The RIGSS Blog

“In God we trust. All others must bring data” is a quote by W. Edwards Deming emphasising the importance of data-driven decision-making.

Data-driven decision-making is using facts, metrics, and data to guide strategic decision-making as opposed to making decisions based on your intuition, emotions, hearsay or blind faith. Many people rely on intuition in making important decisions, but the probability of making better decisions increases manifolds when it is backed by data.

In the past, data collection was a challenging endeavour. But this is no longer the case with the advances in Information Technology. Every organisation already owns large collections of data in their IT systems. ‘Data is the new oil’ has almost become a cliché today. We have been discussing data warehouses, big data and data science for many years. And lately, large collections of data have played an important role in the development of machine learning and AI technologies, taking the use of data to the new frontiers of technology beyond simple statistical analysis and drawing inferences.

A McKinsey study found that organisations using data to make decisions are more likely to be profitable and can more effectively retain and acquire customers than those who fail to use this approach. Research suggests that 90% of enterprise professionals today report that data and analytics are key to their core transformation initiatives.

Data-driven decision-making offers a multitude of advantages for both organisations and nations as a whole. Here are some benefits of data-drive decision-making:

More informed policy or strategic business decisions

Data-driven decision-making enables organisations to spot trends, forecast accurately, and devise optimal growth strategies. Governments no longer have to rely solely on intuition and limited data; they now access vast structured and unstructured data for evidence-based policymaking. Using advanced data analytics tools, governments can extract insights from social, economic, and environmental trends, leading to more effective policy formulation and improved outcomes for citizens.

Improve efficiency and productivity, and hence profitability

Utilising data-driven decisions significantly boosts company profitability by offering insights for increased sales and reduced losses. Relying on solid numbers instead of instincts enables logical, confident decision-making. Data uncovers trends, forecasts the future, and reveals opportunities akin to night-vision glasses in the dark.

In government operations, data-driven decision-making enhances efficiency by identifying inefficiencies, optimising resource allocation, reducing waste, and improving services in sectors like healthcare and education. Clear data-driven decisions eliminate uncertainty, thereby ensuring confident choices, fostering team conviction, and enabling faster responses to market changes, which is crucial for staying competitive.

Improve customer experience

Satisfied customers are key to business success. Data-driven decision-making boosts customer satisfaction by regularly measuring it, gathering feedback, spotting trends, identifying issues, and optimising processes and services. With solid data, you can better understand customer sentiments and exceed their expectations.

In government, a data-driven approach enables personalised services based on demographic data, user input, and consumption patterns. This enhances healthcare delivery, predicts disease outbreaks, and optimises resource allocation. Similarly, data-driven decisions in public safety enable pre-emptive crime prevention and focused law enforcement, ensuring community safety and security.

Examples of data-driven decision-making

Google is a company in which fact-based decision-making is part of the DNA and where Googlers (that is what Google calls its employees) speak the language of data as part of their culture. At Google, the aim is that all decisions are based on data, analytics and scientific experimentation. For example, through their “people analytics” initiatives, Google collected data from over 10,000 performance reviews and compared it to employee retention rates. They discovered key behaviours that high-performing managers consistently exhibited and used this data to create training programmes to develop those competencies.

In Bhutan, the Royal Institute for Governance and Strategic Studies’ (RIGSS) research paper, “Professionalising Domestic Help in Bhutan,” whose data-backed analysis showed the prospects for professionalising domestic services, is an example of collecting data to help evidence-based policymaking.

Adopting data-driven decision-making

Failing to embrace data-driven decision-making in your workplace today can indeed lead to adverse consequences. Whether you are employed in the private sector, a State-Owned Enterprise (SOE), or the public sector, the benefits of being data-driven are evident.

In the private sector and SOEs, not adopting data-driven approaches can put you at a disadvantage compared to your competitors. Your competitors are likely using data to optimise operations, understand customer behaviour, and make informed strategic decisions. Without leveraging data, you may find it challenging to stay competitive, innovate, and meet the evolving demands of the market.

