cellphone with SafePass app in it

DOT launches SafePass app to help businesses under new normal

Metro Manila (CNN Philippines, June 3) — Tourism-related establishments can now count on an application called SafePass to operate under the new normal that was launched by the Department of Tourism.

"It basically provides digital solutions, no, pagdating sa space capacity planning, no, ilan ba pupwedeng pumasok diyanyung contact tracing, no, to make sure that we're able to monitor yung movements ng ating mga customers doon sa establishment, sa restaurant, and then yung protocol enforcement," said Tourism Undersecretary and Spokesperson Benito Bengzon Jr. on CNN Philippines' Newsroom Ngayon.

[Translation: It (The app) basically provides digital solutions when it comes to space capacity planning, as in how many people can actually come inside (an establishment); contact tracing, to make sure that we're able to monitor the movements of customers in the establishment and protocol enforcement.]

The agency launched the app with the Department of Trade and Industry and inclusion-tech venture Talino Venture Labs "to meet the new normal in a post-lockdown or post-pandemic scenario," said Bengzon.

Through SafePass, establishments will be able to determine their maximum capacity provided social distancing requirements are in place, explained the official. Meanwhile, customers may use the app to help map out their visit to their establishment of choice.

"Pagdating naman dun sa booking, pupwede tayong pumunta dun sa app tapos alamin natin kung ano oras ba tayo pupunta dun, ilang tao tayo, and you know, we will be able to get information if we can be accommodated. So nawawala dito ngayon yung problema na pagpasok mo dun eh siksikan pala, hindi ka makapasok," Bengzon said.

[Translation: When it comes to booking, we can go to the app and check what time may we proceed (to the establishment), what is our headcount (going there), and you know, we will be able to get information if we can be accommodated. So this eliminates the problem of (the establishment) already being crowded once you get there, preventing you from getting inside.]

Given that the app is able to benefit establishments and customers, Bengzon said they expect users to avail of its services.

SafePass helps to build trust and confidence with everyone who matters to your business. It enables you to better implement social distancing rules and ease crowds within your physical space while empowering you to deliver the best experience for everyone who walks through your doors.

Designed for bigger businesses, SafePass Enterprise offers powerful features and various options for customization. Learn more about SafePass Enterprise.

"On the part of the establishment, nam-manage mo yung pagpasok ng mga turista at tsaka nasisiguro mo that during the entire operating hours, meron kang kliyente. On the part naman of the customers, sigurado ka na maa-accomodate pagpasok mo dun," he explained.

[Translation: On the part of the establishment, you're able to manage the entry of tourists and ensure you have clients all throughout your operating hours. On the part of the customers, you can ensure you will get accommodate upon entering (the establishment).]

The app also contributes to the ongoing shift to cashless, contactless transactions, with the pandemic forcing the public to reduce as much physical contact as possible, Bengzon said.

At present, hotels are the only tourism business permitted to operate at limited capacity. They may only accommodate overseas Filipino workers, overseas Filipinos, workers in essential businesses like business process outsourcing firms and banks, and medical frontliners, the official said.

Meanwhile, restaurants in general community quarantine (GCQ) areas are restricted to take-out and delivery options. However, those in modified GCQ areas may already provide dine-in operations but only at half their capacity.

SafePass was co-developed by Talino Venture Labs and digital transformation leader Amihan Global Strategies. There's an enterprise-level version called SafePass Enterprise which delivers the right balance of flexibility and ease of implementation for bigger businesses. Learn more about SafePass Enterprise.

This article was originally published in CNN Philippines on June 3, 2020.

A photo of a cellphone with the Zoom app being installed and an open laptop

3 Factors for an Adaptive Culture During The COVID-19 Pandemic

Before March, we were given a 1-day work from home (WFH) privilege as the news of growing COVID-19 cases came in. On March 2, our 1-day WFH increased to 3 days. Then the number of confirmed cases multiplied. Company management then announced a full week WFH by March 9. Three days later, the government announced the Metro-Manila community quarantine would start on March 15.

In my head, I asked myself, “what will happen now?” Events were happening so fast and the only clarity was uncertainty.

The restrictions imposed by the quarantine did not make a huge difference in how Amihan would operate through the pandemic. With offices spread across the country, Amihan’s operations are mostly set up to mobilize digitally -- our meetings can be done online, documents are shared and signed digitally, and solution developments are delivered virtually. Employees can choose to work at home as long as they can deliver on projects. Our offices are open spaces where we can sit anywhere and work with our laptop. Solutions architects, software engineers, analysts, designers, and project managers - everyone is enabled to do their work remotely.

As for me, I manage client and partner relationships at Amihan where face-time meetings and handshakes are important. While I can complete many of my deliverables remotely, the main challenge for me in this quarantine is building and nurturing relationships with customers. I found it a tough situation to be in.

About 3 months after the quarantine, the situation is still full of uncertainty. The main difference we can see is how we’ve coped and have adjusted our working norms relatively quickly. It wasn’t exactly a smooth transition but we have noticed 3 Adaptive Culture Factors that have contributed to Amihan’s ability to adapt to the current paradigm.

Transparency. In the first week of the Enhanced Community Quarantine (ECQ), we started our bi-weekly company stand-up meetings, a time for the leadership team to give announcements and project updates, at the start and end of each week. Initially, the announcements were mainly related to the quarantine situation and served as a venue to raise concerns on the matter. This gave a heightened level of assurance for everyone, knowing that the company is prioritizing its employees’ welfare and would continue to improve its status based on various changing factors, such as government announcements, health bulletins, and employee feedback. Eventually, the stand-up meetings included team accomplishments to celebrate on, targets to push for, and project highlights. Unlike our previous experience of working as separate teams, these meetings allowed us to show greater appreciation for the work all our colleagues put in.

