Help Me Pick an HR Analytics Topic…

I need your help. I am submitting a proposal to speak at an upcoming HR event being put on by my good friends at Ariva and need help determining which one sounds like the most interesting topic.

Option 1: Insightful HR: Integrating Quality Data towards Better Decisions

Most HR teams are surrounded by an almost limitless wealth of information locked inside business data. However, very few HR teams are consistently able to identify the right data at the right time and even fewer are able to integrate high quality data into the strategic decision-making process. The keys to data-driven decision-making are finding the right balance of analytics Talent, Technique and Technology. I will share a few of tips on how to align the 3 T’s in your business so that HR is able to empower data-driven decision making across the organization. For most HR teams, having good data is the easy part, distilling actionable insights is what makes all the difference

Learning Session Outline:

Learn how to Identify the right data
Discuss how to Inventory the data to gain actionable insights
Discover how to Integrate the data insights into HR decision-making
Unlock the analytics Talent needed for cutting edge HR Analytics
Reveal key analytics Techniques to analyze the data
Master the appropriate analytics Technology to optimize HR decision-making

Option 2: Driving Workforce Performance using Balanced Score Card Metrics and Analytics

Balanced Score Cards have been around since the 1990’s. HR teams across the globe have spent millions in trying to perfect ways to positively drive workforce performance based on metrics. So why is this still a topic of interest? Well, in most cases, it is because score cards and the metrics they report keep pointing us problems that are just not going away. Rising attrition, rampant job-hopping, and lower productivity are challenges we are all dealing with. In many cases, though the problem is not what we are reporting with our scorecards but the data we are populating them. As a whole, we are relying on metrics of the past to describe to us how we got here. What we need though is metrics of the future that accurately predict where we are going. I will share with you several of the metrics of the future I use for workforce reporting in my business and how we employ Predictive HR Analytics to optimize our scorecards.

Learning Session Outline:

Discuss HR Metrics of the Past
Learn about HR Metrics of the Future
Discover how to use HR Predictive Analytics
Design a Data-Driven Scorecard Template

Option 3: Strategic Problem-solving for Better Decision-making: Analytical and Critical Thinking in Motion

One of the biggest strategic challenges facing HR teams is transforming Big Data into actionable insights. The speed in which decision-makers need to act can often preclude the deep understanding of what value actual lies in the data. This causes misguided strategic planning and under informed decision-making across an organization. The best strategic solutions to quicker and more accurate decisions are found in a well rounded HR analytics approach. One that empowers critical thinking not just from the top, but down the ranks. Business Dashboards and Data Storytelling are two tools that should be used to quickly enable quick decisions in real time. I will show you how HR teams are able to keep one eye on strategic problem-solving while still taking care of daily challenges as they pop up.

Learning Session Outline:

Discuss the challenges of HR Big Data
Share HR Strategic Planning best practices
Learn how to get Real Time HR Data
Design HR Tactical Implementations using Analytics
Align HR with Organization-wide Problem-Solving and Decision-Making

Let me know what you think asap!

Thanks!

HR & Recruitment Analytics – The recruitment and retention of top talent is the biggest challenge facing just about every organization. You really have to Think Through The Box to come up with winning solutions to effectively attract, retain and manage talent in the Philippines today. DMAIPH is a leading expert in empowering HR & Recruitment teams with analytics techniques to optimize their talent acquisition and management processes. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to learn how to get more analytics in your HR & Recruitment process so you can rise to the top in the ever quickening demand for top talent.

Analytics for HR Managers (2 Day Training)

Deploy Big Data Analytics Solutions to Align HR with Organizational Business Strategy

Learning Session Description

Successful HR Managers are strategic planners and take decisions which are apt and considering all the facts. They also have a knack for metrics as these are essential in improvising various process in the organization and make data-driven decisions for the benefit of the organization.

Learning Session Outline

In the past few years, we have seen the importance of big data, analytics and data science grow at a dizzying pace. By using meaningful HR Analytics techniques, your recruitment and retention efforts can be greatly enhanced.

