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. 

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!!!!

Let's Kopi IP Series – Featuring Codename.biz by Trytec Malaysia

Paper based Business Cards are now Officially Obsolete

Most successful business professionals are fervent networkers and constantly keep an eye out for new talents, potential customers, partnerships, investors and other useful contacts that can be cleverly leveraged to achieve growth objectives. In a fast moving business, executives routinely fill work calendars with professional events, calls and business meetings where new connections are initiated, usually through exchange of paper based business cards, that may be followed by LinkedIn invitations.

However managing and maintaining large number of contacts using this method over time can turn counter productive as executives move organisations, change career path, get promoted, shift to a different region or simply relocate to a new office.

The use of online tools in creating modern professional branding..

Paper based business cards are unable to capture and link to online profiles nor can the contact details presented, altered without reprinting.  Even when business cards are digitised by card scanners, such systems do not necessarily prompt an automatic connect to online profiles owned by card holders. The card formats vary and are not always an exact match for the mobile contact list, resulting in missing information during information capturing process. When there is a change in address, mobile number, email, company or new links such as blog or video is added, the paper based card has to be reprinted and redistributed to keep the network updated.

Codename.biz is a Virtual Business Card Platform 

Online networking, collaboration and content sharing platforms such as LinkedIn, Workspace, Reddit, Twitter, Quora, blogs, online professional groups and YouTube are changing the way professional profiles are composed and orchestrated. The new age workforce actively utilises multiple online avenues to creatively add personification, demonstrate leadership, command specialisation and keep

professional branding relevant with current market, industry and business trends.

Codename.biz by Trytec addresses this challenge and simplifies the process of creating, sharing and updating virtual calling cards that includes additional online branding assets to various business networks simultaneously in realtime. Users can use a single cloud interface to create business contact information with links to social media profiles, websites, blogs, videos and other multimedia content that describes the business and expertise best.

The virtual business card is available in different colours and designs, easily shared via mobile, email or other messaging tools such as WhatsApp or Messenger.

QR codes are generated for users to facilitate connections by simply scanning the code using the mobile camera. Trytec is currently expanding on this idea and considering options to print the QR codes in the form of costume jewelries and watches to promote usability and convenience.

It’s only a matter of time before the traditional calling cards are abandoned…

Traditional calling cards are becoming less relevant as we move into a highly connected work environment where the lines of professional, social and personal lives are beginning to assimilate. Systems and algorithms are amassing data continuously on netizens to generate various types of scores on social, commercial and professional contributions. Making a novel online presence and an original personal branding, a crucial prerequisite for attracting business opportunities.

The simplicity of Codename.biz can turn it into the next de-facto method for presenting contact information and identity to business networks. It offers a compelling value to users by binding all critical professional branding assets in one place with features to add or edit sources in real time without complicating the virtual profile with a resume style outline.

Be an early adopter, try the beta NOW

Codename.biz is currently in beta run as work to lift user experience and robustness of the platform are carried out behind the scene with more user feedbacks becoming available. In the mean time, users are encouraged to take advantage of the free service period to try out the service.

Come Not Between the Dragon Riders, Rise of Asian Platforms

The Asian Platform business scene is worth over a trillion dollars in market value and is only the second most prominent after North America. The region’s thirty over publicly traded platform companies and thousand other startups is enough to make any investor exuberant over growth opportunities for expansion, acquisitions, investments and joint ventures.

Uneven Business Landscape, Full of Opportunities

Market conditions does differ from country to country, hence the contrasting maturity levels. Overall, favourable economic condition, trade policies, maturing infrastructure, growing middle class and an upswing in GDP, is paving way for incredible growth unattainable in developed markets of North America and Europe.

Leaders of the Pack – China, Japan and Korea

Growth is mostly fuelled by China, Japan and Korea where there is high domestic demand for online services, concentration of capital, available talent, a frenzy of innovation projects surrounding core technologies aimed to realise full business potential, enhance services and user experience. Alibaba, Tencent, Baidu, Softbank, Yahoo Japan and Kakao is clearly taking the lead in diversifying their businesses into multi-platform conglomerates, through series of acquisitions, investments and joint ventures.