In the public sector, not being data-driven can have repercussions for citizens. Embracing data-driven decision-making allows governments to allocate resources more efficiently, design effective policies, and enhance public services. Failing to do so may result in suboptimal outcomes, increased costs, and a failure to address the needs of the population effectively.

In both sectors, the value of data-driven decision-making is clear: it leads to better outcomes, improved efficiency, and a competitive edge. Therefore, not adopting data-driven approaches today can indeed be a missed opportunity and potentially detrimental to your organisation or the citizens you serve.

So, how can you adopt data-driven decision-making at your workplace?

Step 1: Make data-driven decision-making the norm

First and foremost, your organisation needs to make data-driven decision-making the norm by ensuring that all decisions are based on data, not intuition alone. The organisation should promote a culture that encourages everyone to think critically and ask questions. This is a mindset shift, and everybody in the organisation should be on the same page and live the slogan “In God we trust. All others must bring data.”

Train your employees in data skills in line with this norm. There are various tools to master. The kind of training you provide for employees at different levels could differ. The following are some of the data skills that experts suggest job seekers to master in 2023:

- Data cleaning and preparation

- Data analysis and exploration

- Statistical knowledge

- Creating data visualisations

- Creating dashboards and reports

- Writing and communication

Step 2: Collect and prepare data

Before collecting and preparing data for analysis, it is essential to have a clear understanding of the purpose. Are you aiming to enhance your processes, uncover vulnerabilities, or pinpoint your most profitable sales channels? What specific questions do you intend to address with the data?

Consult with your internal teams and decision-makers to understand the questions they seek to answer using data. Identify their current data sources and explore opportunities for enhancement. Based on their input, conduct market research to gain insights into how other companies tackle similar challenges. This will enable you to identify and improve the necessary data sources and market research tools to meet your company’s decision-making requirements. At the same time, evaluate the data that exists already within your organisation. Many organisations possess substantial data resources, albeit often in disorganised form.

Also note that, in today’s digital landscape, modern consumers leave extensive online data trails, allowing businesses to scrutinise aspects ranging from their interests and behaviour to purchasing preferences and brand associations. By acquiring more comprehensive, reliable, and accurate data, organisations can expedite data-driven decision-making, facilitating quicker adaptations and agility.

To analyse and interpret data effectively, you must identify all existing and potential data sources and establish a centralised data repository. This can be a challenging task if decision-makers currently rely on disparate data sources, posing risks of data duplication and inaccuracies. Therefore, it is imperative to ensure that your data is both credible and pertinent to facilitate efficient decision-making.

Most importantly, you should know how to use the right tools and techniques to perform these tasks.

Step 3: Analyse your results, look for patterns, and explore

Now that you’ve gathered and structured your data, it is time to analyse it from relevant perspectives to uncover answers to your queries. This is where the importance of data visualisation and dashboarding becomes evident. By utilising various visualisation techniques such as charts, graphs, trend lines, and more, you can present your data in a more accessible and comprehensible manner.

For instance, Google Analytics stands out as a potent tool capable of furnishing businesses with valuable insights regarding their website’s performance. Whether it is tracking website traffic or gaining insights into user behaviour, Google Analytics equips businesses with the data they need to make informed decisions and enhance their online presence.

Additionally, there are several other popular tools available for data analysis, including Microsoft Excel, Python, R, Jupyter Notebook, Apache Spark, SAS, Microsoft Power BI, Tableau, and KNIME. These tools offer diverse functionalities and capabilities, empowering organisations to extract meaningful insights from their data and drive data-driven decision-making.

Step 4: Develop insights and make decisions

Creating data visualisations is important, but it is just one aspect of the process. To truly understand your data, you need to delve deeper into analysis. This means connecting the dots across different datasets to determine if they collectively address your questions and yield valuable insights for decision-making.

