LK Weekly Precis - Corporate investors, monetising 5G, and hustle to complete deals before the slowdown..

March seems to be starting on a higher note with several startups raising late stage funds in th range of US $1 billion and more. This includes Grab, Go Jek, NYSE listed Sea Group in the recent follow on share offer and the Alibaba backed, Chinese influencer power blogger marketing platform, Rhunn.

Government initiatives are picking up steam especially in Southeast Asia for coaching services, co-working spaces, tax exemption, seed fundings and other resources but requires program owners to improve execution, assesment criterias and reach for better outcomes.  

Here are some key highlights to note this week;

5G Opportunities for Operators and Startups

The recent MWC 2019 in Barcelona, Spain may have been a routine yearly event, but visitors certainly caught a glimpse of a very different future for communication sector in the coming years. Change in business model, operation, partner eco-system, new customer and service segments is imminent. Operators will need to move upwards of the infrastructure, basic voice and data services for revenue and quicker ROI or risk running into massive losses at the point of the next network upgrade.

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Various participants including KT, China Mobile, startup communities and others demonstrated usecases on Smartcities, Smartfactories, 5G Cloud, Augmented Reality and Virtual Reality connectivity, autonomous vehicles and many more, that is pointing to enterprises as the key segment to monetise 5G investments.

Traditional partners such as Samsung and LG are adding new IoT services to offerings, apart from a range of mobile and connected devices. For instance the grocery replenishment service with Samsung refrigerator.

Telco operators in Korea, Japan and China are certainly leading the race when it comes to implementing 5G use cases and without a doubt will be in the forefront of innovations, in this space. 

AirAsia launches Redbeat Capital in collaboration with 500 Startups

In our last weekly summary we covered how DBS was looking to invest in startups that can help distribute the banks products further into new territories. It seems that trend is here to stay with more conglomerates taking the same approach to unlock new markets and innovation.

This week AirAsia announces the launch of Redbeat Capital in collaboration with 500 Satrtups. The US$60 million  fund will be used to provide post seed funding for global startups making way into Southeast Asia in travel, lifestyle, logistics and fintech segments.

Huawei Cloud Region Opens in Singapore

Huawei adds a new cloud region in Singapore aside from China, Europe, Latin America, Hong Kong, Russia, Thailand and South Africa. Huawei Cloud now has 40 availability zones in 23 geographic regions. Offerings will include various platform services for artificial intelligence and machine learning.

Currently the company is actively hiring the regional team and is aware of the market's highly competitive landscape with several key cloud vendors already delivering values, where customers are rapidly adopting cloud for better IT efficiencies, investment flexibilities, consistent performance, geographic expansion and faster time to market.

In the past, Huawei depended on its portfolio of foreign based Chinese customers to penetrate into new markets, but we should anticipate some new field tactics beyond price cuts and equivalent services for businesses this time. A shift of sales focus on nailing at least sixty percent of revenue share from services that run above the basic compute, storage and networking infrastructure services is almost mandatory to differentiate from the rest of the pack.

Meituan-Dianping and Chope

Restaurant booking sites and apps in the region has certainly changed how restaurants perceive customer experience for better or worst.

On peak days, customers are rushed to cater next booking, cancellation fees for no show, constant interruption from servers to top up drinks and other add ons to keep the table, have just made it more of a hassle for diners lately.

However, this deal with Meituan-Dianping should particularly benefit Chope to increase utility of their app and tap into the chinese tourist market at the same time. But will these reservation and restaurant referral sites in anyway add value to diners experiences? Can they help restaurants create unique experiences with the data they are collecting?

Horizon Robotics Raises US$600 Million

The trade war is now opening up opportunities for AI chip makers from China including Huawei and Alibaba to accelerate release of products within this year.

Horizon Robotics is one of the highest valued unicorn in China currently, apart from Cambricon for developing AI chips. The company recently raised another US$600 million in funds to push through development, final designs and outsourcing of manufacturing processes.

With several Chinese AI chip makers planning to outsource manufacturing process and rush to release second generation chips by mid 2019, this could prove to be a prospeporous year for Taiwan based TSMC with a full factory load.

Some Cheers for Startup Communities in India

Finally some cheer from our startup entrepreneur communities in India as the Department for Promotion of Industry and Internal Trade (DPIIT) in India announces changes in the definition of startups (turnover not exceeding Rs 100 crore) and set the confusion over 'angle tax' to rest.

Fintechs Refining Playing Field

Lastly fintechs everywhere in the region are refining market strategies to bridge cashless payment, cryptocurrencies, lending, mobile wallets, e-wallets, and other financial services for both consumers and businesses through new alliances, effective sales programs and much polished product releases. 