Pioneers In Challenging Environment

India and Southeast Asia’s best performing platforms such Flipkart, Snapdeal, InMobi, PayTM, OYO, Lazada, Olacab, Garena and Grab on the contrary, are focusing on becoming profitable on well tested e-commerce, gaming, payment, ride sharing, transportation and advertisement models. They are making way for other players by addressing the region’s weak investment landscape, antique trade regulatory policies, uneven access and speed of Internet services. Though, the region is never short of startups. Arrival of newcomers such as Omise (Fintech), and TripAlly (Travel Platform) based out of Thailand, are just two examples reflecting the region's ongoing commitment to platform economy.

Noteworthy Observations on Business Model

The platform business model of the Asian region is centred on consumers and SMBs, unlike American platforms that evolve around enterprises mostly.

Online marketplaces for buying and selling goods, financial services, communication, gaming, transportation and travel are some examples of where good response is tracked in Asia. As such, Asian Platforms generate a significant share of revenue from transactions and trade as opposed to American platforms (e.g. Facebook and Google) which depend on advertising.

A massive population which is learning quickly to adopt consumer technologies for various lifestyle reasons, is a huge encouragement to the sector to digitise existing and create new innovative services.

Innovations centred on Artificial Intelligence, Blockchain and Robotics

China, Japan and Korea is pumping tons of cash on developing capabilities in artificial intelligence, blockchain architecture, virtual reality, augmented reality, Internet of things, cloud computing and robotics.

The breakthroughs are expected to help:
• Automate search ranking, recommendations, image classifications, image character recognition, speech recognition, natural language translation
• Improve experience for Asian customers whose native language characters are complex and cumbersome to type
• Last mile delivery automation with drone (e.g. Alibaba, JD.com)
• Build virtual assistants to enhance shopping, education and gaming (e.g. Baidu)
• Develop a Broader payment solution (e.g. Tencent and Alibaba)
• Establish transparency of supply chain (e.g. Alibaba)
• Ensure food safety (e.g. Tencent, Alibaba)
• Development of humanoids (e.g. Pepper, Softbank)
• Development of autonomous vehicles (e.g. Apollo, Baidu)
• Blockchain e-commerce (e.g. TripAlly)

Research and development centers are scattered between China, Japan, Korea, Hong Kong and Singapore. Government initiatives to utilise upcoming technologies to upgrade industries further aggregates efforts between public, private and government affiliates.

Investments in Stakes and Acquisitions

There is no doubt that Asian Platforms are stepping up their game in the international arena to compete with the likes of Amazon, Google, Apple and Facebook.

Softbank's $100 Billion Vision Fund

The $100 Billion Vision Fund's recent investment track record probably is the best evidence to point out how critical platform businesses are to generate expected return. The largest tech investment portfolio ever to be created, the investment dollars are spread to both international and many promising Asian Platforms such as Flipkart, OYO, Ant Financial and Didi Chuxing. Softbank is also aggressively pursuing stakes outside the scope of this fund in Asian Platforms such as online insurer Zhong An, Grab, OLA Cabs and Snapdeal.

Tencent versus Alibaba Race in Southeast Asia

Just before the arrival of Amazon in Southeast Asia, Rakuten shutdown operation in the region. This was later followed by Rocket Internet’s (operator of Zalora and Lazada) exit, selling most businesses it operated. But, what seemed like a drawback of key players from the region very swiftly started a healthy regeneration with close to $3 Billion in investment from Chinese players.

Some notable acquisition and investment news since then are;
• Softbank and Didi Chuxing took a large stake in Grab
• Redmart was acquired by Lazada at price point lower than initially raised
• Lazada was acquired by Alibaba
• Ant Financial acquired Hello Pay
• Ant Financial invested in Ascend Money, Mynt, M-Daq
• Tencent acquired Sanook
• Tencent invested in ABC 360, Go-Jek, Ookabee

The arrival of large Chinese players in the e-commerce, fintech and logistic space is certainly driving more pressure on regional groups such as Orami and Ascend Group that has been fighting for a clear marketshare for sometime. Nevertheless, this development can benefit the region by driving maturity of the sector, underlying infrastructure and regulatory designs.

The ‘Alibaba versus Tencent’ race may not necessarily create a conflict as many analyst cite. Close scrutiny may reveal that both companies are establishing dominance in different segments based on strengths. However, together the giants may impact advertising revenue for product search as consumers shift to their platform to conduct such searches.

