Amid the rapid expansion of our technological world, a new business standard has emerged. Today, the modern marketplace is increasingly fuelled by numbers, trends, and statistical insights. At the core of every business decision made is data, as both customers and employees are generating more information than ever before. Put simply, the value of becoming more data-driven can no longer be ignored. It was time we adapted to this shifting landscape.
As an organisation that aims to help clients and partners become relevant in the present and future through forward-thinking practices, one of the many questions we started to ask ourselves lately was: “Are we applying the same innovative ways of working at PALO IT as well?”
The answer was not as much as we would like to, especially when it comes to data.
To swiftly address this disparity, we embarked on a data transformation journey early this year that would shape the way we operate at PALO IT and accelerate our competitiveness. The five most significant changes we aimed to achieve were:
- Data Democritisation — Easily accessible data will allow us to get insightful information, and enable us to make faster and more informed decisions
- Insights Automation — By automating our internal and external processes, we can focus on more valuable and creative tasks
- Value-Driven Initiatives — With data insights, we will be able to measure the impact and return of investment of our initiatives from a financial, manpower, and performance perspective
- New Businesses — Being data-driven will enhance our existing offering and give us the ability to identify new business opportunities
- Increased Profitability — Data will help us discover and eventually tap on sources of incremental revenue
Our Framework at a Glance
As part of our data transformation framework, we established eight dimensions within our organisation that needed to evolve.
Our Transformation Dimensions
- Data Governance — This covers building a standard framework for data collection and access controls. The purpose of this framework is to ensure only the right people have access, as well as serve as a central location to view metadata
- Legal & Compliance — This covers enforcing applicable compliance standards wherever and whenever we do business or collect data. A robust data governance system, and audit checks and controls, are two of the key tools that facilitate success in compliance
- Ethics & Transparency — This covers ensuring transparency in data sources when building Machine Learning models, with the primary aim of eliminating bias so that we can ably serve all cross-sections of the client base
- Culture — With a strong organisational culture, we can ensure longevity of good business practices around data and governance
- People — No organisational initiative will be successful without giving people the tools and training to work with data
- Communications — This covers creating a coherent communication plan to update all employees on the status of the company-wide data transformation, highlighting process impacts and improvements
- Leadership Engagement — Our leaders will add further context to communications, distilling organisational goals into ground-level process updates and improvement. They will also be critical in ensuring people understand these changes
- Platform & Tooling — This is the implementation layer that underpins everything above. This involves leveraging the right technology plan, architecture, implementation, and support plan
Naturally, this massive undertaking would also require a broad set of diverse, distinct, and complementary roles working in synergy to ensure data quality, compliance, and security standards are met.
Our Transformation Team Structure
By identifying these individuals roles and pertinent responsibilities, we were able to look at issues holistically and deliver solutions that cover all aspects of a problem. In the same agile manner we approach our projects, we utilised a product backlog, weekly sprints, scrum ceremonies, and regular feature releases — all backed by a clear communication plan.
Data Platform
We are designing and building a resilient data platform where data can be secured, structured, and readable. It will also be scalable and robust so that we can be incremental in what we develop next and where we apply it to. Take a look at our architecture below.
Our Data Platform
Data Ethics
Ethics is the foundation of any data-driven organisation and should be at the centre of everything a company pursues. Throughout its life cycle, data flows through many people and systems. The rapid proliferation of data quantities, format, and usage, has given rise to increasing instances of data misuse. During this critical juncture, we must strive towards becoming and being ethical and remaining conscious of the fact that data ethics goes beyond security and privacy.
Like most organisations, we face a difficult challenge when it comes to ethically-informed data collection, sharing, and usage. That being said, we have several measures in place to ensure that data ethics is properly systemised and enforced. They include:
- Data Principles — These principles define the do’s and don’ts of how we use data, bringing greater accountability while identifying reference points
- Ethical Committee — Our ethical committee is entrusted with maintaining transparency and addressing problems when they emerge
- Ethical Framework — This framework helps us translate our data principles into tangible assets
- Data Ethics Canvas — This canvas helps us anticipate potential ethical issues, frame the right questions, and serve as a overall guide before we begin working on new projects
With our approach, our organisation will be empowered with clearly defined practices driving honest and appropriate behaviours toward data utilisation.
Building Blocks For Innovation
As our data transformation roadmap continues to crystallise in the coming months, so will many new and experimental ideas. Our framework will empower employees to come up with data-driven solutions that will address existing and future problem statements.
For example, one such initiative that we’ve already successfully launched is Maya, an AI chatbot developed in collaboration by our People Experience Team and Data Dojo. Built to streamline the HR workflow, Maya is designed to answer a set of ever-expanding queries with ease. Leveraging Natural Language Understanding capabilities housed in Google’s Dialogflow, Maya will continuously evolve to process more data (in the form of training phrases) and eventually become a fully-fledged virtual member of the organisation.
Further down the pipeline, we’re also exploring data-driven solutions for employee, finance and project management, and sales and marketing automation.
The Future Is Data
Data has become a major asset to competitive advantage in a business world that’s growing smarter every day. An organisation’s ability to stay ahead of the curve hinges on how well it can leverage data, apply analytics, and implement new technologies. In effect, this has galvanised us to take action and revolutionise the way we operate. Underpinned by a clear and robust strategy, our data transformation journey will serve as a touchstone to our offerings, enhancing the way PALO IT invariably delivers more impactful products and solutions to our clients and partners.