Once you’ve unearthed these insights and have concrete, data-backed answers to your queries, it is crucial to share them effectively with your teams and stakeholders. Employing the technique of data storytelling is instrumental in this regard. It enables you to provide your audience with the necessary context behind the data, helping them grasp both the broader picture and the finer details that underpin your decisions. Moreover, data storytelling facilitates the engagement of key decision-makers within your company, fostering transparency in the data-driven decision-making process.

Data Protection and Privacy Concerns

Embracing data-driven decision-making offers numerous advantages, yet it also presents challenges that governments must effectively address. One significant hurdle involves safeguarding citizens’ privacy while harnessing the power of data. Striking the right balance between data utilisation and privacy protection is essential to maintain public trust.

Stringent regulations, like the EU’s General Data Protection Regulation (GDPR), have been implemented to uphold data protection and privacy standards. Companies and organisations handling data of EU citizens are mandated to comply with GDPR. Similarly, in Bhutan, adherence to relevant data protection and privacy provisions in the Information, Communications, and Media Act of the Kingdom of Bhutan 2018 is mandatory.

Both the GDPR and the ICM Act of Bhutan prohibit sharing personal data and information without the individual’s consent. One effective approach to overcome these restrictions is data anonymisation. This process involves safeguarding private or sensitive information by removing or encrypting identifiers that link an individual to stored data, ensuring privacy while enabling the beneficial use of data for analysis and decision-making.

Data Sharing by Government Agencies

While Europe has one of the strictest privacy laws, it also champions a movement called the Open Data. data.europa.eu is a platform that gathers metadata from public data portals across European countries. This metadata includes information about the availability of Public Sector Information (PSI) and the advantages of using this data. Likewise, the United States government’s open data portal, data.gov, publicly shares a wide variety of datasets from different agencies. Besides these, there are many other open data portals.

The Open Data movement is an effort aimed at fostering the accessibility and availability of data to the general public. It encourages governments, organisations, and institutions to share their data in a format that is not only readily accessible but also user-friendly and comprehensible. The overarching objective is to promote increased transparency, facilitate collaborative efforts, and stimulate innovation by granting the public open access to valuable information. This movement seeks to empower individuals, businesses, and communities with data-driven insights, enabling them to make informed decisions and create innovative solutions for various societal challenges.

Public Sector Information, often referred to as Open (Government) Data, encompasses data collected, generated, or funded by public entities. This data (after anonymisation is applied) is made accessible for reuse by the public, without restrictions, under specific licensing terms. In Bhutan, The Government Technology Agency (GovTech) has put in place a mechanism to enable data sharing between government agencies by using APIs through the Electronic Government Interoperability Framework (e-GIF) (See: https://egif.dit.gov.bt/).

Conclusion

Data-driven decision-making encompasses the methodical and purposeful utilisation of data to shape business strategies, streamline operations, and improve overall performance. Instead of solely depending on intuition or historical experiences, data-driven organisations make decisions guided by insights derived from data, ensuring a more informed and evidence-based decision-making process.

As we’ve discussed earlier, both government and private organisations stand to reap substantial benefits from data-driven decision-making. However, it is not enough to recognise these advantages; fostering a culture of data-driven decision-making requires executive advocacy and a supportive community that actively embraces such practices. When these foundational capabilities are in place, it encourages individuals at all levels of an organisation to routinely question and explore data, uncovering valuable insights that drive actionable outcomes.

Many companies and nations have excelled in leveraging data for effective business and policy decisions. While there is so much emphasis on data-driven decision making and data democratisation, Bhutan still has a significant journey ahead in this crucial aspect of governance and business. And with the renewed focus on economic growth and leveraging technology for nation building, institutions such as RIGSS will assume even bigger role in promoting a culture of data-driven policy-making and governance in the country. Both our businesses and the government apparatus stand to gain immensely by harnessing the power of data to inform and enhance decision-making processes.