Employee Engagement. While nothing beats socializing in a shared physical space, the Human Resource and Marketing teams took the opportunity to keep social connections alive and even level up employee engagement through weekly Amihan Virtual Parties (AVPs). They have hosted fun quizzes, insightful fitness talks, engaging coffee chats - all of which have become one of the items in my calendar that I look forward to. This promotes a fun atmosphere to interact with colleagues virtually. It’s also amusing to learn about colleagues you didn’t know but now notice because of the skills and knowledge they have. Moreover, it’s an enjoyable experience to see when even the bosses join the games and are as competitive as everyone else!

Valued Feedback. It was encouraging to know that Amihan’s leadership listened to employee feedback and suggestions as part of the solution building process. The concerns raised during Q&A sessions were noted and we did surveys where challenges were identified, such as intermittent connectivity and domestic distractions. The results of the surveys were also shared and presented, creating a conducive environment for us to voice our concerns and share ideas to create a better virtual workplace.

At Amihan, we believe conducting digital transformation is not just about the technology, but more so about developing the right culture. Being empowered by technology, along with using these Adaptive Culture Factors, enabled Amihan to quickly respond to the pandemic There’s still plenty of room for improvement and that’s the beauty of it - the learning never stops.

There’s an image going around social media with the question “Who led the digital transformation of your company?” Was it 1) CEO 2) CTO or 3) COVID-19? It’s funny because it is true. The pandemic accelerated the realization that we need to digitally transform to swiftly adapt to evolving situations. As Charles Darwin said, “It is not the strongest of the species that survives, nor the most intelligent, but the one most responsive to change.” I believe the same applies to any organization.

Haifa Carina is a Business Development Manager at Amihan Global Strategies. She also leads various initiatives for the Philippine tech community, volunteers for DEVCON Philippines and curates for Startup Digest Philippines. Connect with her on LinkedIn. 

Photo showing employee wearing mask as businesses reopen in next normal

Reopening the Economy Safely in the Next Normal

Reopening safely, next normal is here

Businesses are dealing with the economic and health challenges arising from the COVID-19 pandemic. Priority is to re-open, however, we must all remain vigilant as restrictions are eased. Contact tracing remains very much significant in the fight against COVID-19.

Without a vaccine, it is clear that re-opening the economy will necessitate the implementation of protocols to minimize health and safety risks as well as protocols for contact tracing.

How can businesses re-open and operate safely in this next normal?

Build an enhanced health and safety plan for employees and customers.

While there are pre-requisites from the Department of Trade and Industry (DTI) and the Department of Labor and Employment (DOLE) on workplace prevention and control of COVID-19, which include the provision of face masks and the implementation of physical distancing by a distance of at least one-meter radius space, businesses would benefit from implementing a more robust set of health and safety measures.

For example, businesses may deploy scheduled work-hours and capacity planning to ensure proper social distancing within the workplace. In Amihan, we will be utilizing SafePass to manage access to our offices. SafePass’ Scheduling and Capacity Management features allow business owners to do capacity planning based on a particular schedule. Depending on one’s SafePass’ subscription plan, a business owner will have access to basic to customizable options relative to schedule and slot types, as well as have the flexibility to set maximum capacity per slot (defined) per day.

Together with the proper management of walk-in registrants, SafePass will help in implementing social distancing rules.


Photo of SafePass and businesses reopening after lockdown in Philippines


Having these things automated and digital eases the burden on businesses, which have to balance the need for safety measures with a comfortable/convenient experience for its employees and customers. All a visitor or an employee would need is his / her SafePass QR code or ID to get access or entry to a particular location.

Imagine this: you run a building and given the modified enhanced community quarantine, a few offices have started to re-open and their employees are now coming back to the office premises. If everything were done manually or paper-based, how would you know when employees will arrive at the building? Will you be calling each tenant and asking for a list of their employees who will be going to the office? Just how much time will this effort entail? How will you know how many employees will be arriving at a specific time slot? How will you be able to manage social distancing if and when a lot of people suddenly start to arrive?

You’ll probably experience an influx of employees coming in during the morning, and security personnel will probably be challenged with enforcing social distancing at the lobby. Or you’ll have people waiting longer than usual given the safe distancing rules that need to be implemented, for example, only 4 people can occupy and ride the elevator at one time.

Of course, implementing SafePass wouldn’t come without challenges. Just like any technology, it will need some “time to get used to” and proper training on its use for it to be successfully deployed.

Make (your) business more predictable by gathering data digitally (digital onboarding).

If you run a supermarket and you know how many customers will come in on a day-to-day basis and at what time, then you will be able to serve these customers better once they enter through your doors.

You may also be able to predict how long each customer will shop, as well as be able to replenish inventory better. All of this information and insights -- they will not be automatically and immediately available though, but when you have a way to easily and consistently gather data, look at and analyze your data -- it will help you.

SafePass has this Guest Reservation feature which will allow end-users to register and schedule their visit with your business (your establishment). Amihan team members will be fully utilizing this feature so our employees can book their schedules before they visit any of our offices.

Implement contact tracing quickly and more efficiently.

Just a few days ago, the Philippine government had announced plans to hire 136,000 contact tracers to help the Department of Health (DOH) with its efforts in combatting the spread of the virus.

It would help a lot of businesses can aid in this effort.

Contact tracing is the process of monitoring people who have come into close contact with a person who is infected with a virus, according to the World Health Organization. It’s broken down into three steps: Contact Identification, Contact Listing, and Contact Follow up.

Now after having read about contact tracing, while it is the “key to reopening businesses and resuming some form of normal life,” it remains a mess as much as a challenge.

Speed is critical for contact tracing. The more contacts a person has had, the higher the chances that they may have already passed the virus to another person. If we (and I mean both the government and private sector) can shorten the time for contact tracing then we can improve containment.

