Data Science and Big Data Analytics For Finance

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

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

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

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

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

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

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

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

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The Fundamental of Business Analytics – Business Analytics is the application of talent, technology and technique on business data for the purpose of extracting insights and discovering opportunities. DMAIPH specializes in empowering organizations, schools, and businesses with a mastery of the fundamentals of business analytics. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to find out how you can strengthen your business analytics fundamentals.

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APEC Data Science & Analytics Key Competency #1: Operational Analytics

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

By definition, a DSA professional uses data analytics and specialized business analytics (i.e. business intelligence) techniques for the investigation of all relevant data to derive insight in support of decision-making.

Operational analytics is made up of all the analytics processes within an organization that take data and transforms the data into actionable intelligence. In short, this is management reporting.

Without a doubt the most widely used form of analytics, management reporting is deeply ingrained into the culture of data-driven organizations.

I often liken management reporting to a pyramid. The bottom of the pyramid is the data or the base of decision-making in an organization.

The middle of the pyramid is the processes of operational analytics. Where the data is transformed.

The top of the pyramid is the decision-making. Managers need intelligence that comes in the form of insights. Great analysts deliver these insights in reports, dashboards and visualizations.

DMAIPH offers a wide range of analytics centric training solutions for professionals and students via public, in-house, on-site, and academic settings. We tailor each training event to meet the unique needs of the audience. If you need empowerment and skills enhancement to optimize the use of analytics in your organization, we are here to help.

Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to set up a free consultation to learn which of our DMAIPH analytics training solutions is best for you.

Actionable Management Reporting

Except from my upcoming book on analytics for the small business owner…

One question I get asked a lot is what should someone do when they know the data they are reporting and/or using in their analysis is not the best data available?

  • Typically, Excel and PowerPoint are the primary tools used to provide management reporting to a company’s leadership. In the past few years there have been major technology innovations in business intelligence applications and data visualization software that have taken management reporting to a whole new level.
  • Recruiting has seen a huge increase in number and types of reporting tools available to deliver very fast and very detailed recruitment analytics.
  • This leads up to the concept of a business dashboard… which we will get to later.

No matter what part of the business you work in, the first thing to do is to define the current Key Performance Indicators (KPIs) being used in decision-making.  Often right off the bat, some of the KPIs being reported aren’t even being used.

You can do a simple survey, asking end users to rank in order of importance the KPIs they get. Also ask if the ones at the bottom are even useful or should they be eliminated if no one is using them.

At the same time you should be working on understanding what computations go into each KPI. Often we just do simple counts, total and averages that mask more important data. On the flip side, we tend to over complicate things with extravagant weighing and scoring. Either way, we need to make sure we know exactly what is being reported and how does the final data point come to its end state.

The next step is to look at the data architecture to make sure there is nothing happening upstream that might impact the data we are using in the KPIs. Before making changes to the KPIs we want to have the full view of what happens before the data gets to the end user.

Now we are at the point where we can start experimenting. What happens when we swap out data points? Or if we change a variable in a calculation? Or we pull the data from a different source? The questions are endless. Pick a few, make some changes in a test environment and start sharing the updated KPI data. See if it has more value with the end users.

Again, this shouldn’t be hard. But of course in many organizations a lot of consequences can result from a simple change to just one KPI. Spreadsheets may have to be reformatted, review processes may have to be updated, and dashboards may have to be redesigned. But in the end, what is more important? Making decisions with crappy data or setting a standard to let the reporting process evolve as the business evolves?

This come back to my point earlier, changing KPIs is as much sales as it is analysis… that you have to be ready to share a story, back it up with data, and really influence the minds of senior management that updating the KPIs makes good business sense.

If you are at a point where you are trying to figure out what KPIs aren’t working anymore or you need help in building a business case to change some KPIs, let me know. I’m here to help.

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Business Strategy with Analytics – Aligning a business strategy to drive an organization forward requires a robust analytics solution. Businesses who have good analytics tend to be much more profitable and efficient then ones that do not. DMAIPH has helped dozens of companies in both the U.S. and the Philippines with adding more data analysis in their business strategy. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to find out what we can do to help you align your business strategy with analytics.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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.

 

 

Data Analytics Training on Feb 21

Did you know that most successful businesses have solid data analytics in place across their entire organization?

Organizations that invest in data analytics generally make much better business decisions then one’s that don’t.

In fact, IBM found a few years back that companies who use data analytics are up to 10x more efficient and 33% more profitable the ones who don’t.

By bringing data together data from across the business, companies can get real-time insights into finance, sales, marketing, product development and much more.

Data analytics enables each team within the business to collaborate, achieve better results and outsell the competition.

Join us on February 21, 2017 in Ortigas, and learn how to turn your business data into insightful and actionable analysis.

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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.