SMEs can develop data unicorns too

Jordan Barker, Director, Sales Engineering, APJ, Alteryx

Data analytics is no longer a buzzword and driving data-driven outcomes should no longer be complicated. It’s been almost a decade since the Singapore government launched its Smart Nation initiative – a national effort to drive pervasive adoption of digital and smart technologies throughout the city state and to position Singapore as a leading economy powered by innovation.

Some of the key strategies that have been pushed out are the prevalent adoption of e-payment methods and the introduction of National Digital Identity (NDI), a digital identity system for residents and businesses to transact digitally with the government and private sector, in a convenient and secure manner.

More recently, the government announced in the Singapore Budget 2021 a funding of S$1 billion to accelerate digital transformation and support local companies in adopting emerging technologies like 5G and artificial intelligence.

However, the reality for Singapore’s small and medium-sized enterprises (SMEs) is far from adopting these emerging technologies. While Singapore companies take the lead with the highest proportion of data-driven organisations in the region, an estimated 70% of SMEs have yet to adopt data analytics and their current knowledge only covers spreadsheets and databases.

Moving forward, half of these SMEs also indicated that they have no intentions to do so in the future, citing limited financial resources and the lack of information systems infrastructure support as main concerns. At a glance, advanced data analytics may seem out-of-reach to these SMEs.

However, a data culture is no longer a nice-to-have but rather a must-have for organisations to navigate uncertainties and ensure business resilience. Data-driven firms are quicker in making strategic business decisions and more effective at communicating with stakeholders.

The term “data unicorn” – an individual who is mathematically strong, technically learned and narratively inclined to draw data insights for the business or mission value – has been popping up in digital transformation narratives. While these data specialists are steering the digital transformation and conversation, and SMEs’ workforce may lack the seemingly specialised skillsets to kickstart their digital journey, deriving data-driven insights to bolster their business outcomes is not as daunting as it seems.

Analytic Process Automation (APA) is the answer to this mythical “data unicorn” for SMEs and this platform puts them, and their business knowledge, at the forefront of generating specific, customised and actionable outcomes.

An APA platform provides any organisation, such as a SME, a unified, human-centred platform experience that automates access to data analytics, data science and process automation all-in-one. Powered with hundreds of ready-to-use automation building blocks in the platform, any and every SME employee of varying degrees of data literacy can leverage their industry specific skills and data to deliver analytics-driven outcomes. Behind the mythical magic lies four guiding principles of APA:

Data Discovery to Auto-Discovery 

The time-consuming and resource-intensive tasks of operationalising analytics is now removed with machine learning (ML) technology. The APA platform transforms the cumbersome tasks of manual data discovery to an automatic discovery of critical assets. This process can take place across data in any format, be it pdf files, data lakes or data platforms.

Self-Service to Auto-Service

In the past, insights-driven decisions were heavily reliant on data-literate employees who can easily locate, quickly analyse and efficiently share relevant data. However, with the present-day APA platform, insights and business processes in applications are now automated, and recommendations are auto-triggered.

Employees from SMEs can easily construct their own diagnostic, predictive and prescriptive analytic applications in a fuss-free, drag-and-drop environment.

Manual Coding to Auto-Generation

With limited financial resources and lack of IT infrastructure in most SMEs,

hiring data scientists adds an unnecessary strain to their top-line, and solutions that heavily rely on coding, becomes a formidable barrier to entry in proliferating analytics for business outcomes.

However, the modern analytic capabilities provided in the Alteryx APA platform offer a code-free, auto-generation of models and algorithms. Removing all the hiring and technical barriers, employees of SMEs can simply operationalise AI and machine learning without prior experience.

Embedded Insight to Auto-Process

Going beyond the end-goal of closed-loop intelligence to embed insights in business processes, the APA platform delivers insights and triggers actions in an automated manner. Upon introducing the intelligence into a business process, each resulting response is continuously improved with each transaction.

Today’s self-serving analytics and data science solutions have proven to simplify and broaden the accessibility of data, analytics and data science to every organisation and employee. Zeroing in on mobilising SME’s greatest asset – their workforce, APA enables SME owners and employees to accelerate insight-driven business outcomes with AI and machine learning. With advanced diagnostic, predictive and prescriptive analytics, machine learning and AI at a SME’s fingertips, they can be their own data unicorn of today.