Flow of Investments from China to India

Despite a large pool of skilled programmers, proficiency in English, and strong business ties with US and Europe, India’s platform startups continue to struggle to expand with uneven infrastructure, poor internet access, suboptimal government regulatory policies and lacklustre interest by other successful tech related public groups such as Reliance, Future Group, Aditya Birla, and Appollo.

But the potential of platform companies such Flipkart, Snapdeal, Ola and OYO is too good to be ignored by the Chinese giants, notably Alibaba, Tencent and Chinese Internet Plus Holdings who are constantly competing to get a stake in the countries platform scene. There is no mistake that these platform giants are building a ingrained presence in India at the moment.

Fuelling the Startup Eco-system

Programs such as SuSS by Alibaba and others by Tencent is quickly becoming a platform for entrepreneurs to connect and build business support structure. By encouraging platform startups in Asia, larger platform companies are able to cherry pick suitable acquisition targets.

Regulatory Challenges

Regulation over platform and online businesses remains a challenging area for governments in the region due to the border less nature of the business. Exposure to security and privacy matters, impact to local industries, government trade and taxation policies, flow of investments, and the overall economy are some of the factors which stifles effort to harmonise governance.  Self-governance may be helpful for some policy concerns, but deeper cross border regulatory challenges  require collective government effort to codify through regional and international trade  agreements such as the Trans-Pacific Partnership (TPP) which provisions for e-commerce and other digital trade.

Superior Service or Protectionism is Driving Success?

Many experts argue that some of the largest Asian Platforms are perhaps growing out of government protectionism and inability of foreign platforms to operate freely from unfair data, trade, compliance and other domestic policies. Often the region is target for criticism and accusations over inability to innovate effectively, espionage activities, poor privacy and security control.

Inbound and Outbound Trade Gateway

Even if there is truth to this, it’s extremely hard to dismiss the fact that millions of people and thousands of businesses are still transacting over Asian Platforms. In fact, their reach is starting to grow beyond the region. For instance many of the sellers on Amazon and eBay place orders in Alibaba for their stocks. Alibaba acts as a trade exchange to connect Chinese businesses to global consumers and global businesses to Chinese consumers. For small businesses, this is a valuable and cost effective service which includes handling of cross border transaction.

Exceeding Customer Expectations

Similarly Yue Bao an online money market fund owned by Alibaba offers a annualised seven day yield of 3.4% to customers who wish to save their leftover money from transactions. Over 60% of holders in this fund have less than $1000 in their accounts. This fund is currently sized at $165 Billion, performs better and is larger than the JPMorgan Chase US Government Market Fund ($150 Billion).

Not All Strategies Work in Asia

Asian Platforms understand that superiority in technology stack alone is not sufficient for success in diverse Asia. Aligning technology, innovations, investments, and consumerism to address netizens’ needs and SMB growth challenges in buying, selling, conducting secure payment and managing the cross border processes are key to their success.

Criticism, both ill intended and constructive, was taken to build a better business. For instance Alibaba and Tencent took market advice to further improve platform transparency by launching blockchain and artificial intelligence intersects to address issues around unsustainable supply chain and food safety. They are on a journey to debunk all disapproving claims over effectiveness of Asian Platforms.

5 Levers to Optimise Learning

“Nothing is ever Achieved without Enthusiasm”, Emerson

Ever wondered how Uber, ANT Financial (Alipay), Xiaomi, DiDi Chuxing, or Airbnb turned into world's largest unicorns in 2017 (and yes, please note that 3 out of 5 are actually from China) ?

Perhaps it was the early market lead, a disruptive technology, platform inspired business model, successful fund raising rounds or simply favourable government policies. Each firm hacked growth based on different mix of factors but shared one similarity. Their leadership and workforce was able to keep pace with the supersonic growth and recalibrate repeatedly to the next future state.

Entrepreneurs whom are in constant pursuit of new knowledge and finds a thrill in the perils of solving difficult business problems are effective learners. They promote sharing of information, inferences and team collaboration for optimal execution of every business function. Making optimising learning capacity of individuals and teams in organisations an imperative measure in driving and sustaining growth. A metrics closely observed by leaderships and funding ventures alike.

