Big Data Analytics > The Art of Presenting Big Data



It has been my experience that presenting Big Data requires quite a bit of artistic ability.

I will be talk about the Art of Presenting Big Data among other topics at an event this coming February 21 in Ortigas.

For me there is a clear need to Apply a Process to Present Big Data Clearly
. This process has 3 parts.

  1. Selecting the Appropriate Presentation Format to Communicate Your Findings Effectively to Your Audience
  2. Mastering the Power of Enchantment
  3. Sharing Findings from Big Data to Drive Decisions Within Your Organization

Knowing How to Select the Appropriate Presentation Format to Communicate Your Findings Effectively to Your Audience is where we will stat.

To that end I have a checklist I use before every presentation I share involving Big Data:

  • Know Your Audience
  • Consider Time Constraints
  • How Will The Data Be Consumed?
  • Can The Data and Analysis Be Accessed?
  • Make it Interactive

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.

 

Can Analytics Help a Sari Sari Store?

I had this interesting conversation earlier about analytics.

I started explaining to the person I was sitting next to what I do and he asked can analytics really help any business?

Of course I said yes.

He asked even a Sari Sari store?

For those of you who don’t know much about Sari Sari stores, let me tell you a bit about them.

By far the most common form of self-employment in the Philippines are small, family operated convenience stores. Called Sari-Sari stores, there are an estimated 1 million Sari Sari stores across the Philippines. Per wikipedia, this counts for an estimated 30% of all retail sales in the Philippines.

Sari-Sari, which is Tagalog for variety, are an important economic and social pieces of just about every Filipino community. Most are privately run, family owned and are operated from the front of the owners house.

Commodities are displayed behind a large mesh screen to both allow customers to see what is available and to prevent shoplifting. The most common goods sold are candy, snacks and other non-perishable food items. Cigarettes and mobile phone cards are also popular items for sale. Household needs like soap, detergent and cleaning supplies are also common. Some stores have small refrigerators to offer cold drinks like soda and beer.

Sari-sari stores generally have higher prices when compared to supermarkets which is a tradeoff for proximity to their customers. It is also common to buy single units of a product versus an entire package as paying more to meet a quick need is valued over planning and budgeting bulk purchase over the long term.

Some Sari Sari stores also offer credit to neighbors. Micro lending of this scale is wide spread and generally done under the rule that if the credit is not repaid, the store owner will report this to the local government officials.

Some Sari Sari stores barter goods and services with farmer, fishermen and other businesses.

Most Sari Sari store proprietors buy their goods at supermarkets then mark up the prices for resale (on the average 20%). In some areas, businessmen make act a middle man offering bulk products to the Sari Sari store.

It is my belief that most Sari Sari stores can benefit from a simple strategic business plan and some very basic analytics.

My understanding is that Sari Sari stores operate on a very tactical level with little long term planning and operate with little market awareness.

If I ever to consult with the owner of a Sari Sari store, my initial approach would be to develop a business strategy plan and build a basic analytics process to gather data and provide a proof of concept.

This approach would be broken into the following steps:

  1. Business Strategy Assessment – How do they conduct business?
  2. Competitive Landscape – Who do they compete with?
  3. Demographic Profile – Who are their customers?
  4. Market Assessment – How much upside is in their market?
  5. Inventory Analysis – How to they optimize inventory?
  6. Facilities Assessment – Are they getting the most of their location?
  7. Risk & Security Assessment – What risks do they face?

I will flesh out each of these steps in upcoming blog posts.

Once I have complied data from these 7 steps, I can develop a business strategy plan unique to the individual Sari Sari store.

After my presentation of the business plan, I can make a determination if they Sari Sari store will enter Phase Two of the plan.

I would work with the proprietor store for a set period of time in a consulting role to determine viability of operations and if they meet our program standards (detailed later in this document).

In addition to offering a consulting solution, through my company, I can also offer additional services including cash management, accounting, marketing, inventory and fulfillment assistance, and other solutions as they arise.

Its my experience that the busiest Sari Sari stores offer something unique. Some might have an ice cream maker, or a special dish they prepare, or some have home baked goods. Regardless, they generally have something that sets them apart from a store that just offers traditional goods.

So, the final piece of my involvement would be cross selling our unique products to Sari Sari stores in need of a unique product to build their business around.

After that consultation, I would expect that three things would happen:

  1. the Sari Sari store proprietor would have a better grasp of a strategic business strategy.
  2. the Sari Sari store would increase profits and
  3. the Sari Sari store would expand its customer base and build up loyalty with existing customers.

So, to get back to the question… how can analytics help a Sari Sari store?

By applying some lessons from the corporate world.

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.

 

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.

 

 

 

 

Being A Great Analyst > Key Attribute #4 > Be Enchanting

If you are a good analyst or a decision-maker that uses analytics, being enchanting makes your job much, much easier.

One key to using data and analysis effectively is understanding how to enchant people by being likable, trustworthy and using data and analysis to further a great cause.

A few years back, I came across a book by Guy Kawasaki called Enchantment. It is my all-time favorite business book.

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Guy Kawasaki is a marketing expert and used to be Apple’s Chief Evangelist (aka Chief Marketing Officer). At Apple their goal is to convert customers to being loyal to Apple products for life.

In Enchantment, Guy talks about how Apple and other successful companies are able to create enchantment in their customer base that fuels passionate and long lasting relationships.

As an analyst there are many lessons that you can draw from Enchantment to being an incredibly impactful member of your organization.

One of the pillars of Enchantment is being Trustworthy. As an analyst, you have to be trustworthy for people to want to follow the direction your data and analysis point.

Your data has to be clean, valid, and accurate.

Your analysis has to be easy to understand, easy to replicate and easy to boil down into a few bullet points.

When you accomplish these things you are creating trust. Getting decision-makers to listen to what the data is telling them comes when the analysts have their trust.

That’s just one part of Enchantment. I use many examples of how to apply Guy’s concept to data and analysis in my training classes and in my company.

If you are looking for a way to add value to your company, which in turn can make the business more successful then this book is a must read.

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.

Being A Great Analyst > Key Attribute #3 > Be Decisive

If you are a good analyst or a decision-maker that uses analytics, being decisive is much, much easier.

One key to using data and analysis effectively is understanding how people make decisions and what impacts the ability to make unbiased decisions.

A few years back I came across a book by Dan and Chip Heath called Decisive. It was a fantastic read.

The Heath Brothers are marketing and management experts who do a lot of research into what works and what doesn’t in the business world.

Decisive looks at what influences effective decision-makers overcome.

As an analyst, there are many valuable lessons that can be applied to both selecting data and presenting the analysis of the data.

One example of being Decisive that I use a lot related to trying to avoid a narrow frame. Too often we limit our choices.

When it comes to what data to use to answer business questions, we have to always ask ourselves is this the right data? Is there other data I can use to validate my findings? What data can be blended with this data to tell a more compelling story?

Being aware of your own biases will help you ensure you get the right data, that it’s what is really need to answer business questions at hand.

Being of aware of the biases of the consumer of your analysis (generally your boss and their peers) can help you position your data in ways that can mitigate those biases and let them see what you see.

There are dozens of examples from Decisive that I use in training people to be analysts and in using analytics effectively.

It is a book, well worth your time.

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.

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.

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.

 

 

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.