Aside from startups, fintechs are increasingly seen as a lucrative attached revenue source for mobile operators, ecommerce platforms, conventional financial institutions and travel related sectors that has access to a broad audience of B2C and B2B buyers. 

Some noteworthy highlights of fintech activities this week are as follows; 

• Axiata and Singtel collaborating for cross border payment;
• Alipay having reached staggering 2 million users and 50,000 merchants in Hong Kong in just a year from launch;
• PayTM India introducing subscription programmes to increase utility;
• Razer launches beta services of Razer Pay digital wallet in Singapore;
• and Mobi Direct teaming up with Worldline for digital payment processing in Pakistan.

Some common trends persist and still an untapped B2B segment.... 

Overall the startup scene is still evolving around ecommerce, ride-hailing, logistics, travel, gaming, payment and other B2C segments where a majority of funding deals are channeled by investors at the moment. As a result, we continue to observe several common repeating themes from previous weeks as follows;

• Traditional sectors such as finance, telco and travel continue turning to startups eco-system to accelerate innovation, build new growth engines and discover business frontiers. 
• Chinese corporate investors such as Alibaba, Tencent, Didi and Meituan-Dianping continue to supply capital to various Southeast Asian startups in ride-hailing, travel, e-commerce and other lucrative B2C segments. 
•  Cloud companies such as Facebook (with IMDA) and Alibaba are working in deeper collaboration with regional startup incubators to lure and accelerate startup success on their platforms.

Nevertheless, this is an ideal period for startups in the region to reboot the drawing board in the B2B segments, leveraging the approaching 5G connectivity in IoT, augmented reality, virtual reality and smart factory arenas for new innovations. 

Telco operators in Southeast Asia are generally less prepared to monetise 5G services and may be more willing to pour investments in a startup ecosystem that fills the service gap in a shorter span of time. 

In addition, many of these telcos are positioned poorly for an internal transformation in terms of adding skills, reorganising business structures and constructing business capabilities for 5G use cases due to outdated business policies, practise of privilege systems and lack of diversity in workforce.  

AI Playbook for Startups and SMB

The AI Playbook for SMBs and Startups

Most businesses in the SMB and startup class, still struggle to grasp the broad definition of AI disciplines, what AI really is to their business, where to get started and what successful execution looks like for their businesses. Simplifying a focus area narrowing these concerns specifically to address your business pressures is helpful to keep team in line with long term business goals and strategies.

There are many AI Playbooks written by renown gurus such as Andrew Ng, meant for Fortune 500 organisations and they do contain some very useful guidance and tips for all businesses. Nevertheless, smaller ventures with limited funding, skills and resources may need to rework tactics to suit business.

Here we present steps to formulate a generic AI playbook meant for small and medium sized businesses, which includes stages to:

• internalise AI definition for the business; 
• outline and prioritise business problems that can be addressed with AI;  
• experiment with ready pre-trained model
• build required skills or internal structures;  
• prepare training and test data; 
• choosing a path between pre trained and custom built model for solutions, 
• and assessing overall impact to businesses performance. 

The generic AI Playbook should ideally incorporate other dimensions unique to your business, industry and commercial eco-system over time, for maximum results.

Define and internalise AI for your business...

AI itself is a broad subfield of computer science. It encompasses many branches of studies including rule based AI and decision trees; machine learning (regression, classification, neural networks/ deep learning, reinforcement learning, supervised and unsupervised learning); robotics; text and speech processing (NLP, NLU, NLG); vision (computer vision, image recognition) and several other applications that still have not left the laboratories. 

AI is a field where one or several of these approaches are used to create machines, agents and models that perceive, learn and adapt to perform various tasks and cognitive function similar to humans.  

The AI domain is practically exploding with hundreds and thousands of new approaches, methods and solution areas in transfer learning (learning from lesser data and smaller models), networks with memory (generalising AI, e.g. DeepMind’s differentiable neural computer), reinforcement learning, training simulations, hardware for training and inference that are rapidly advancing in the research, development and real world application stages. 

Communicate how AI should be perceived in your business....

As such, it's easy for businesses to get lost in an ocean of offerings that comes with vendor specific methods, best practices, strategies, tools and ready use cases. Charting and communicating how AI should be perceived within the business very early on, in your AI journey is crucial to ensure potent utility, informed expectations and performance. 

For instance should AI merely assist workers to perform better at tasks? Should AI considered as an avenue to outsource cognitive functions otherwise performed by human workers ? Or should AI be a form of cognitive technology to help expand ordinary worker's ability to explore meaningful solutions to business problems both creative and logical?