Technology to Assist and Augment 

Businesses operate in an extremely fast environment today, where advancements in consumer gadgets and enterprise technologies have enabled us with massive computing power capable of deciphering quintillion bytes of data in nano seconds. Artificial intelligence and machine learning is further sophisticating automation of softwares, machines, neural networks, robots and humanoids.

Ignoring such developments and their benefits in assisting and augmenting work in sectors such as health, legal, high tech, retail and financial will only leave the business irrelevant to market over time. Instead every technology disruption provides a purposeful learning opportunity to move higher in the work chain that should be embraced.

Make Sense of Data

Similarly online business models, platforms and devices are flooding us with data and information. Researching a customer or partner, means pulling and collating information from various sources internal and external (e.g. within the enterprise walls, certified agencies and what is available publicly).

Using analytics to make sense of the different data sets and correlation to business helps to build better reasoning for business cases, speedily scratch the surface of critical operational issues, dive deeper into situations, or anticipate an upcoming threat (or avoid the ‘boiling frog’ phenomenon). It expands cumulative ability to uncover answers to inherent business questions and expose unchartered frontiers for seeking new understandings. This improve resources allocation and focus for all the right business activities in product innovation, sales, marketing and support.

Practice Problem Solving

Growing startups exposes entrepreneurs to various types of business constraints. Some problems are clearly defined with goals, while others are inhibited by vagueness, thrusting us into a panic zone. The iterative process of identifying, classifying, defining, diagnosing, understanding and breaking down the problem, results in expansive mental progress that improves strategies and methodologies in problem-solving over time.

However, exhausting teams with repetitive problems (which is a target for complete automation anyway) will only erode this cognitive exercise to an inertia. Instead refocus them to address complex challenges, where the process of active revealing and listening in search of a solution mechanism takes place. It is here, where many startups stumbles over a lead, growth engine, untapped market, or a golden opportunity to gauge market share from conventional players.  Riding back on the iceberg parable illustrated in the previous point, the deeper you dwell into business inhibitors, the more questions you will uncover. The journey to answer these questions will lead to breakthroughs.

Failures multiply Worth of Lessons

It's bizarre but success and failure lies in the same direction. Success is reiteration of adjustments made from failure to failure without ever loosing the excitement for the venture.

If Abraham Linchon would have shied away from numerous disappointments and feared the angst that may arise, it would have taken a lot longer to abolish slavery and build a modern America. If Nelson Mandela would have stopped fighting apartheid in South Africa at the thought of being imprisoned for life, South Africa will still be torn in civil wars and severe human rights crisis.

Failure teaches value of resilience, focus, reflection and to bounce back stronger each time a pursuit hits a dead end. Only by apprehending the lessons of defeat, one can gain clarity to amend path forward and avoid repeating mistakes. In fact, no one successful is ever reserved from having to confront calamities, criticism, and temporary standstills. After all, success is sweet when you can tell a story that can inspire others.

Performance Support Tools

Performance support tools, such as collaboration platforms, portals, advance analytics (including bigdata), case and content management solutions (e.g.  JIRA, G Suite, Slack, Asana, and other SMB SaaS Services) that are integrated across the various business functions in the organisation is a great way to distribute and update team members of newly available learning assets. In addition, the design and representation of these tools across functions can influence how quickly complications in process or product can be resolved.

The Act of Perfecting the Game

Using the levers mentioned above will speed learning pace and get us quickly to the deeper composite nature of any business riddle. This creates more room to effectively piece personal mastery with cumulative learning assets garnered from others in a collaborative manner. Pushing teams to increase adoption of core capabilities to understand complexities, prioritising what matters most and develop effective conversations to perfecting the game.

Practise does make us perfect (or at least better) but equally important is to break away from bad habits of not seeing the big picture quick enough, getting stuck in management myths, or living in a delusion that learning comes with experience (The Fifth Discipline, Peter Senge). As they say, you can’t gain without pain or by being oblivious.

Finding the Right People – The “5 Questions, 90 Minutes Conversation” Rule

Finding Good Talent, Remains a Challenge for Startup Community Everywhere

Whether it's China, U.K. or the US, hiring good people continues to be a painstakingly difficult task to accomplish for startup community, due to a number of reasons. A limited domestic talent pool, disconnected talent networks, competitive market and even public policies, are just some culprits to name.