SafePass’ online and exportable reports plus multi-level filtering capabilities help to speed up and improve incident management. SafePass takes out the tedious task of having to go through paper-based logbooks and to a certain extent, cross-checking of data manually.

End Note

Newer quarantine measures will take effect on June 1, but are businesses ready for this next phase -- this next normal?

There are two things that resonate every time we talk about SafePass: courage and confidence,” Executive Chairman Winston Damarillo had shared when we launched SafePass last week.

Gusto nating bigyan ng lakas ng loob ang ating mga negosyo para magbukas, at gusto nating bigyan ng tiwala ang ating mga consumers at pumunta at [tangkilikin ang] ating mga businesses (We want to give our entrepreneurs the courage to reopen, and we want to give our consumers the confidence to go and patronize these businesses).”

While Amihan team will still be on full telecommute in the next weeks, some of us will have a need to work in our offices. Leadership is committed to employee safety and that’s why we want to implement the solution we ourselves have built.

Are you looking for a contactless QR based option and contact tracing solution? Let’s talk about your safety challenges.

Macelle Legaspi is a digital strategist & tech marketing professional.

4 Cases Where Retail Data Analytics Can Give Quick Wins

Despite all the buzz around Data Science, a lot of retail companies today are still struggling to become data-driven. Working in the retail data analytics field for the last 5 years, I noticed that many retailers seem to think their hands are tied because of the limited amounts and types of data available to them: “I would like to be more data-oriented, but I need real-time sales data to do that.” “If collecting individual customer data wasn’t so expensive, I would be doing a lot of retail data analytics right now.” Due to this mindset, many companies become DRIPs: Data Rich, but Information Poor. Many companies have yet to realize the wealth and potential of the data they already have. Having more data is not always the solution -- it is what you do with it that counts.

Having limited data is a big roadblock to achieving a data-driven culture, but it shouldn’t limit managers from making more informed decisions. With the right knowledge and application of Data Science and Analytics techniques, there can be a lot of quick wins for retail companies.


On Expanding Customer Basket Size

There are two ways retailers earn -- by getting new customers or by getting existing customers to buy more. For businesses, a bigger basket size is also a form of validation that the customers are loyal to the brand. One way to expand average basket size is through market basket analysis, a technique used to look for associations among products by exploring customer transactions. By analyzing which items are purchased together, the following questions can be answered:

  • Which products should go together on store shelves?
  • Which products can be bundled together to boost sales for a less popular item?
  • Which products can merchandisers or field agents push to customers through smarter recommendations?

For example, companies will be able to see if customers who buy the shampoo product of a particular brand also buy the corresponding conditioner product from the same line. Some associations can even be surprising like the classic data urban legend about beer and diapers. The legend goes that a store owner discovered that male shoppers who buy diapers also tend to buy beer. By placing beers close to the diapers section, he was able to boost the sales for beer.

With the right infrastructure and resources, a market basket analysis can even be elevated to become a recommendation engine. These are models that power targeted digital ads highly customized to a customer’s preference based on past purchases, location, or interests. If only non-real time transactional data is available, a market basket analysis is the next best thing.


On Price Optimization

Pricing can be a sensitive topic for marketers. Increasing it means taking a hit on volume while decreasing it means taking a hit on margin. The most ideal scenario then is increasing the price without making a significant impact on volume. Many retailers with e-commerce presence adopt dynamic pricing, which involves changing prices in real-time according to current data on website traffic, competitor prices, demand, etc. You will see this in action with eBay and Amazon. However, dynamic pricing requires real-time data that is difficult to acquire. One alternative for retailers is a price optimization model that considers publicly available information. These kinds of data can be collected from the internet or from the field and can be combined with internal data on sales and advertising:

  • Competitor prices
  • Weather
  • Holidays or events
  • Inflation
  • Product attributes (size, brand, color)
  • Store location

The only caveat here is that manual data collection will require more time and effort, especially if the company does not have web scraping capabilities. Statistical methods might help in inferring how much data should be collected and how efforts can be minimized to ensure the data being collected is representative of the overall picture. If data collection is still not possible, a price optimization model based on just internal sales and advertising data will still enable data-driven decision making. 

Cluster analysis can also be used to infer pricing trends and elasticity. A simple clustering model can be used to find segments across products based on factors such as location, season, and product attributes. Are there products that can take a price increase because they do well in premium locations? Are there low-priced products with similar attributes to a higher-priced product? 


On Retaining Customers

Companies that have the means to track customer transactions, such as loyalty programs or online e-commerce accounts, can easily predict which customers are likely to churn by looking at patterns of churned customers. With a churn re-engagement strategy, companies can win back customers and prevent churn.

If you’ve ever received an email that goes like this- “We miss you. Here’s a coupon code you can use on your next purchase”-chances are you’ve been deemed as a likely churner. Re-engagement emails like this one from Missguided, a UK-based fashion retailer, are examples of reactivation strategies that target specific customers who are not likely to come back and shop again. The strategies are based on attributes such as last log-in date, length of time in between log-ins, time spent on browsing, count of items in the shopping cart, etc. Through a churn model, retailers can implement preventive measures to engage users at risk.

Example of a marketing email offering a special coupon encouraging customers to shop again
Here is part of an email from Missguided, a UK-based retailer, encouraging a customer to shop again using a special coupon code.

In the retail landscape, a customer churn model can be developed by considering the following:

  • Basket size and value
  • Days since last purchase
  • Days in between purchases
  • Day of visit (Weekend or weekday)
  • Categories of purchases
  • Seasonality

For companies that rely on offline transactions data from POS systems, attributing purchases to individuals may pose a challenge. It might be worthwhile to consider introducing a membership program or another similar strategy to capture customer information. Notice how SM Advantage users get text blasts on promos and discounts from time to time. Aside from knowing your customers, there is also great value in being able to reach them. Measures to engage retail customers who are likely to become inactive can easily be implemented with a membership program in place.


