risks and rewards and keep your focus on the metrics that matter most.


Analytics Leadership – DMAIPH 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 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.


Big Data Analytics and Business Intelligence

Enabling Your Business to Make Smarter Decisions

Are you tired of being under constant pressure to make the right number-based decisions for your organization?

Are you too often overwhelmed by an out-of-control flood of numerical information, much of it conflicting and confusing?

Big data is booming ast as organizations devote new technology resources to tapping the terabytes (if not petabytes) of data flowing into their organizations.

Today big Data is flooding into the business both through internal processes and externally via social media.

What does this all mean for business intelligence (BI) users and systems?

With all the attention on advanced analytics for big data, what’s the play for BI?

Integrating advanced analytics for big data with BI systems is an important step toward gaining full return on investment.

Advanced analytics and BI can be highly complementary.

Advanced analytics can provide the deeper, exploratory perspective on the data.

BI systems provide a more structured user experience through there richness in dashboard visualization, reporting, performance management metrics, and more can be vital to making advanced analytics actionable.

Recently on December 6, 2016 I was at Astoria Plaza, Ortigas Center, Pasig City for a dynamic and empowering one-day training on Big Data Analytics and Business Intelligence.

Course Description:

Make smarter business decisions using these powerful data analysis techniques

Information is supposed to make us smarter, but more often than not, it simply overwhelms us.

This program is for you if you feel like you’re drowning in data and unsure which data to use to drive your company initiatives.

The truth is that the amount of data available to help run your business is greater than ever before. To effectively use this information, managers must consider the practical side of big data…what matters to you is how do you grow and build a team to make smarter decisions.

Much of the information out there just discusses the promise of the data deluge. The challenge is not the volume of data but rather the judgment needed to use it.

This seminar goes beyond the qualitative side of data analysis to explore proven quantitative techniques and technologies for identifying, inventorying and integrating data, so that more informed and reliable business decisions can be made.

Learning Objectives

  • Apply Best Techniques and Cutting Edge Technologies to Organize, Interpret, and Summarize Quantitative Data
  • Create a Process to Analyze Data and Identify Patterns Not Apparent at First Glance
  • Reduce “Analysis Paralysis” and Go from Hard Data to Well-Reasoned Conclusions in Less Time

What Was Learned

  • Specific skills to effectively frame the problem you’re addressing to uncover key opportunities and drive growth
  • Critical marketing steps of orientation necessary before engaging tools and technology
  • How to simply and quickly amplify decision making by separating the signal from the noise
  • A framework for asking the right questions, allowing the ability to link analytics to business strategy

What Was Covered

  • Using data and statistics effectively in business today
  • Improper data manipulations and their consequences
  • Exploring quantitative data collection methods
  • Improving analysis success by effectively utilizing software
  • Understanding regression, trend lines, and scenarios in Excel
  • Utilizing the power of business intelligence software
  • Finding and analyzing data patterns, trends, and fluctuations
  • Interpreting and translating data into decisions

Who Attended

Over 80 business professionals who needed to learn more about the basic tools to quantitatively and accurately analyze the mountains of data that come across their desk each minute of every day.

Section One

Big Data—It’s Not Just Size

  • Describe the Importance of Effectively Analyzing Big Data in Business Today
  • Come up with a Data Map to Analyze the Big Data in your business.
  • Establish Clear Objectives When Analyzing Big Data
  • Recognize and Apply Various Data Collection Methods
  • Identify and Resolve Problems Associated with Data Collection
  • Discuss the difference between Data Warehouses and Data Lakes
  • Determine when to use Data Blending in your analysis

Section Two

Analysis—Using Business Intelligence Tools

  • Assess Your Current Analytics Culture
  • Describe the Issues and Trends in Today’s Analytics Field
  • Optimize your use of MS Excel for Big Data analytics
  • Discuss the concept of Data Visualization
  • Utilize BI Tools like Tableau Public
  • Build a Business Dashboard Prototype

Section Three

Interpretation—Assessing Results

  • Articulate the Importance of Accurately Interpreting Data
  • Determine and Analyze Risk, Uncertainty, and Probability
  • Spot Patterns, Trends, and Fluctuations Through Correlation, Regression, and Descriptive Statistics
  • Understand when to employ Descriptive, Predictive or Prescriptive Analytics
  • Build Data Models

Section Four

The Art of Presenting Big Data

  • Apply a Process to Present Big Data Clearly
  • Select the Appropriate Presentation Format to Communicate Your Findings Effectively to Your Audience
  • Master the Power of Enchantment
  • Use Findings from Big Data to Drive Decisions Within Your Organization

Too often people dive into the data only to be lost in haze of data.

This discussion will be pragmatic and immediately applicable to analysts, professional using analytics and managers of analysts across all industries.

Analytics Training – DMAIPH in partnership with Ariva Events Management, 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 or connect with me directly to set up a free consultation on which of our DMAIPH analytics training solutions is best for you.

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,

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.


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 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.