Recruiting is a time and resources intensive business activity, especially for businesses that are in midst of scaling for new growth. The process of identifying the right candidates in terms of expertise, behaviour, attitude and compatibility with work culture is arduous. But asking over recycled interview questions and employing self-discriminating filtering criterions, will only lead to a suboptimal process that eliminates much of your “A Team” potentials.

Interview Questions that fails to extract useful Candidate Informationh

For a start, we should question why executives tend to use the same 10 to 15 standard interview questions, that we so often find on the Internet, if every business has a different DNA? Even worst, when the same questions are repeated by several executives in different cycles of the job interview. Shouldn’t questions prompt response to reveal or demonstrate the qualities that you are seeking in a candidate?

Questions, such as “What is your strength, weakness or tell me about yourself ?” existed since the seventies. Back then, there were no social media, mobile devices, cloud, or widespread Internet service to submit applications online. These questions were created at a time when most job seekers carried their printed CVs  into walk-in interviews. Many of the questions asked by hiring managers today are redundant and is only an echo of the CV which was also used to filter for the first interview.

Start by Outlining Assessment Criterions and Expectations

Preparing interview questions starts with the listing of categories of expertise, qualities and traits you are seeking in the ideal candidate for the role you intend to fill based on the responsibilities and expected outcomes. You also need to factor in a weightage to the criterions to assist in decision making process (e.g leadership – 20%; sales – 30%; pipeline management – 30%). This process should be initiated even before the job advertising begins, to ensure that the adverts clearly communicate key requirements and will serve as a guidance for candidates to respond accordingly. For example, if you are looking for a senior enterprise sales hire for large deals, the following can serve as the baseline for your expectations;

Listing the criterions helps to keep focus on what really matters and fully utilise the interview cycles to gather incremental information on the shortlisted candidates. The filtering criterion shrinks and expands your talent pool. For instance, by inserting ‘startup experience’, as a necessary filter, you may automatically turn away from other credible candidates with a broad background in building businesses from ground up. As such, practicing a bit of caution as to how the criterions will impact your search is necessary to avoid over filtering very early in the process. Phase the filtering based on the weightage.

Align Interview Questions with Business Requirements

Once you know what you are looking for, designing the interview questions is swift. Ensure, that the questions are geared to obtain information according to criterions that you have set and prompts spontaneity from candidates. Spontaneous reactions are reliable benchmarks on how one would react to situations in reality. Thus, reveals a lot more about the candidates’ true character and attitude to their surroundings in stressed or difficult situation.

You don't need many questions, use "Let's Kopi's" 5 Questions, 90 Minutes Conversation rule to substantiate constructive conversation in each cycle. Ensure the questions are phrased cleverly to extract and capture incremental information on the candidates in each cycle. Also, allow for clarifications and subservient questions from both parties, in between. For example, falling back on the previous sample of criterion above, the following questions can help pull the necessary information;

1. What can you tell us about the market you are currently covering?
2. How does enterprise technological advances e.g. Internet, web, cloud, mobile devises, AI, AR/VR and etc. are affecting your role and the sales process?
3. What are some of your favourite projects to date and why?
4. Describe how you manage a crisis situation ? E.g a team member turns into a loose canon in front of a client during a crucial meeting.
5. Moving forward, what is a lucrative deal to you and what strategies you employ to stay ahead of quota requirements?

Apart from being a good instrument in helping the hiring team to match candidates’ skills, expertise, attitude and character;  these questions serves as a blank canvas to the candidate in demonstrating creativity, communication maturity, conflict management, negotiation, curiosity, intelligence deployment, exposure to various situation, relationship building and their unique differentiators that sets them apart from other candidates.

Smart Companies Develop People for Tomorrow

Good people will continue to be the success foundation of startup businesses, no matter how much automation and digitalisation infiltrates the future. Making scrutiny of the interview process, imperative. Just following the increasingly “talent only” focused best practises of larger companies puts startups at risk of not having the right team in place to take on opportunities and grow the business.

The wide-spread adoption of SaaS HR services, to a certain degree is adding to the problem as most systems simply mimics processes of large enterprises instead of allowing the flexibility in creating the right filtering tools, assessment criterion, flows or interview execution functions suitable for startups.