Setting the right internal tone on AI can guide alignment with work culture, strategies, high impact projects, investments, selection of tools and services that can drive AI values across the business.

Define business problems that can be solved with AI

The common misconception in this stage is, data science or business team alone is responsible to outline business problems solvable by AI. 

Every business unit can contribute to this stage including sales, marketing, services and tech departments. Imagine how it will affect your business if tech can reduce 40% of cooling needs in your datacenter or how your customer service or inbound sales department can improve performance by multi-fold with realtime speech to text analysis that prompts them with emotion, sentiment and other useful information during a call with a customer.

Build working team; conduct regular meet-ups; answer business questions around growth hacking, improving or staging customer experience, workforce productivity and innovation; keep a revisable record of issues pressing the business growth (this can be a simple excel sheet with list of items); prioritise problems to solve; assess data availability; experiment, assess skills requirement; select initiatives for executive sponsorship and create projects to execute. 

Assess data availability and prepare training data for the problem

Data sources...

Data can be gathered from within the business, public datasets, procured from external sources (e.g. Image Net, Google Data search) or a mix of these. Identify useful data assets for your business problem, list what data is missing or not available and which data can be excluded from your raw selections. Collect and aggregate sufficiently to fit your model. 

Data preparation is a significant contributor to cost of building AI solutions specifically ML models, aside from high performance computing resources though GPU innovations has brought so much economics since a decade ago.

Clean and transform data for training...

Most ML models requires large amounts of data to train and converge before they can be applied to business. Preparing these data may require domain experts to collect raw data, identify features with strongest prediction power and label them. Though the business problem you are aiming to solve, tools and selected algorithms ultimately influences data preparation approach and mechanisms. 

Data transformation is revisited several times....

It is common for developers to spend 50% or more time preparing and scrutinising data quality and revisit data transformation processes (or feature engineering) several times during the development of the model. 

Split data sets for training, test and validation...

The prepared data is usually split into training set to fit the model, test set to evaluates final model fit on the training dataset and validation set to evaluates model fit on the training dataset while tuning model parameters.

Consider pre-train models

Ready to train models for various use cases...

For common business problems which requires simple recommendations, classifications, regression, clustering, anomaly detection and ranking, look for pre-trained model offerings by public cloud vendors such as Google, AWS, Alibaba and Microsoft. Many large and niche AI vendors now offer pre trained models for other slightly complex solutions to perform predictions, speech processing, computer vision (video, image and object recognition), decision support and planning tasks. 

No need to build algorithm or ML models.....

These offerings saves businesses the hassle of building algorithms and models from scratch. Plus it's a great way to get started with applied AI for business with quicker results and fast ROI times without having to reinvent the entire process (the value is in the model outcome not building it, especially for non-tech businesses). 

No need to replicate work for  ML backend .....

The team need only concentrate on preparing data, select features and train the model for required tasks (e.g predictions, classifications).  Trained models/ functions can then be deployed with other production applications and systems through APIs provided by cloud vendors to apply learnings on new data samples without replicating any work for ML backend.

ML and DL frameworks

In the event that the business problem you aiming to solve is much complex and does not have a ready pre trained model available, it is advisable to custom build the model custom build the model on a machine learning and deep learning frameworknof your choice, offered by cloud vendors through their ML-as-a-service offerings.

Frameworks such as Tensorflow, Pytorch, MXNET, Keras, Caffe, Scikit, Microsoft Cognitive Toolkit and Theano, comes readily packaged with interface, libraries, tools, pre-built and optimised components to facilitates fast development of AI models without getting into the details of underlying algorithms and complex architectures. 

New developers can benefit from starting with frameworks such as Keras and delve deeper into Tensorflow or other suitable frameworks as they get accustomed with the building blocks and programming languages.

However, it is highly recommended for new teams to get experience from simpler projects involving pre trained models first before venturing into challenging custom building models. It is easy to loose ROI when tinkering with ML or DL models without past experience and benchmarks.

Building AI skills 

When it comes to smaller businesses, building AI skills in-house is really a trial and error exercise to find the right blend of subject matter experts (or the minimal quo) to address AI problems and build solutions. This team's skill level is adjusted according to how they plan to address business problems, for instance with ready models or custom build models.

AI requires programming (e.g. R, Python, Lisp, Prolog, Scala, C, C++ and Java) data science (at least fundamental level) and business domain knowledge at the minimum to obtain some high level results. A strong foundation in mathematical fields such as probability, statistics, linear algebra, mathematical optimisation is necessary if your business wish to develop own algorithms or modify existing ones to fit specific goals and constraints.

Training existing workforce, hiring from other organisations and university grads are some of the common methods to build the right team.