A recent Facebook job posting for HR Manager described the importance of Analytics for HR Managers. “We are looking for a visionary who gets excited about using data insights to drive HR related business decisions at all levels. The right candidate thrives on HR data, overseeing dynamic reporting and implementing actionable analysis within both HR and across the organization.”

New techniques like predictive analytics and data storytelling as well as new technologies like social networks, applicant tracking systems and business intelligence applications are fundamentally changing the entire talent management process from recruitment to retirement.

The pressure on HR Managers to deliver results has never been greater as they are required to demonstrate the return on investment being made into HR functions.

Building analytics centric teams and using techniques taught in this training session will empower more data-driven decision making across your HR organization from the top down.

Learning Session Objectives

To learn analytics techniques that will allow quicker, deeper and more impactful analysis of HR & Recruitment Big Data.
To be exposed to cutting edge technology being used in other companies to build HR & Recruitment business dashboards and design more powerful reports.
To assess the current state of analytics in your HR & Recruitment process and build a strategy to empower the greater use of HR analytics in your organization.
Understand the implications of Artificial Intelligence and Machine Learning in regards to HR functions.

Who Should Attend

This session is suitable to a wide range of professionals but will greatly benefit:

HR Managers and Recruitment Managers
Business Analysts working with HR and Recruitment teams
Senior Leaders who work closely with HR and Recruitment

Learning Session Process

Based on a Set of Key Data Science and Analytics Competencies developed by the Asia Pacific Economic Cooperation (APEC), our learning sessions are designed for HR Managers to use both in the Philippines and across the region.

Session One – HR Domain Knowledge & Application: Apply HR domain-related knowledge and insights to effectively contextualize data, achieved by practical experience and exposure to emerging innovations.

The Complexity of Multigenerational Workforces
Aligning the Brand between HR & Recruitment and Marketing
State of Data Science and Analytics in the Philippines

Session Two – Data Management & Governance: Understand data management strategies and governance, incorporating privacy, data security, polices and regulations, and ethical considerations.

The 5 V’s of Big Data
The 3 Tenants of Data Governance
Following Data Privacy and Security Laws

Session Three – Data Analytics Methods & Algorithms: Appreciate the processes used to capture, clean and inspect data for HR & Recruitment. Evaluate and implement data analytics initiatives to derive insights for decision making.

Finding the Right Data at the Right Time
Data Warehouses and Data Lakes
Blending Data from Across the Organization

Session Four – Data Science Engineering Principles for HR: Use analytics software to share findings and tell data stories. Develop analytic processes to improve HR operations.

Getting IT: the 3’s I and the 3 T’s of Data
Data Science 101: How to Build a Data Science Team
Data Storytelling Case Study: The Best NBA Team of All Time

Session Five: Computing Principles for HR: Appreciate information technology, computational thinking and utilize programming languages to design and develop data analysis processes and techniques.

Optimizing the use of MS Excel for HR and Recruitment
Defining KPIs Case Study: Google Project Oxygen
Working with the IT Team: Buy them Doughnuts

Session Six – Statistical Techniques for HR Data Analytics: Direct the application of statistical concepts and methodologies for data analysis including predictive HR analytics.

Predictive Analytics Case Study: HP’s Flight Risk Model
Tying Management Reporting to HR Analytics Models
Group Exercise: Build a Flight Risk Model

Session Seven – Operational Analytics: Use data analytics and specialized business intelligence techniques for the investigation of all relevant HR data to derive insight in support of decision-making.

Competitor Landscapes and Demographic Profiles
Overview of Business Intelligence Tools
BI Tools Demo: Tableau Public

Session Eight – Data Visualization & Presentation: Ability to create and communicate compelling and actionable insights from data using visualization and presentation tools and technologies. Build a HR Business Dashboard prototype.