Your business success, lies on your ability to pull high potential individuals that you can cultivate. People who in return, turn themselves into the backbone of businesses to deliver business functions that maximises outputs of human, machine and carbon resources. So pay close attention; dare to flip outdated processes and tools; search for balance between talent, traits and potential.  Envision a future workforce optimised for learning, to ride a highly competitive tomorrow.

Cost , When IT Advisory Breaks Down

No Enemy is Worst than ‘Bad Advice’

When the financial books are closed each year, we meticulously measure the profits; growth of assets;  intellectual property and patent portfolios; accumulated liabilities to employees, suppliers, service providers, regulatory bodies, investors and owners. Subsequently a lesser portion of entrepreneurs, submit further to observe number of unexpected business turns, mishaps or even anomalous increase in operational cost, which consumed significant part of the already tight resource allocations. In other words, the discovery of a series of cash burners that lead to the flushing of valuable resources which could have otherwise deployed

for growth engines. 

For instance, If a small business is operating on a budget of $50 million and is incurring 5% unexpected expenses on average per year, that translates into $2.5 million in financial losses alone. In addition, let’s say that 50% (25 million) of your operational budget is allocated for production which incurred an overrun of 10% of the forecast which translates into another $2.25 million. That is still a total of $5 million over the budget (assuming that no buffer allocation was made for unexpected expenses). Reflecting carefully a little deeper, every one of the drawbacks, may lead us to a point when we received ‘bad advice’ or even worst ‘no advice’ (withholding information intentionally is also a form of ‘no advice’) from a cadre of expert and specialist consultants that we retain as financial, legal, marketing, advertising or technology advisors, among others. According to a survey conducted in the U.K small businesses loss over £6 billion due to misdirections from experts with IT consultants leading the pack (44% followed by management and marketing consultants at 34% and 32% respectively) causing the most damage to businesses.

The common theme here is to take every advice with discretion. As such, investigating IT projects that are currently squandering resources and yet hindering the business from its goals, is a necessary step to identify sources of specialist misrepresentations. 

The Alluring Appeal of the Third Platform Infrastructure and Services

Asian SMBs are pouring billions of dollars (3rd in spending after North America and Europe) into technology with the hope to increase their competitiveness and success rate against larger businesses by adopting more and more of third platform infrastructure solutions (e.g. mobile, cloud, big data, analytics, Blockchain, social tech and collaboration tools) and services (e.g.  AI/cognitive, virtual /Augmented Reality, IOT, 3D, Security, Robotics). Choosing the obvious ‘cloud’ path (both private and public) may have reduced the conventional risks associated with IT projects but even then, there are questions to be asked and answers to be probed to avoid mistakes. Matching the software or services that links best with business operation; choosing the right cloud technology (often to be align with the existing tech eco system); picking the right development platform for mobile or IOT applications and even understanding the various direct and indirect licensing estates, is crucial in realising the returns of investments channeled into automation, optimisation, waste and redundancy elimination. In short, pretty much any decisions on solutions to business challenges depend on sound IT advice.

When Reputed Automation Projects turns into Drawbacks

When strategic IT initiatives get derailed they turn into impediments that weigh on the business forming waste, sluggish business processes, redundant workloads and prone to manual interventions to produce – the very same elements that we are trying to abolish for a much error free and productive business environment. For instance, in 2004 HP stated that is suffered a shortfall of $400 million in quarterly revenue due to a failed ERP migration of its ordering and supply chain systems. The breakdown caused a 12 weeks business interruption with order process and resulted in manual intervention to conduct day to day business, not the least three key executives fired by the CEO Carly Fiorina, at the time for the costly affair. Closer to home, AirAsia was sued by the Australian regulators in 2010 for breaching consumer law by not displaying the total ticket prices on their 
reservation systems. AirAsia later admitted that this was due to a poor localisation of their system for
the Australian market. However, this incident caused them $200,000 in fines. In 2006, CPF took action on a leading global IT Services provider for a failed IT project it contracted in 2001. It was cited that communication breakdown within the parties along with complacency has caused the project to collapse.

Such is the price to pay when IT projects goes awry. While they may not impact the business severely as isolated incidents, a plague can form collectively if not addressed in timely fashion resulting in overrun of budget, miss delivery dates, suboptimal applications that leak revenue, threat from various non-compliance (industry, consumer, data privacy, security, tax, accounting, software licensing), wasted computing resources (comatose VMs, equipment), damage to brand reputation and overall workforce productivity.