Education sites such as Coursera, EDX, Machine Learning Mastery and many others provide neutral self learning content suitable for both technical and business audience. Content varies from fundamental to advanced level and comes with certification process that can be committed at one's own pace. 

Vendors such as AWS, GCP and Microsoft too have their own academies but syllabus may be skewed towards respective services. AWS and Microsoft are so far the best corporate academies I encountered and complies to many criteria mentioned in Andrew Ng's Fortune 500 AI Playbook in addition to easy to follow content and no fuss lab use (note that this is paid resources).

Assessing impact to business..

Once trained, tested and deployed, weigh the model's impact to your business performance. I use a no fuss method where I categorise what was increased, reduced, created and eliminated over a set period of time.

For instance:

• Did the model INCREASE overall customers value, revenue or profitability ? 
• Did the model REDUCE fraud risk, customer churn or cost ?
• Did the model CREATE new growth engines, data products or differentiators ? 
• Did the model ELIMINATE manual task, blind spots or redundancies ?

These answers are then scored and quantified for best alignment with overall strategic goals and objectives. The data is then collated for all AI projects to visualise and quantify the total impact to business financially (profit, revenue, growth rates, etc) and other areas such as competitiveness, reputation, and customer satisfaction. 

This exercise is helpful in two or three ways :

• to identify successful AI projects and approaches
• to build AI projects that can increase the value or performance of existing models
• find optimal opportunities to apply AI learnings to other functional areas 

There are many ways to measure impact, choose one that you are most comfortable with and put it to work. Use the discoveries to increase effectiveness of AI projects for your business while filling gaps in skill sets and access to useful data assets.

Conclusion - Ethics, Explainability and Human-Machine Interaction

In the end, AI systems are nothing but stacks of infrastructure and programs in various architectures that learns and executes continuously, depending on its utility. The machines aid human workers to predict outcomes, navigate a situation and decide on best action path with less mental drudgery while spanning solution options that was never possible before.

But that doesn't mean AI systems and models are perfect or free from self vested exploitation. Since the 2010s public concerns about racial and other biases in the use of AI for criminal sentencing decisions, creditworthiness and other forms of social credit systems (e.g. China) is driving demand for transparent AI systems and agents.

Explaining decisions of AI algorithms or models, especially those powered by deep learning or other complex neural networks is still a difficult task and is also known as the 'interpretability' problem.  Unlike decision trees and Bayesian networks that are more transparent to inspection, complex neural networks stack on one another and may involve millions of neurones processing towards the outcome.

As such, deploying sufficient governance protocols for data privacy and security; an architecture which facilitates transparency and tools to detect bias in algorithms is as critical as creating successful models or functions. Though in many cases engineering for more explainability and transparency may lead to significant accuracy trade offs. 

LK Weekly Precis - A Quiet Post CNY Week

It's a quiet post CNY week with no major shifts really. Go-Jek gears up plans to add payment partners in the region, the ongoing Didi~OYO chemistry, DBS warming up to startups for fresh new growth, PayPal office closure in Malaysia, Huawei's security concern and impact to 5G rollouts are just a few things to highlight this week.

Go-Jek adds Coins.ph as Payment Partner

The battle to win ride hailing leadership in the region continues, with Go-Jek making several moves to progress in the past weeks. After completing alliance agreements with VietinBank with Go-Viet and Singapore's DBS last year, Go-Jek adds another fintech partner this week, called Coins.ph to mobilise things in the Philippines market despite some brush offs with regulators there, last year. 

Go-Jek, considers payment as the core of its super-app play and intend to complete payments gaps in every market. The Indonesian unicorn is currently backed by investors including Google, Tencent Holdings and JD.com and is pushing valuation to $9 billion.

https://asia.nikkei.com/Business/Companies/Indonesia-s-Go-Jek-invests-in-Filipino-payments-startup-Coins.ph

The Didi ~ OYO Chemistry 

"Ride comfortably with Didi and Stay comfortably with OYO"! The Didi ~ OYO chemistry is catching on naturally with riders and travelers in China, that the Chinese ride-hailing giant Didi Chuxing is investing $100 million in Indian hospitality chain Oyo despite cut backs in the Chinese market.

OYO is currently expanding actively in markets such as Southeast Asia, Europe and China apart from home market adopting similar campaigns with ride-hailing partners.

https://economictimes.indiatimes.com/small-biz/startups/newsbuzz/oyo-gets-100-million-from-chinas-ride-hailing-giant-didi-chuxing/articleshow/67985663.cms

DBS is Open to investing in Startups

As more service sectors converge and customers turn to mobile app for all of their daily service needs, banks such as DBS too are eying the the app and super-app economy to realise new customer segments and growth engines. 