Data Visualization Guidelines
Group Exercise: Build a Business Dashboard Prototype
The Concept of Enchantment

Case Studies and Exercises

We will use case studies and group exercises throughout the two-day class. In these activities, the group is divided into teams. Each team will analyze datasets using the principals learned in the various learning sessions. These exercises will also use elements from the case studies as we progress from finding data, to conducting analysis on the data and finally presenting the data.

Augment BPO

The Augment BPO Data Science and Analytics Advocacy Project (Augment BPO) is empowering BPO Companies, Executives, and Workers in the Philippines to prepare for and address the clear and present danger posed by Artificial Intelligence Chatbots (AI Chatbots) to BPO revenue growth and jobs through Data Science and Analytics strategy planning, awareness building and upskill training.

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

Global Chamber Manila: Filipino jobs threatened by Artificial Intelligence

For the past couple of weeks, digital transformation has been making headlines in the Philippines… finally!

A recent article from the Philippine Daily Inquirer has Senator Bam Aquino worried about Filipinos losing jobs to Artificial Intelligence.

Aquino, who chairs the Senate committee on science and technology, filed Resolution No. 344 that seeks to look into the government’s plan and initiatives to maximize the development of AI and other emerging technologies. Aquino says, “This early, we should be preparing for any eventuality that may occur when automation goes into full swing.”

Thus, we need to move very quickly to prepare! Don’t miss the Digital Transformation Summit on May 24-25. Save 15% on tickets with promo code: DTSBBDA15

Read the full news article: http://newsinfo.inquirer.net/894684/filipinos-losing-jobs-to-artificial-intelligence-bam-aquino-worried

DMAIPH hires, refers and connects Filipino analytics talent. The Philippines is at the center of the action when it comes to solutions to the global need for analytics.

Working with DMAIPH to find work, hire analytics talent or set up analytics teams will ensure you are tapped into the best of the best when it comes to analytics in the Philippines. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to find out how to take advantage of this booming opportunity.

Global Chamber Manila helps members get business done across metro areas!

We are a thriving and collaborating community of CEO’s, executives, and professionals growing business across 525 metropolitan areas. We leverage technology and our collective networks around the world to help member companies grow, reduce risk, be more productive, and succeed faster.

We are the only organization in the world with the mission to grow business from anywhere to anywhere while collaborating with every organization. We help companies, investors and business service providers around the world succeed.

Worried Your Call Center Job Might Be Taken by a Robot? You should be.

http://news.abs-cbn.com/business/05/12/17/bpos-gearing-up-for-impact-of-artificial-intelligence-on-industry

I shared this article on an FB group and got a lot of inquires from people who are indeed seeing an opportunity to move from a call center job to a Data Science and Analytics (DSA) job.

Most of the questions revolved around how to transition.

Want to get Data Science and Analytics Training. Not sure how, here are some tips!

Self-Teach a Skill. (YouTube has thousands of free resources)
Volunteer at Work. (Find out what skills are in demand in your company and ask if you can help)
Take a Training Class (there are a lot of public training classes out there, including some that DMAIPH does).
Read a Book (Experts share a lot… like my book Putting Your Data to Work: An Analytics Guidebook for Filipino Professionals)
Find a Mentor (Jedi Knights start as an apprentice, so do many analysts and data scientists)
Join a Group (there are a lot of meet up groups like Data Science Philippines you can use to network)
Go Back to School (a few dozen schools here in the Philippines are either already offering data science an analytics programs are kicking them off soon)
Follow a Blog. (Besides reading books, there are a lot of good ideas shared on blogs like mine, dmaiph.com)
Become a Member (join associations like aap.ph aka Analytics Association of the Philippines)

Another question that came up often was, “What should you learn first?”

Find a tool, technique or technology that is high demand and fits your interests and aptitude. The best way to find out what to focus on is do a job search for the kind of job you want and look at the requirements. For newbies some of the in demand skills are

SQL (the most widely used language used for data analytics)
Microsoft Excel (if you know pivot tables, simple formulas and can make decent visuals you will be in high demand)
Tableau (a free version called Tableau Public can be downloaded and is easy to learn)
R (the most widely used tool for predictive analytics and data science and its free)

And then a lot more people added me on FB, hoping to network and find new opportunities. Thats a good tip too. Networking is key.

jobspicture2 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.