On Expanding Customer Segments

Another benefit of collecting customer information is having greater visibility on customer segments. Companies spend huge amounts of money to identify market segments. Product development and campaigns all depend on which customer groups are undervalued and untapped. However, in order to make sound decisions, retailers must also complement market research with methods in retail data analytics. Most of the time, company-specific customer segments do not really align with industry-wide market segments.

Internal customer segmentation can easily be done by analyzing customer and transaction information, such as:

  • Age
  • Income
  • Transaction Data
  • Purchasing Behavior

By doing this, retailers will be able to uncover behaviors that are specific to their customers. For example, a company would be able to design better products or campaigns if they know that 60% of their customers are young professionals who go to the store at least twice a week and have a minimum income of Php 60,000. Typical market segmentation may capture age and income, but rarely does buying behavior get considered as valuable data.

It might be hard to do a customer segmentation analysis for companies that do not have membership programs. One alternative is to do random surveys on customers during store hours or through social media platforms.


How Can You Get Started?

There are many ways to tap the potential of already existing data. A lot of the examples given above require transaction-level data that are usually already collected by companies to track aggregated sales. However, if even this information is not available, retail companies can consider other cost-effective ways such as surveys and manual collection. 

What’s most important to take note of is that all data, no matter how granular or detailed, have value. Businesses don’t need fancy AI models and bots to get started with Data Science. With a team of Analytics experts, Retail Data Analytics can be done with data that are already accessible. For companies without in-house Data Science capabilities, consulting with companies well versed in extracting value from data would be a good starting point to becoming more data-driven.

The DRIP culture is a thing of the past. Companies already have the power to achieve more -- they just need to unleash it.

Justine Guino is a Senior Data Analyst at Amihan Global Strategies. She specializes in helping our clients unlock tangible value from data. When not working, you’ll find her planning for her next travel adventure. Connect with her on Linkedin (https://www.linkedin.com/in/justinecg/).

Graphics showing different technologies in data science and analytics

Data Science Solutions for Social Good

When we talk about data science or data science solutions, things that come into mind are sexy and advanced implementation in technology–we think about knowing our users on such a deep level, predicting behavior, having personalized recommendations right on our notifications, having an almost seamless conversation with a chatbot. We think about the endless possibilities of data that’s right on our fingertips accessible through our smartphones and browsers. These endless possibilities spell convenience, accessibility, and choices.

But not everyone has a smartphone. Or an internet connection. In the Philippines, only 65% of the adult population has a smartphone, while the internet penetration rate is at  71% (Digital Report: Philippines). When we think about data solutions, how do we make it accessible to the marginalized? How do we take these techy, sexy solutions about data science for social good?


Inclusion at the core of data science for social good

During this COVID19 health crisis, what are the most intuitive data science solutions have you seen or used?

A lot of it is probably convenience related–delivery of goods and meals at your doorstep, finding open banks and other services within your area. Maybe something altruistic–finding the donation centers, where to bring the right donations like food or PPE for our front liners. Or just to know what’s happening out there by looking at dashboards that describe the state of the pandemic in the Philippines, or how our government is faring in terms of poverty assistance or budget disbursement.

All of these, at the touch of a button on our smartphones or personal computers.

It’s easy to assume pristine conditions when cooking up AI or ML solutions–data is readily available, people will use it, it will improve lives, and we will live happily ever after. One of the challenges in developing AI/ML solutions is bringing it to the masses. How will these data science solutions improve the everyday lives of people at the margins?

Data science for social good is not new, but it has yet to gain popularity in development sectors. There are a lot of opportunities on data that the development sectors can start with. This crisis produced a lot of great collaborations as well as lessons that we can learn from.

So, where do we start?


Of open data and platforms: Sharing as a habit

A lot of the first barriers of collaboration is inaccessible data. There can be a lot of reasons: it can simply be no one wants to share the data, or data formats released are usually not machine-readable (oh yes, hello tables in PDFs). If it’s possible to share data, let’s make it easier for everyone! What does it mean to go open data?

Open Data Handbook says there are three important things to keep in mind when you want to share your data: 

  1. Data should be accessible and available: Minimize reproduction cost and maximize convenience, remember to render it into file formats that are easy to modify (like CSV or XLSX) and acquire. For example, during this public health crisis, government institutions can easily get people working on analysis and applications when data is convenient to get—less work for collaborators on cleaning and scraping the data. But getting this started is not easy at all. It requires integrating data and knowledge management to everyday operations of an institution or organization.
  2. Data should be reusable and covers redistribution: Make sure policies on sharing data are in place. Doing open data practices means you should consider reuse and redistribution—like merging it with other datasets for analysis. 
  3. Data should cater to universal participation: You can’t just restrict particular fields, groups, or individuals from using that data. No discrimination in participation.

The keyword here is interoperability. To work together, data should easily adapt to diverse systems, flexible enough to be wrangled and merged for analysis and applications. Interoperability also touches on the opportunities of creating great (and well documented, I may add!) application programming interfaces (API)—giving other developers and data scientists to work on other solutions you haven’t thought of yet. 

While not all datasets are meant to be open, there are opportunities that can be explored for open datasets. Share, if you can!


No more redoing the wheel: Collaboration is key

At the peak of the information age, data is a resource. From one dataset, we can derive different values for it depending on our analysis or purpose. Don’t reinvent the wheel! An innovation mindset requires a faster turnaround and collaborations. From my experience in the academe and the industry, good solutions bring different disciplines together. Various domain knowledge outside of computing brings fresh perspectives on how a team will look at solving problems.

During this COVID19 crisis, as data scientists, we can see the value of collaborating with epidemiologists, medical doctors, biologists, mathematicians, statisticians and social scientists on making assumptions and models that can help create a clear view of the situation. Development problems are complex—privileging one point of view is a simplistic way of solving problems like poverty.