In a recent interview with the Nikkei Asian Review, Mr. Piyush Gupta stated that the bank is open to investing in Startups where the bank's products and services can be distributed to whole new segments. As stated before, DBS recently entered into a strategic partnership with Go-Jek for facilitating payment services but it's unclear if this will this result in new customer flow for the bank.

https://asia.nikkei.com/Business/Banking-Finance/DBS-open-to-investing-in-startups-CEO-says

Huawei, 5G Rollout, Security Concerns - It's business as usual in Southeast Asia

In the backdrop of an intense US-China trade war, are claims made by US intelligence community that Huawei products (particularly the 5G base stations and mobile phones) may contain serious security vulnerabilities that empowers the Chinese vendor with capabilities to conduct undetected espionage. 

This has lead global communication network operators, including long standing business partners such as BT, Vodafone, Dutch Telecom, Orange, LG U+ and others to temporarily suspend and reconsider Huawei agreements pertaining to 5G rollout. LG U+ also made a press statement recently, that the aforementioned equipment source code and various other materials have been sent to an international common criteria (CC) verification institution in Spain for security verification and the report is expected to be out in August or September this year. In the meantime LG U+ intends to rollout base stations for 5G in major city areas. Other Korean network operators such as SK Telecom and KT have suspended Huawei deals for the moment.

In the meantime, Huawei released a media statement informing clients that the company will work along customers with any additional security requirements or compliance towards meeting sufficient cybersecurity standards. The company has also set up a comprehensive FAQ Page to address accusations and correct misinformation.

In the meantime, it's business as usual in Southeast Asia with operators in countries like Philippine, Thailand and Malaysia affirming continued allegiance to Huawei.  Many have openly stated that it will be a tremendous effort to build the next 5G network without Huawei. Top executives further stressed the fact, that 5G is a non stand alone network, as it needs to integrate to LTE and other networks Installed previously, many of which use Huawei's equipments. As for Southeast Asian operators, rebuilding means undoing work accomplished in the last two decades, apart from acquiring huge losses and working forward with Huawei to patch any security concerns if valid, is the sensable way forward.

https://www.scmp.com/tech/big-tech/article/2185816/huawei-gets-vote-confidence-philippines-globe-telecom-which-says

PayPal closes Malaysian Operation Office 

Media reports this week that PayPal has offered VSS to all employees in Malaysia and is closing its operation office there. PayPal has been in Malaysia since 2011 and has offices in other Asian locations such as Philippines, China and Singapore. Reasons for closing the office is unclear but observers are pointing to competitive landscape and a weak business team as the contributing factors. The company however reaffirmed that the internal reorganisation will not affect customers in Malaysia.

https://www.bankingtech.com/2019/02/paypal-to-close-offices-in-malaysia/

aCommerce in Trouble?

aCommerce just released the upgraded BrandIQ line of products and services late last year. A relentless startup when it comes to helping clients accelerate online sales with many leading brands such as Unilever, Samsung, Nestle, Philips and L'Oreal in customer portfolio, the company like many other growing startups did change direction from purely an enabler of e-commerce to distribution of products. Operating in Thailand, Indonesia, Philippines and Singapore, the Google Premier Partner Award winner provide services including logistics, fulfilment, delivery and digital areas like marketing. 

But a recent report by Dealstreet Asia is indicating that the company might be in trouble with key executives leaving the operation including in country offices.  aCommerce was planning IPO in 2020.  

https://www.dealstreetasia.com/stories/momentum-works-acommerce-120055/

That's all for this week and wishing everyone a belated CNY! 

How to Choose a Public Cloud ?

This is a popular question, especially for startup and SMB leaderships, whom may not have an advance tech team at their disposal to support with queries and selections when picking a public cloud that returns the most value for new development or migrate existing workloads. Please note that these questions and methods are skewed towards screening IT infrastructure and platform service provider and not so much the Saas provider (we might cover that in another piece of cheat sheet separately).

Ask Questions
Here are couple of things (in no particular order), that your team can use to prepare before meeting the service providers.  

Please note that it's a really bad idea to meet them unprepared, as it provides a white canvas opportunity for the vendor to paint anything they like. It is highly recommended that you avoid such situations. 