Also if you own or manage a call center, we can help. In fact, DMAIPH has successfully set up Filipino analytics teams for over a dozen U.S. based businesses. Offering both virtual and office based teams that specialize in problem solving using data, new technology and analytics techniques is our strength.

Finding and empowering analytics talent is increasingly challenging, but we have mastered Surfing Into The Storm and can show you how to succesfully set up a team. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to learn more about how to set up an analytics-centric team in the Philippines.

Teaching Analytics: APEC List of Competencies

Teaching Analytics: An Instructor’s Guide to implementing the recommendations of Project DARE (Data Analytics Raising Employment).

APEC (Asia Pacific Economic Cooperation) hosted an event on May 4-5 bringing together over 50 analytics experts and visionaries from over 14 counties across the Asia-Pacific region to form an advisory group.

The APEC Project DARE (Data Analytics Raising Awareness) Advisory Group started with an agenda set to develop recommended “APEC Data Analytics Competencies.

There are still being finalized, but as of last week here is a high level of the competencies that we came up with:

Business and Organizational Skills

Operational Analytics: Use 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.
Data Visualization and Presentation: Ability to create and communicate compelling and actionable insights from data using visualization and presentation tools and technologies.
Data Management and Governance: Develop and implement data management strategies and governance, incorporating privacy, data security, polices and regulations, and ethical considerations.
Domain Knowledge and Application: Apply domain-related knowledge and insights to effectively contextualize data, achieved by practical experience (e.g. apprenticeships) and exposure to emerging innovations.

Technical Skills

Statistical Techniques: Apply statistical concepts and methodologies for data analysis.
Computing: Apply information technology, computational thinking and utilize programming languages and software and hardware solutions design and development for data analysis.
Data Analytics Methods and Algorithms: Capture, clean and inspect data. Evaluate and implement data analytics and machine learning methods and algorithms on the data to derive insights for decision making.
Research Methods: Utilize the scientific and engineering methods to discover and create new knowledge and insights.
Data Science Engineering Principles: Use software and system engineering principles and modern computer technologies, incorporating a data feedback loop, to research, design, and prototype data analytics applications. Develop structures, instruments, machines, experiments, processes, and systems to support the data lifecycle.

Workplace Skills

21^st Century Skills: Exhibit crosscutting skills essential for DSA at all levels including, but not limited too; collaboration, customer focus, communication and storytelling, organizational awareness, critical thinking, planning and organizing, problem solving, decision making, business fundamentals, awareness of social and societal awareness, intelligibility, cross cultural awareness, dynamic (self) re-skilling, professional networking, ethical mindset and entrepreneurship.

Once this list is finalized I will update you all.

My end goal is two fold, (1) to help craft a version of the competencies into an academic discipline that the Analytics Council can present to CHED for adoption and (2) to design a vocational education track to address the basic skills needed for entry level DSA work here in the Philippines.

Stay Tuned!

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

Chief Data Officer – The Data Geek in the Room

In his latest book Data Strategy, analytics guru Bernard Marr, discusses how to profit from a world of big data, analytics and the internet of things. Marr breaks down the importance of having a data strategy to ensure data-driven decision-making, improve business operations and to monetize the data in a business.

data strategy

One of the key takeaways from his book is the emerging role of Chief Data Officer. This is a separate C-Level Suite position form the more traditional Chief Technology Officer or Chief Information Officer as this person should serve as both an analytics cheerleader and data-driven decision-making champion.

Big companies have CDOs, but even smaller and medium sized companies need to have someone who acts in this role even if its not an official title. I often say that analysts have to not only analyze data, but be champions of using data for decision-making. They have to be the data cheerleaders to educate, enable, and empower the use of data and analytics across the organization.

There are six primary areas a CDO should oversee; (1) high level vision, (2) implementations, (3) data governance, (4) business opportunities, (5) data culture leader and (6) sees data as a commodity.