Participation is not a token

In my work as a development practitioner, one of the things I always emphasize is our community partners should have a sense of ownership with the solutions we bring to them. What does this mean? When we create applications and solutions with a particular sector, asking for their feedback should not remain as lip service. Development initiatives fail when the community feels it does not solve the problem at all—bringing AI/ML is doubly challenging.

Accessibility is the first consideration when working with communities in the development sector. Imagine designing a good solution that you can use with a smartphone and internet, but the area has no data connectivity available! 

In creating AI/ML solutions, we often forget to look at representation from our end users. One federal study found that a facial recognition technology in the US will likely fail in recognizing people of color. Algorithms are representations of our worldview as developers and data scientists, and therefore we should be wary of how our code teaches machines how to see the world.

This brings us to the last point I want to make.


Reflection is essential

Like how machines learn from mistakes and uncertainties, development initiatives concerned with data science solutions will benefit from asking questions: What can we do better? How do we reach the people who need the solution? I heard once from my mentor that we usually skip reflecting because it’s non-billable work—we don’t make money off it, we don’t create groundbreaking academic work, it’s not even considered productive. But reflection makes us stop and think about what happened and maybe learn lessons for future reference. 


What now?

We can take small steps in starting data science for social good initiatives. Sharing and collaboration are achievable goals. Have an idea for communities in need? Talk about it with a friend who can help you. In the words of the hit HBO series Silicon Valley, let’s start making the world a better place.

Rikki Mendiola is a data analyst under the Product Engineering - Analytics pod at Amihan. Before joining the industry, she worked in the academe implementing various communication and information technology projects for the development sector.

Amihan shared ideas and possibilities with AI and Data Analytics with C-level business executives.

Amihan Welcomes Digital Transformation Leaders to a CxO Session on Data Analytics and AI

Amihan, in its commitment to foster organizational environments powered by data analytics, invited data analysts and business strategy officers from the banking, insurance, fintech, and real estate development sectors last February 20 at the Amihan office in the Zuellig Building, Makati for the first of this year’s Amihan CxO Series.

The CxO Series is a quarterly gathering of business executives interested in creating transformation within their organization to strategically adapt to fast-changing trends and technologies. Titled Navigating the New Economy with AI and Analytics, the session focused on how artificial intelligence and analytics can spur business growth and transform digital customer experiences.

Amihan’s Chairman, Winston Damarillo, opened the day’s event by sharing some insights about the early-stage digital journeys of industry leaders in the lens of Amihan and data analytics.

“We have uncovered many interesting things -- not just how to use big data analytics for value creation, but also how it could be used to manage risk as well as to detect fraud. Most importantly, how it can be used to find and open up new markets,” Damarillo shared.

He added: “These days, it’s no longer a question of whether you should do big data analytics or take up digital transformation. It’s really a question of how fast do you want to do it.”


Winston Damarillo opening Amihan's CxO session on using Data Analytics and Artificial Intelligence in various businesses and industries.Joining Damarillo were Amihan’s Chief Technology Officer Francisco “Kiko” Reyes and Data Analyst Rikki Mendiola. Mendiola shared how data analytics has evolved to become a driver in digital transformation initiatives while Reyes explained the practical applications of using artificial intelligence in the enterprise setting.

“AI and Analytics together can be economically significant, precisely because it will make something important much cheaper,” Mendiola explained the value of using data analytics for decision-making. “You will only lose out on opportunities and waste valuable time and money by ‘trusting your gut’. Stop flying blind and become more data-driven. You can bring in more value with (your) data.”

Incorporating the profile and needs of customers using the data that businesses collect simplifies the end-goal of the whole analytics process. “We have a saying in design -- ‘Asking the right question is half the job done.’ One of the core things of digital transformation is knowing and prioritizing your users, or your customers.”

Rikki Mendiola, Amihan Data Scientist, sharing insights on using Data Analytics with Artificial Intelligence for better business decisions. Reyes shared a short history of the recent gains in Artificial Intelligence, but he also gave a stark reminder of how to use it given its complexities. “We should think about where we put AI in the spectrum (of business). It would be fantastic to place AI throughout the entire process, but your employees might get scared (for fear of losing their jobs).”

He further added how using AI in certain scenarios can be an exercise in risk management -- that people who will use the technology must be at the center of any transformation initiative. “If you implement AI, you should not alienate your employees,” explained Reyes. “You have to be mindful in communicating the reason for this implementation -- that this will make their jobs better.”

Amihan's Chief Technology Officer gives his thoughts on the differences between Data Science, Machine Learning, and Artificial Intelligence. At the end of the session, Damarillo gave a short briefing about his new book, Ready or Not 2020: The 5 Trends Changing the Landscape of Business. Out now in Fullybooked branches, the book illustrates the new decade’s wave of continuing technological innovation and the necessary steps local businesses and entrepreneurs must take in order to thrive.

In a quick synopsis of his book, Damarillo exclaimed that while e-commerce is making waves in the metropolitan areas, “hybrid commerce” in far-flung towns -- a combination of online selling and face-to-face transactions -- is fast growing. He also shared about how cash is being heavily digitized nowadays, the increasing usage of QR codes, and the issue of using passwords for data protection.

Watch the full video recording of the event.

Amihan's Executive Chairman Winston Damarillo talking about the current use cases of AI and Data Science, while sharing a light moment with CxO guest attendees. Do you have a question about using AI or Data Analytics in your company? Shoot us a message and we can schedule a meeting to discuss your needs.

Tech trends 2020 - Cloud computing, IOT, hyperautomation

Top 5 Tech Trends That Will Shape 2020

As the year rolls on, we will see trends that have been incubating for years see progress. From cloud computing to artificial intelligence and blockchain, many concepts that used to only exist in science fiction are becoming very real and are becoming the top tech trends of the day.