Here are the questions/ areas worth exploring;

1. A list of current IT operations (e.g. applications, tools, analytics, security, data-warehouse and etc.) and technologies in place (e.g Operating systems, databases, development tools and languages, security, infrastructure or even other clouds in place).
2. A list of projected/strategic business activities and their automation/digitalisation needs (e.g mobile app, big data analytics, buyer & seller optimisation, etc.)
3. Customisability of compute and memory requirements (in other words, how much control do you have on your VM or VMs).
4. Pro and cons of owning the PaaS level...
5. Standard tech questions - Interoperability, portability,  new app development cycle, security, redundancy, backup and recovery features.
6. The type and size of technology eco-system that the cloud provider connects to - here you are simply looking for three things; suitability of the technology to your operation; standardisation and; provider that connects with a larger eco-system of technologies (e.g Hadoop, ML, AI, Blockchain, Mobile App Platform and a host of other opensource pieces).
7. Pricing mechanism and projections for on-boarding; utilisation blocks (e.g by minutes, hours, monthly, yearly, types of workload - predictive and unpredictive); exit or off-boarding (be aware that some vendors charge even during off-boarding to migrate data and other intellectual assets off of their platform – this happens when you complete contractual term and don’t plan to renew);
8. Discount and rebate applications - when you get them, and when you don't (ask both questions)?
9. What is the lock-in period (e.g 1 to 3 years). What happens if you exit prematurely. What is the unnatural discontinuation cost?
10. What service guarantee does the vendor provide (e.g. SLA, compliance, security)?
11. What happens when vendor fail to deliver service (system performance, security, data, compliance)”according to contractual term? 
12. What support procedures are in place when a support request is registered?
13. What if you need to scale ? How quickly you can scale the needed footprint?
14. What about trainings and upskill activities?
15. What SMB focused programs does the vendor have in place? Some service providers might have special programs for you to mingle with other users in your category and connect. This can be an added bonus to your business as you can tap onto the knowledge and resources of a wider network.

Request for a Pilot Test

if you are happy with the information gathered through the pre-meeting research and cloud salesperson's answers to aforesaid questions, move on to a test request for the tools and  platform services in question.  Scope the test areas according to your procurement needs to stay on course with your current needs. Look out for performance, usability, flexibility, scalability, security and inter-operability results to support and corroborate information you gathered (unless the test fail to do so).

Tap Talks in the Grapevine
It’s a good idea at this point to fraternise with other fellow startups and SMBs who may have already been using the services first hand.  Their experience could be a valuable addition of information to your decisions. Though, when collecting information from informal sources such as this, be aware of the timelines - a problem or disadvantage that existed a year ago may not apply anymore as cloud companies improve (especially the largest 3 or 4) at a rapid pace.

What is a Satisfactory Outcome?
What are you looking to map with these initial questions and explorative activities?

1. Your IT computing and operational requirement based on business roadmap.
2. Suitability of the service provider/s and their offerings to support your business and future growth.
3. Good understanding of tools and services recommended by vendor before you embark on them.
4. A clear idea on pricing matters; discounts and rebates applications; contractual terms.
5. Outline or scope of duties and responsibilities between you and your vendor in regards to your IT footprint. 
6. Cost of discontinuation of business relationship upon completion of contractual terms.
7. Cost and consequences of discontinuation of business relationship due to premature termination of contract.
8. Your rights when service provider fails you? e.g service delivery, compliance, security or data breach.
9. Exit and migration path to other clouds.

Finally, a piece of useful advice to stay productive and avoid frustrations. Expect for contact points to change at anytime while dealing with vendors or any external parties for that matter. As such, it would be wise to document all requirements, arrangements and agreements to terms, contractual and non. This will help you save time in the reestablishment and reinstatement of such interactions which looses sight due to change of contact points.

In addition, get feedback from both business(finance included) and technical team members on the selection before concluding.

Happy Screening!!!!

Will Data Privacy spark the next Wave of Innovative Applications?

Privacy is a top agenda as we live in an era where data is a fundamental requirement to access healthcare, education, financial facilities, commercial services, employment, security, welfare, social networks, media and even exercise voting rights. Everything around us is designed to optimise and improve by harnessing data, that it has become an undeniable asset with unprecedented utility. 

This makes data a prime heist for unethical hackers and modern day criminals who steal, doctor and manipulate it for illicit purposes including financial gain, scams, terrorism, identity theft, spreading fake news or spying. Some notable breaches from 2018 are the Aadhar breach involving a staggering 1.1 billion records, forum site Quora, Googleplus, Facebook, several airlines and other online entities.

This is why many large corporations that gauge petabytes of user data are under heavy scrutiny by privacy enforcers and regulators such as National data protection authorities in the European Union through the much debated GDPR guideline. For instance a recent announcement by one of Alphabets subsidiary, Sidewalk Lab on a plan to package and sell cellphone data for various service enhancement sparked outrage from various ethics observer and human rights groups, even when the company justified that the unique identifiers will be removed from the dataset.