CDOs have to have either a seat at the C-Suite table or the ear of the top decision-maker in the company. They are the ones who make sure that data is properly channeled to the right people at the right time to ensure data-driven strategies.
CDOs have to be the one ultimately responsible for data project implementations. This is not an IT thing. IT should be involved, but not the owners of data and analytics.
CDO’s have to make sure good data governance is followed. Data has to be stored, secure and accurate.
CDO’s are the ones who have the task of discovering business opportunities and identifying risks. They should have access to all the data they need to do both.
CDO’s are the ones who consistently and clearly articulate the importance of data and the value of data-driven decision-making.
CDO’s see data for its monetary value. Data is a commodity that in itself can be used to not just help the company, but to generate revenue itself.

So if you have a Chief Data Officer, or just a chief data geek, you are on the right path. If you don’t have one of these in your organization then your organization are likely going to be left behind.

may 17-18 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.

The Rock Stars of Data: Big Data Analytics & Data Management

How to master big data analytics and data management?

The Rock Stars of Data: Big Data Analytics & Data Management

2-day Class: Big Data Analytics and Data Management

June 27-28, 2017

Discovery Suites, ADB Ave., Ortigas Center, Pasig City

9AM-5PM

Rock Stars of Data Series: Big Data Analytics & Data Management

Data Rock Stars Dan Meyer (DMAIPH) and Dominic Ligot (Cirrolytix) have joined forces to offer a unique training focusing on both the Analysis and the Management of Big Data.

To find out more about our next scheduled public learning session on May 18-19, 2017 in Ortigas or to set-up an in-house training, send an e-mail to analytics@dmaiph.com

Learning Session Description

Building The Data Value Chain. Data is pervasive – everything we do in the modern world uses and generates data in some shape or form: from web sites we surf, the social media we consume, to the mobile devices we use to connect and communicate. Modern businesses also use and generate data, from financial data, to customer data, to transaction data and sensor data.

But data is only a raw material. Regardless of amount, the real importance of data is only determined by the value people and businesses derive from it. Getting data is the first step. Then the challenge becomes transforming the raw material into a processed good: information. Information enables decisions, and decisions create value.

This session is about the basics of transforming data into information: the data value chain. Attendees will learn how to identify the right data, about how data can be efficiently stored, then transformed into a friendly form for analysis, and finally how data analysis can yield insights.

This seminar will lightly touch on each aspect of data identification, collection, storage, transformation, and analysis and involve hands-on use of common data management and analysis tools such as Excel, Tableau and SQL, but is designed for those with little to no prior experience with these tools.

Learning Session Objectives

Apply cutting edge technologies to organize, interpret, and summarize Big Data in your business.
Create a process to analyze data and identify patterns not apparent at first glance
Understand the components of The Data Value Chain: Ingestion, Storage, Transformation, Analysis – and how they are all important to deriving value from data.
Learn database manipulation and processing basics using the Structured Query Language (SQL)
Connect a data analysis tool such as MS Excel or Tableau to a database to be able to perform analysis on processed and stored data

In this session, your organization will be able to use:

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

In this session, your participants will be able to:

Learn the best practices for organizing, summarizing, and interpreting quantitative data
Create a repeatable process for analyzing your data
Shorten the time between analysis and action to avoid “analysis paralysis”
Know how to get from hard data to well-reasoned conclusions

Who Should Attend

Business Analysts, Data Analysts and other Analytics Professionals
Business professionals who are involved in day-to-day analysis of data.
Data analysts who are already performing analysis using spreadsheets but struggle with manual data processing.
Managers of analysts or staff who spend a significant amount of their time collecting, analyzing and reporting data.
IT and Development Staff that work closely with business leaders and decision-makers.

Section One – Big Data—It’s Not Just Size That Matters

Understand the 3 T’s of Analytics: Talent, Technique and Technology.
Describe the importance of effectively, analyzing big data in Business today.
Develop a Data Map to analyze the Big Data in your Business.
Recognize when to employ Descriptive, Predictive or Prescriptive Analytics.
Establish clear objectives when analyzing Big Data.