It is difficult to predict what futuristic ideas will eventually turn into reality, but here are five top tech trends that are sure to drive the conversation among decision-makers and tech leaders.


Increased Use of Cloud Computing

2019 was about cloud cost optimization, securing data in the cloud and the continued rise of container usage. We expect to see more multi-cloud, hybrid cloud, and private cloud adoption, AI implementations in the cloud, as well as further growth in edge computing in the coming years.

5G and further developments in edge computing will make data processing faster and more responsive to customer and business needs. Automation, combined with Artificial Intelligence (AI), will allow decision-makers to simplify work processes and to secure operations in public, private, or on-premise environments. 

Another step will involve more containerization- the ability for developers to write and manage their code in the cloud. Building this capability will further develop the ability of enterprises for near-instantaneous updates and bug fixes for their products.

In questioning how much this will affect how we do business, it’s not a question of when and how. The better ask is:  How far can cloud computing take us?


Rapid Development in IoT

The businesses of today and tomorrow will be heavily reliant on IoT devices to assist us in everyday tasks. Most personal devices can already interact with other smart devices in their immediate environment. Meanwhile, devices connected to manufacturing facilities can observe and dictate operational efficiency and productivity. An example of this is the use of sensors in POS machines and store shelves that help retailers keep track of their inventory or of their best selling items.

Data collection and sharing will also be more efficient, especially in the case of devices equipped with AI and voice-user interfaces. Digital assistants such as Amazon’s Alexa and Apple’s Siri are constantly competing to become your next much-have home accessory (if it’s not yet on your desk!). 

IoT technologies work best in the background, collecting data and interacting with other devices to make work and everyday living so much easier. And with more developments in artificial intelligence and cloud technology, it will not be a surprise to see ‘smarter’ homes, offices, even cities.



Hyperautomation advocates for continuous automation of work processes to augment human functions.  Through Machine Learning (ML) algorithms and controlled workflows, almost any business process or function could be automated. But it can also involve making more sophisticated process models for customer acquisition, data ingestion and processing, analytics, and measuring and monitoring of other automated processes for assessment. 

With RPA (Robotic Process Automation) and Artificial Intelligence at its core, expect organizations that hyperautomate to see better responses in customer engagement and demands, identify crucial opportunities, and reach record efficiency and effectiveness numbers for service delivery. Integrating automation will also reduce chances for human error, allowing managers and decision-makers to make better resource allocations and decisions. 


Continued Integration of Artificial Intelligence

The AI industry involves many facets, yet a large part of its growth has revolved around the use of data and analytics. With an increased focus on collecting, storing, and utilizing data, companies have become more aware of the different ways they can do better business with smart robots. 

Retailers and e-commerce sites can create targeted campaigns and personalized offerings through predictive analytics, which uses AI to predict outcomes using patterns and historical data. This is how certain platforms such as Facebook and Google can give product recommendations, a discount coupon, or content that is curated for you.

Chatbots with advanced AI can be made into smart digital assistants. Natural language processing and machine learning algorithms have advanced to a point where we can train bots to translate and analyze data input into contextual written prompts. An example of this is a leading insurance firm in the Philippines pioneering the use of a deep-learning AI platform that’s integrated into Facebook Messenger and other chat apps. More than 200 microinsurance agents equipped with these robots in far-flung provinces are able to quickly provide clients with protection against fire, accidents, and critical illness, all through the convenience of Facebook.


Further Developments in Blockchain

There is a saying among tech circles whenever the topic of blockchain is brought up: “Blockchain is a solution looking for a problem.” For all of blockchain’s promise of a decentralized and secure system, it has had problems with scalability and speed vs cost. Interoperability issues and much-needed regulation also persist- not all solutions are present on all blockchain networks (such as Hyperledger and Ethereum) and legislation on its use differs per nation. Yet, this has not stopped its development as one of the top top tech trends often discussed in business and government circles.

In spite of companies continuing to grapple with how blockchain can best serve their purposes, its advocates continue to build on its foundation. In the book Ready or Not 2020, Winston Damarillo explained how financial institutions like banks can make transactions on the blockchain and secure them through smart contracts. Smart contracts are digital programs that enforce an agreement between two parties. This means that specific actions can only be executed after prerequisite conditions have been made. This ensures reliability and security are enforced for all parties on the blockchain.

This is what a leading Filipino bank is doing with its own blockchain platform. Built to process inter-bank fund transfers instantly, the platform was made for rural bank branches to avoid the usual pitfalls of servicing clients so far away from urban centers. Since its launch, the platform has on-boarded 31 banks and has processed over Php 150 Million worth of transactions. Supply chain financing and international remittances, amongst other features, are in the works.

Accessible blockchain for all has yet to arrive, but there is progress. What needs to happen is constant cooperation and collaboration between the bigger blockchain players.


What other top tech trends do you think will have an impact on how you do business this year and beyond? Feel free to tell us your thoughts by dropping us a message.

Hyperledger Indy for Self-Sovereign Identity Management

Protecting Identities: Hyperledger Indy for Self-Sovereign Identitity Management

Protecting Identities:
Hyperledger Indy for Self-Sovereign Identity Management


The possibility that you can ‘live’ your entire life on the internet, hypothesized decades ago, is now a reality. People can transact with businesses and organizations online anywhere in the world, and communication apps and social networks have shrunk the distances between us.

This freedom to do everything on the internet, however, leaves us open to security risks. Every purchase, log-in, or entry using our personal information creates a digital footprint stored or cloned onto many different databases. What more, third-party entities can collect individual data without the owner’s knowledge nor permission. How can we better use and protect our digital selves when the traditional methods are no longer safe nor sustainable?

Hyperledger Indy, a distributed ledger system built using blockchain technology, was purpose-built for decentralized identities. This is also called self-sovereign identity management, a protocol with one distinct directive: protecting our identities.