But Should Technology Advisors Condemned?

Pointing the fingers never helps anyone. In majority of cases, relationship breakdown between business and IT advisors over accountability and delivery of outcomes, or dissensions arising of it, are the true causes of project failures. The agency theory problem perhaps is best to explain why either party might get derailed from accomplishing project goals in the process of aligning and creating values for their employers (sometimes may involve several business units), partners, customers and their ownself. What’s important to know though, is that most IT advisors (technical and business) are earnest and perform credibly to stay in repute. Nevertheless, provisions should be allocated by both parties to take action in the event of negligence, complacency or breach of contractual agreements, that likely to emanate losses.

In addition, it’s crucial to tap into this rich pool of experience, knowledge and technology mastery in scoping and deliberating on what makes an IT project successful. What a cognitive waste it would be, to just ask this group of plans and recommendations but to never dive in the ‘why’, ‘how’ and ‘when’ such recommendations takes full effect to benefit business. Here are some notable areas to heed in navigating conversation with your IT advisors.

Firstly, understand who your IT Advisors are, what they represent, aims and areas of conflicting interests. In any one project, it is common to have several IT advisors with slightly different agendas and strength. On the vendor’s part, sales and consulting has a responsibility to promote, position and sell their solution as the best fit for your requirements. An independent or in-house IT champion may maintain a neutral position to assess what's the best for the organisation but tend to build assumptions and loyalty with certain providers from past experiences, creating a blind side to their judgement. Sizing these advisors and their leverage in key initiative, is the first code to crack. It is also advisable to adjust compensation model if necessary to suit the dynamics of the relationships, their interests and priorities (E.g instead of hourly rate to delivered functions).

Secondly, align expert recommendations and proposals with business, strantegy, users and its automation needs. Don’t underestimate the power of isolated units, their fiefdoms and current workarounds to complete order processing, procuring supplies, making payments or even connecting with other third party providers such as logistics to ensure business runs as usual. Bring together owners of processes to communicate the automation plans and why it is important to the business. Early involvement of all stakeholderst of the respective processes, aids in uncovering challenges that would be otherwise missed.

Thirdly, request your IT advisor to help you visualise a best case and worst case scenarios of success, with current resources, work culture, best practices, governance mechanisms, process methodologies and existing technology environment. This should help match risk areas during implementation, triage of business interruption, impact to productivity and regulatory compliance among others. This information will enable further adjustment to budget, timeline and drive the necessary changes (e.g. skills upgrade for workforce, upgrade of relevant tools and applications, inducing suitable best practices, familiarisation of the futuristic workplace notion) which in creases the success rate and contain risk exposures.

Technology Advisors turns into Priceless Assets

Recognising a reliable and credible technology advisor is somewhat facile. They are ‘rebels’ and ‘masters’ of their field, constantly contending the constraints of modern technology in a value creating business, even though they are not entirely immune to defeat. A good advisor will ensure you invest in the right business areas; choose the right technology solution; lead technology benefit analysis; help define a suitable integration strategy for best inter operability of tools, systems and applications; promotes acculturation of the right skills and best practises; outlines risk exposure; and is never without a mitigation and disaster recovery plan. 

Much importantly, they stick around wielding their prescience and immaculate social intelligence, when a project is hit with unanticipated calamities or additional requirements to include ongoing changes from regulatory, compliance, technology landscape, integration, operation, customer and market behaviour perspective. 


But these traits can only be an asset if the idea to manage failure, change and challenges is premeditated in the governance of IT initiatives. Expecting everything to go exactly as planned is a ‘mortal sin’ in this practise, as much as surrendering to stultifying statements claiming all application projects are headed for Armageddon (as stated by Gartner) which is both highly disturbing and questions the very constituent of IT advisory.

Third party platform may have intensified complications notably in areas of integration, security, data privacy, intellectual property, access to services, and multiple clouds; but instantaneously this also made way for much efficient delivery, flexibility and agility to the business. Exercising sufficient control on bodies of work according to timeline and extracting values as you go, is the new norm of the tech world. If this is understood correctly, than we know which part of our conventional wisdom should be relinquished for the future of a democratised technology environment