Staying connected at all time and living somewhat transparently, is the future reality...

But harnessing data is an unavoidable exercise when it comes to achieving greater quality of life, good decisions and optimal utilisation of natural resources.  As such, refraining from the internet, social networks, online media and performing digital transactions will only result in disadvantages, inconvenience and missed values from economic, social and safety standpoints.

Even if we successfully retained a mysterious existence, we will not be free from unwarranted surveillance by both businesses, independent institutions and governments in public places for various reasons as cities, buildings and public amenities become embedded with sensors, camera feeds and chips that connects to the Internet or clouds to perpetually collect data and create values.

Privacy in Asia....

Asia witnessed multiple incidents of data breach last year among CSPs, healthcare providers, financial service providers and even government sources that lead the public to question credibility of domestic institutions in protecting personal, usage and behavioural data. According to a report by Gemalto, Asia Pacific region contributed to over 35% of cybersecurity incidents last year. 

In most cases, institutions took no further action to restore user confidence apart from the breach announcement, which is a mandatory compliance requirement. Gemalto further stated that the numbers could have been much higher in reality, due to unreported incidents especially in Southeast Asia. Singapore is an exception to this as the authorities take great pride in concluding data breach cases successfully to safeguard the regional digital economy.

Asia also suffers from an overall weaker legal framework and laws for privacy though dedicated privacy task force is emerging in India, Thailand, Indonesia, Singapore and Philippines, out of which Singapore perhaps is the most advanced in ratifying and enforcing the aforesaid laws. 

At the same time, there is a rise in governments that are explicitly developing and extending state surveillance under the pretext of national agenda, security and cyber crime laws for political reasons. Technologies such as facial recognition, artificial intelligence, biometric, advanced identity card systems, ever increasing compute capacities and various citizen facing applications are converging into social scoring systems that provides granular monitoring of individuals, regardless of their consent. 

But there is a new way to tackle privacy - a new form of application architecture is on the rise .....

Apart from comprehensive legal framework, enforcements and the use of advance security architectures, strategies and tools, the application design and architecture itself can serve as a mechanism to protect privacy by separating personal data and identities from applications.

For instance, a project led by Led by Tim Berners-Lee called 'Solid' and is currently run from MIT, consist a set of tools and conventions that helps to preserve integrity of identities, privacy and data ownership while enabling developers and businesses create a new wave of innovative web applications. Solid is a web decentralisation project that aims to put rightful ownership of data back to every users and empower applications that are completely decentralised. 

Currently the use cases are limited for developer community alone, though discussions on Solid servers and tools are beginning to emerge in Quora, Reddit, FB Groups and GitHub.

Similarly Digi.me and HAT are all projects aiming to decentralised applications on the web, where users can create libraries of their data and is completely in control of how the data is used by corporations and governments.

Privacy concerns will lead to new opportunities ....

Most large businesses perceive privacy as a critical challenge to overcome with growing pressure from regulators. Though regulators approach are not helping as solutions developed around privacy laws are difficult and expensive to attain technically, especially for Internet giants.

In the end, solution might just emerge from the tech world itself through new architectures and business models lead by smart startups willing to embark on new frontiers such as Solid, Digi.me and HAT to develop fully decentralised applications that satisfy users, businesses and regulators.

Larger companies might use 'business within business' approach to innovate in the privacy space or quickly get onto the new themes through acquisitions, mergers and rethinking business models. On the another note, decentralised web may lead to even larger paradigm shift, similar to the ones we experienced when organisations moved from on-premise to cloud of everything, creating new digital eco-systems altogether. The one thing that no one can afford to do, is to remain unchanged.

LK Weekly Precis - New e-Commerce Regulations, Acquisitions and Expansions

This week, new ecommerce regulations in India shook the tech business community and indicated that government meddling and protectionism policies may continue to hinder progress of emerging markets in sectors such as ride hailing, hospitality and many others aside from ecommerce.

Ecommerce regulations was also a topic discussed in Davos at the World Economic Forum (WEF), lead by Singapore. In addition, the event for the first time hosted talks among tech executives and leaders, including from BAT, to shape up AI framework that addresses both the seller and buyer nations.

Other than that, ST Telemedia acquisition of Cloud Comrade and Travelstop expansion to 7 Asian markets simultaneously, along with JD.com's first drone delivery outside of China are some notable developments in the startup sphere this week.

ST Telemedia Acquires Cloud Comrade

Last year we saw a number of consultancy firms such as Deloitte and the likes, hunting for acquisitions in the partner space of large tech companies namely Oracle, Sap, AWS, GCP and Microsoft.  This trend is now picked up by several data-centre service providers in the region.