How Our Digital Identities Work

In our everyday interactions, we use documents that can prove who we say we are, such as government IDs, email addresses, or credit card information. It is easy to prove who you are when you are face-to-face and can present your credentials in person. But that’s not how our identities are managed on the internet.

The internet was born from a network of computers interconnected through an institution’s identity administration system. Traditionally, single identity providers (IdP) run administration duties for an organization’s own network. But because organizations work like independent silos, there is no way for another organization to identify you on their system.

If you want to log in to another company website or email, you have to go through their own identification process and most likely, provide the same information you’ve already provided elsewhere, to prove your identity. These repetitive processes are not only taxing on a person’s time; exposing identity data multiple times can also lead to privacy breaches.

These lapses in our identity security are a threat not only against individuals but to organizations and governments as well. Technology leaders have been facing increased scrutiny due to recent cases of illicit data exposure, while public officials all over the world are pushing for stricter data privacy regulation.

Decentralized Identity on Hyperledger Indy

Hyperledger and the Indy platform uses Self-Sovereign Identity (SSI) to reconfigure siloed identifier systems to return the agency and control of identity information back to its users.

In SSI, identities that can prove who you are will now be treated as credentials. Only the owner of these credentials has control of who can see or access their information. There are three roles essential to this network: the credential issuers, the holders, and the verifiers.

  • The credential issuers are the ones who own, hold and determine how their credentials will be used and how the information on them will be validated.
  • Credential holders determine the credentials they would need to use in their workflows in order to prove things.
  • Credential verifiers determine what credentials to accept and which issuers to trust.

For example a customer wants to open a new account at a bank. A representative of the bank will ask for a credential (e.g., customer’s name or birth date) and a signature from the customer (the credential holder). The bank (the verifier) will then verify the credential through a digital identity management system. After a search in the distributed ledgers, the customer’s employer (the issuer) will confirm that they issued the credential. With the confirmation, the bank representative can finish creating the account.

Hyperledger Indy is a distributed ledger purpose-built for independent digital identities. It is a framework that can be used for a global decentralized identity management system. It has the tools and components to create real-time reconciliation and authentication solutions across multiple industries, giving it extreme flexibility in many applications that requires fast and secure identity authentication.

  • The government of British Columbia in Canada created an online directory, the Verifiable Organizations Network (VON), making it easier for businesses to register and to get permits while massively reducing red tape and unnecessary sunk costs.
  • To improve the banking experience of customers, the Bankers Association of the Philippines is developing a digital banking ID registry with its member banks to streamline the opening of new accounts and to hasten the delivery time of mobile services.
  • Evernym, the company that provided the first codes for Hyperledger Indy, created Connect.Me, a digital wallet app that uses self-sovereign identity verification. The wallet allows users to gather credentials as digital proofs, store or backup digital wallet credits, and answer secure messages from any connection on the Sovrin blockchain network.

Hyperledger Indy for Enterprise Development

Hyperledger Indy’s platform, using blockchain technology, allows for many different applications that revolve around the secure use and verification of identity information across other organizations on the blockchain.

  • A self-sovereign records management system for healthcare agencies can assist in providing prompt and accessible care for patients, eliminating barriers and slow processing times in accessing crucial medical information.
  • New e-payment systems using self-sovereign digital identity can simplify transactions and reduce opportunities for fraud. Instead of using usernames and passwords, customers can shop securely with just one click.
  • Digital identities can be controlled and managed easily using a self-sovereign identity platform. Individuals can verify their identities when interfacing with entities on the blockchain, notarize documents, and access personal records such as citizenship IDs.

To learn more about how Hyperledger Indy can work for your particular needs in digital identity management, connect with us through the form below, and request a product demo. Add greater value to your client relationships by protecting your clients’ identities and securing your organization’s digital integrity.


    Mapping Digital Space: Neo4j and How Graph Database are Changing the Way We Use Data

    Neo4j and graph database technology is a fairly new segment in the field of databases. But it goes well beyond data management and application development- it is a re-imagining of how data works in relation to one another.

    Today, the world’s leading digital enterprises (such as Google, Amazon, and Netflix)  have combined to contribute to the largest repository of information in history. 

    Facebook, for example, has nearly three billion unique accounts in its system, making it the largest ‘country’ in the world. But with such high volumes comes the need for better ways to collect, store, and analyze all this data. It makes sense then that this new challenge requires new solutions. 

    A New Evolution in Connecting Data

    New database demands require higher speeds in performance and flexibility. Current relational databases work best for problems that already have tabular data, an organized structure, and a defined schema. Because of this rigidity, developers have to create their applications to structure data accordingly. 

    This becomes a challenge when the pool size of the data becomes too big and complex. When exploring certain relationships in data, multiple queries in such a rigid structure will lead to slow down and bottlenecks. 

    To illustrate this, we can use an Employee to Department example. If you would want to connect an Employee’s ID in a table to their Department ID in a separate table, you would need to produce a Join that has foreign keys that could connect both IDs to one another. To connect even more data points with each other, you would need a Join table that holds more foreign keys. You must also know the exact values for both the Person and the Department IDs to know which person is actually connected to which department. These costly Join operations are often solved by denormalizing the values further, but this can lead to a loss in data integrity.

    A diagram illustrating a database lookup table different from Neo4j graph database

    The graph database prioritizes and stores relationships that connect data points to one another. But instead of just establishing relationships between data points in separate tables, each data model, called a node, can have its own set of relationships with other nodes. 

    When you run an operation, the graph database will use the list of relationships contained in each node to establish the appropriate connections in the graph. The nodes will then connect with one another through multiple data points to create a visual representation of the database.