Section Two – Assess Your Current Analytics Culture

Define What Is an Analytics Centric Culture.
Describe the issues and trends in today’s analytics field.
Discover how to find the most important KPIs.
Learn how to build better management reports.
Optimize your use of MS Excel for Big Data Analytics

Section Three – Using Business Intelligence Tools

An overview of BI Tools.
Tableau Public Demonstration,
Discuss the Concept of Data Visualization.
Build A Business Dashboard Prototype.
Apply a Process to Present Big Data Clearly.

Section Four – Interpreting Your Data and Analysis

Articulate the importance of accurately interpreting Data.
Determine how to validate your data analysis.
Mitigate and analyze Risk, Uncertainty, And Probability.
Spot patterns and trends through Statistical Analysis.
Use findings from Big Data to Drive Decisions within your Organization.

Section Five: Presenting the Data Value Chain and Databases

Discuss the components of The Data Value Chain and the various users and roles involved in transforming data to value: Database and ETL engineers, Data analysts, Business users.
Learn about basic data architecture and the role of databases in processing data.
Understand the basics of databases, tables and views.
Learn about the Structured Query Language (SQL) and SELECT statements.

Section Six: Data Processing with SQL

Discuss the additional value that can be derived from using SQL for Data Processing.
Go into detail on various ways of processing and preparing data using SQL.
Learn about aggregates, conditions, how to join tables, and run queries within queries.

Section Seven: Accessing SQL Tables with Excel

Learn about Open Database Connectivity (ODBC) and how Excel uses ODBC to connect to external data sources.
Discover how SQL tables and views can be read by Excel into instant Pivot Tables and Pivot Graphs.
Understand how changes in database table or view via SQL Inserts, Deletes, and Updates are reflected on Excel.

Section Eight: Performing analysis of SQL-based data using Excel

Learn about how SQL data can be dissected using the Data Analysis functions in Excel.
Talk about form tools and macros that can automate manual reporting.
Discuss tips for reporting and sharing the results of your analysis.

Minimum Hardware and Software Requirements.

Laptop with Intel Core i3 and 4GB RAM.
Windows OS with Excel 2007 or greater.
ODBC and database connections will be provided during class.

Case Studies and Exercises

Dan and Doc will use case studies and group exercises throughout the two-day class. In these activities, the group is divided into teams. Each team will analyze datasets using the principals learned in the various learning sessions. These exercises will also use elements from the case studies as we progress from finding data, to conducting analysis on the data and finally presenting the data.

Learning Investment for 2-day Seminar:

Exclusive Offer!!

Early Bird Rate

P 12,000.00 + VAT

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

Group Rate (Minimum of 5)

P13,000.00 + VAT

Regular Rate:

P 14,600.00 + Vat

(starting April 21, 2017)

All investments includes: 2-day Analytics Seminar with two of the most in-demand Analytics and Data Management Guru in the Philippines, complete with Training Materials, AM/PM Snacks, Lunch and Certificates.

ABOUT THE SPEAKERS

Dominic Ligot, Data Scientist

Doc’s areas of expertise focus on Fintech, Big Data Analytics, and Digital Transformation.

Click here to see Doc’s full speaker/trainer profile >>>

Daniel Meyer, Analytics Champion

Dan specializes in a variety of analytics themed training and speaking option including HR& Recruitment Analytics, Data Analytics, Data-Driven Decision-Making and Analytics for CEO’s.

Click here to see Dan’s full speaker/trainer profile >>>

Reserve your seat here >>>

Philippine BPO’s urged to prepare for Artificial Intelligence

Sharing from the Global Chamber® Manila Newsletter

April 7, 2017

Philippine BPO’s urged to prepare for Artificial Intelligence

An American technology and business expert urges Business Process Outsourcing (BPO) companies to prepare for the disruption that will be brought about by artificial intelligence (AI). The Department of Science and Technology (DOST) recently held a talk about how to prepare for the time when intelligent computers take over call center agents’ jobs.