ST Telemedia is certainly moving in the right direction by acquiring Cloud Comrade to enhance its datacenter service offering portfolio, especially in cloud services, IT management, cybersecurity and overall datacenter performance. 

Cloud Comrade helps customers in Indonesia, Malaysia and Singapore deploy cloud to accelerate new development and migrate existing business applications for operational excellence. The startup works in alliance with almost all major public cloud providers such as Ali, Azure, AWS, GCP and Digital Ocean. 

Last year, ST Telemedia acquired stakes worth $27 million, in cloud management company, Bespin Global that operates in Korea and China. The new acquisitions will help ST Telemedia complete service offerings in cloud, AI, Bigdata, digital experience and cybersecurity.

https://bit.ly/2Uj7FKe

JD's Drone Delivers Books and Bags in Rural Indonesia

JD.com has been delivering to some rural parts of China using drones for the last two years. This week JD ran its first drone delivery trial outside of China after securing a government license for regional level operation in Indonesia. According to media the drone travelled 250km to deliver boxes of books and bag packs to school children.

Tencent has a 15% stake in JD.com and together the companies co-invested in a number of Chinese companies. Last year Google announced significant amount of investments in JD and Tencent to make inroads in China. 

Soon, same day and next day delivery will be a common offering, sighting of drones in residential areas should be expected and e-commerce logistic players may have to reinvent their game.

https://globalcosmeticsnews.com/jd-com-paves-the-way-for-drone-deliveries-in-southeast-asia-with-first-government-approved-flight-in-indonesia/

Travelstop Expands to 7 More Markets

Travelstop is a year old startup from Singapore, that simplifies business travel and expense management to the SMB and startup segments. Since inception, the T&E Saas platform has been updated continuously with features and functions to sufficiently meet the needs of both travellers and employers in a segment where such services were inaccessible. 

We believe they are in the path to join the likes of 'certify', 'coupa' and 'apptricity' to challenge other established players such as SAP Concur in the travel and expense solution space for the enterprises.

Recently, the company announced service availability in Indonesia, Thailand, Hong Kong, Taiwan, Japan, South Korea and Vietnam.  The company also announced a mobile app for iPhone users to easily access services. 

https://www.eventsnewsasia.com/20190122052718000454-business-travel-startup-travelstop-strengthens-presence-asia-launches-seven-markets/

New e-commerce Rules/Restrictions in India

The new rule restricts online retailers or marketplaces from sourcing more than 25% of inventories from a single vendor, vendors where the online retailers may have a stake and exclusive deals that results in deeply discounted products. 

The new rules seems to be aimed at protecting millions of small traders, operating offline and suffering from huge losses due to deep discounting practices of both Amazon and Flipkart. According to analysts and mainstream media, the recent electoral losses is seen as one of the contributing factor to this unusually regressive move.

https://www.zdnet.com/article/india-issues-new-e-commerce-rules-to-check-amazon-and-flipkart/

AI Discourse at World Economic Forum, Davos 

Finally AI takes a critical spot in WEF this year with US (Alphabet, Apple, Facebook, Amazon, IBM, Microsoft) and China ( Baidu, Alibaba, Tencent) seen as leaders of the space. Economic potential, social threat, globalisation 4.0., ethical practices, AI nationalism, global policies for both AI sellers and buyers were some of the issues beginning to shape the global AI agenda.

https://asia.nikkei.com/Business/Technology/Asian-tech-execs-voice-hopes-and-fears-for-AI-in-Davos

Singaporean Ride-hailing Startup, 'Tada' in Vietnam

This year we might see more ride hailing players emerging in the region, including traditional players modernising their business and competing for their pie with larger competition namely Grab and Go Jek. 

New entries might come from taxi operators, affected driver groups and rental service providers. 

We might also see, new country level regulations, niche plays, convergence of industries/sectors, significant mergers and acquisitions in this space as we cool off in quarter four.

https://www.retailnews.asia/singaporean-ride-hailing-startup-tada-launches-in-vietnam/

HG Exchange

HG Exchange, a fintech industry backed initiative has recently submitted a regulatory application to Monetary Authority of Singapore (MAS). This move will provide investors in the region with better access to high growth companies such as Grab, Go Jek, Didi, Deliveroo and others. 

The exchanged will be built by blockchain developer Zilliqa and Taiwanese digital asset platform MaiCoin.

https://www.techinasia.com/in-brief-hg-exchange-seeking-launch

It's seems to be a slow week in anticipation of CNY next week but we believe businesses will keep up momentum till quarter 3 as a slow down is expected in quarter 4. 

Happy Sunday!