    Instead of relying on keys to match an Employee to their Employee or Department ID in different tables, a graph database would present a node containing an Employee’s list of relationships to various Department nodes. To find out which departments a person belongs to, a simple search of belongs_to relationships within the Employee’s node will present the department nodes it is connected to.

    This level of precision and speed allows graph databases to process and analyze data in real-time. It also allows for multiple relationships between nodes to persist, leading to better data integrity.

    Neo4j and the Uses of Graph Databases

    Neo4j is a database management system that utilizes a graph search framework to traverse databases and answer queries in a faster, more efficient manner. It creates and maintains data connections in a logical fashion while lessening translation friction between developers and executives- those involved in sales teams can easily explain its uses through visual examples, while developers can meet application requirements much faster due to its ease of use.

    Neo4j technology has enabled leading enterprises to transform data into tangible solutions.

    Real-Time Product Recommendations

    In highly competitive industries such as retail and e-commerce, product placement and customer recommendations play a large role in increasing visibility and probability of purchase. Using data collected from transactions and customer feedback, a company can create a system that surfaces relevant products to customers in real time. 

    Walmart used Neo4j to optimize its online shopping experience by constructing a real-time recommendation engine. It was designed to create highly personalized product recommendations while instantaneously offering suggestions for one-size-fits-all product queries. 

    For the engine’s foundation, Walmart built a database that could connect huge amounts of complex buyer and product data to create insights into customer behavior and trends. The graph database also allows them to quickly search a customer’s past purchases and combine this with any current online visits and searches to create real-time recommendations.

    By using Neo4j, Walmart now has a keener sense of what their online customers prefer to see and buy online. They are also able to optimize the up-sell and cross-sell of major product lines. These changes ensure that the company sustains its competitive advantage over other online retailers.

    Identity and Access Management

    Expanding enterprise networks and multiple accounts originating from single users- these are just some of the daily issues that revolve around Identity and Access Management (IAM) amongst IT professionals. It is through IAM solutions that organizations can manage the identification, access, and control of resources for individuals, business units, and departments. 

    Telenor Group is a mobile network services firm. Their business revolves around creating self-service account management systems.  Due to performance and response issues with their older IAM platforms, they had to develop a new system that would be more adequate for the needs of their customers.

    Neo4j’s native graph query engine can be used to handle changes to an entire organization automatically; it can even build or rebuild entire directories for personnel or asset management or create complex access and control structures.

    The new application can execute a complex identity and access management system that assigns service privileges to a client’s whole organization. With a graph database IAM solution powered by Neo4j, Telenor was able to deliver better performance, scalability, and improved maintenance for its self-service portals.

    Content and Asset Management

    Neo4j was created due to a need for a better content management system. The goal was for the new system to recommend photos based on unique, but related search terms. These parameters actually lead to much better-related search results, and during the testing phases, lead to increased engagement for the new platform.

    The principles behind this initial version of Neo4j could be used for search and data-intensive processes found in content and asset management. Lufthansa Systems, a technology company under the airline Lufthansa, developed an in-flight digital asset management system specifically for their commercial airlines.  They use this system to keep track of the digital content being delivered across the fleet, which includes managing the hardware being used, the content licensing, rules, and much more. Due to the requirements for an advanced system that could evolve over time, the graph database used in this system has the operational flexibility to efficiently receive, store, and use Lufthansa’s data while maintaining high performance.

    So How Can Graph Databases Help My Organization?

    The advantages of using Neo4j and graph database technology have to lead to new and flexible solutions. If you are looking for a database framework that could help you navigate through a modern data challenge, Amihan can help and provide insight into how Neo4j can work for you. Simply fill up the form below and we will get in touch.

      Amihan Launches Tech Briefings with Partner GitLab

      IT developers and security experts met up at the Amihan office in the Zuellig Building, Makati last March 7 for the first Amihan Tech Briefing, organized in partnership with GitLab.

      The Tech Briefings is a series of free learning sessions created to share the latest technologies and strategies for digital transformation. Titled Driving Innovation with DevSecOps, the day’s event, organized by Amihan and GitLab, centered on the current role of DevSecOps in modern software development.

      Amihan’s Chairman, Winston Damarillo, kicked off the session with a short opening message about the driving force behind the new event.

      “We were looking for opportunities to talk about our innovations with our partners, but we wanted something that was more casual. The ideas that we will share here, if used well, could be game changers in the industry”, Damarillo said in his message.

      Joining the Briefing as speakers were Amihan’s Vice President for Enterprise Architecture, Alistair Israel and GitLab’s Technical Account Manager, Guenjun Yoo. Israel focused on the advantages of adopting a DevSecOps environment, while the latter half featured Yoo conducting a practical demo of GitLab’s latest software platform.

      “Enterprises are facing growing consumer demand from customers who are now digital natives,” Israel said on the current state of technology, “What used to take decades to reach 50 million users now only takes several days.”

      “Sometimes, we don’t commit to security checks because most often we push things to market as quickly as possible. People make mistakes, but not out of sheer malice to destroy work, but because we’re only human,” Israel explained as he positions the need for better security and control in DevOps processes.

      Yoo, meanwhile, presented GitLab as a timely solution to an old problem. “In most organizations in the past, the engineering teams do their own processes and make working cohesively very difficult. This lead to the massive number of tools users had a hard time using.” He goes on to say that the simplified pipelines in GitLab are meant “to address the toolchain crisis through one, simple tool.”

      Jerry Rapes, Amihan’s President, connected with Damarillo’s remarks in his closing address, emphasizing the importance of creating and scaling advanced technologies today for the needs of tomorrow’s consumers and businesses.

      “Today is a good reminder of how far our industry has come in terms of enterprise development. The market rewards institutions that prioritize agility and service delivery while keeping an eye on the future,” Rapes remarked.

      Thank you to our guests for joining us and we look forward to seeing you in the upcoming Tech Briefings!

      To learn more about our DevSecOps Platform, click here.