Dr. Ted Ladd, who is on a lecture tour of the Philippines, says the technology for artificial intelligence is already here. While some experts say AI’s impact on BPO’s will be felt in five years, Ladd says BPO’s and entrepreneurs should already be preparing for this and start looking for new opportunities that will be opened up by AI. According to Ladd, “We don’t have to wait for the industry to show cracks before entrepreneurs prepare new solutions.“ AI is not just going to create new products or services but will create new business models which entrepreneurs could take advantage of.

DMAIPH is working on a new learning session offering entitled Surfing Into The Storm; A Guidebook on How to Turn Your Call Center into an Analytics Hub. Stay tuned for more info on the upcoming course.

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You can also catch the topic on Augmented Intelligence: Robotic Process Automation in BPO at the Digital Transformation Summit on May 24 & 25 at SMX Aura Convention Center, BGC

As a founding member of Gloabl Chamber Manila, DMAIPH specializes in a variety of analytics consulting solutions designed to empower analysts, managers and leaders with the tools needed for more data-driven decision-making. We have helped dozens of companies get more analytics in their business. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly so we can tailor an analytics solution made just for your unique requirements.

Decision-Making with Data Learning Session with Ariva Events

This coming Friday, March 31, in Ortigas, I will be Data-Driven Decision-Making for Executives, Managers and Leaders. I will focus on proven strategies of data mastery go a long way to becoming a Data-Driven Leader.

This master class is for you if you feel like you’re drowning in data and unsure which data to use to drive your companies decision-making processes.

Information is supposed to make decision-making faster and easier, but more often than not, it simply overwhelms our ability to accurately use the data we have in our business.

The truth is that the amount of data available to help run your business is greater than ever before. To effectively use this information, exeuctives, managers and leaders must consider the practical side of big data and how best to use it to make better decisions…because 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 learning session is specifically designed for executives, managers and leaders to learn techniqeues that will ensure reliable business decisions can be made based on the massive amounts of data at your fingertips.

Through a series of case studies, exercises and interactive lecture, we will cover the following:

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

Attendees will also be able to learn how to do the following things for their team:

Learn the best practices for organizing, summarizing, and interpreting quantitative data
Create a repeatable process for analyzing your data
Bring out patterns in data that were not apparent at first glance
Identify and explain tools for data analysis
Shorten the time between analysis and action to avoid “analysis paralysis”
Know how to get from hard data to well-reasoned conclusions

There are still seats available, contact me at danmeyer@dmaiph.com so I can connect with you my events partner, Ariva.

http://www.ariva.com.ph/data-driven-decision-making/

Stone Age Analytics

I was chatting with a friend about Peter Drucker’s famous quote, “Culture eats strategy for breakfast.”

He made a point that made me think this lesson is still hard to actually put into practice even though it’s a 50+ year old concept. In fact the idea that a good culture is more important than a good strategy is as probably as old as man.

My reply was the best run caves where probably run by the caveman with the most efficient hunters and gathers, who felt a common purpose that their leader empowered in them.

In many senses, analytics has been around since day one. Even before we had basic math, just by observation cave men that survived told stories to explain where the best hunting grounds where and things like saber toothed tigers are bad for your health.

Centuries before Lean and Six Sigma, human engaged in process improvement. And Im sure the smartest cave man (or woman) in the cave ended up being the data guy who did some kind of simple analytics to advice the chief on who was the best hunter and who was the best candidate to use as bait to stampede a mammoth into a box canyon.

My point is, analytics is not anything new. In fact most businesses don’t have good analytics because they think its too complicated and too expensive. Now maybe employing a data scientist to build a state of the art predictive modeling tool, is a bit to Space Age for some, but everyone needs to have at least Stone Age Analytics.

That’s where DMAIPH comes in. We specialize in helping companies who feel like their analytics are stuck in the Stone Age evolve.

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