Governments and Decision Making: Science or Intuition and Experience?.

“Our problem has not been and will not be in the formation of committees and working teams to find solutions and recommendations for our current and future challenges, but it lies in the need to improve the work of those committees with information and knowledge arising from the analysis of data is related to the work of those committees.”
Countries’ economies are changing for the better with the development of technology, and data in the twenty-first century enhances all official or commercial activities, as it is one of the most important sources of enabling growth in the wider economy. It can be clearly said that governments have become one of the largest producers and collectors of data in many different fields. For example, governments may collect or produce data related to civil status, land, taxes, social security, residence and borders, traffic, work, telecommunications, companies, investments, social media data and others. Data is considered the “new oil” in our time, but this oil needs a combustion engine to convert it into different energy sources that can be used, and in the case of data, the combustion engine is represented by the technology of the Fourth Industrial Revolution, the most important of which is data science and (big) data analysis technology. In fact, the process of collecting and producing data in itself has very limited importance and value, unless that process is accompanied by the use of data science and analysis techniques that will create information and knowledge of value and benefit in the decision-making process. .
In economically developed countries, data science and analytics play a crucial role in enabling government departments to save hundreds of billions of dollars by improving operational efficiency. Data science in these economies also plays a major role in increasing government revenue and working to reduce unemployment rates by developing governments’ ability to innovate and innovate, and develop new products, services and business models.
In an urban environment like the city, the role of data science and data analysis techniques is to make significant impacts on the quality of life of citizens, especially when a data analysis product is used in the decision-making process. This aspect is part of the “smart city” concept that relies on investments in human and social capital, traditional (transport) and modern (ICT) communication infrastructure, and wise management of natural resources that will fuel sustainable economic growth and citizens of ‘ a high quality of life Quality through participatory management. An example of this is the use of smart meters and other sensors to reduce energy consumption by monitoring usage in real-time and analyzing that data to gain insights that are of great value to help future decisions with a high degree of confidence and certainty take.
Weather data can also be used to predict whether there will be a weather emergency, such as floods, landslides, earthquakes, etc. This forecast can be used to issue warnings or evacuate citizens in time. Patient data can also be used to monitor the patient in general during ongoing treatment or to issue reminders when examinations or vaccinations are needed. Traffic data analysis can also help citizens to verify the best time to use certain roads or use public transport, and the use of this technology in an optimal way helps to increase the efficiency and effectiveness of public transport management by the arrival times of accurately predict a fast frequency. bus, for example. The use of this technology helps the Public Transport Department to reduce traffic and congestion by providing suggestions regarding alternative and practical transport options in line with the current environment and conditions. On the other hand, governments can take advantage of this technology by creating a system that collects and analyzes on a large scale the amount of data received from various sources to help them track down criminals and prevent them from money laundering , as well as to improve internal security. In another context, and by relying mainly on data science products, decision-makers will have a greater degree of confidence and certainty when determining the needs of different geographical areas in the country, such as the establishment of health centers, hospitals, schools or universities, as well as the prioritization of each of those needs must be placed within time plans, in accordance with the state budget for that period.
Based on the above, we realize that data science plays a major role in improving the government decision-making process by involving a data-driven model in governance, using data to monitor citizens’ attitudes and opinions, and to innovate ways around government. discover. business models through data analysis and correlation. And risks and opportunities that we could not observe before, as well as to simulate different scenarios aimed at improving current government services, developing new services, or creating a clear vision of what the government wants to achieve. It can also take advantage of data science in the industry and strengthen knowledge of current or expected future regional and international risks and opportunities and prepare for them in advance. On the other hand, we are also aware of the extent of the technical and non-technical challenges we face in the path to optimizing the use of data science and analysis, which is represented in the availability and quality of digital data, organizing and linking different data, storing and sharing data, and the process of linking decision-making to knowledge resulting from data analysis, as well as Availability of the qualified human factor to handle data at all stages of the analysis process, leading to the employment of the product of the analysis in the decision-making process.
From a personal point of view, the biggest challenge for data science in our beloved country lies in the culture of decision makers and the degree of their acceptance of the shift to making decisions based primarily on information and knowledge resulting from data analysis and secondarily on the vision and experience of decision makers instead of traditional methods based primarily on knowledge and experience Personality, intuition and guesswork are secondary to data analysis products (if any). Here we emphasize the need to improve the work of these committees with information and knowledge resulting from the analysis of data related to their work.
Despite the importance of data science and the benefits that can be achieved at the national level, which we mentioned earlier, we find that national initiatives and projects in this area are very limited and dominated by individual character, and they are significantly behind many neighboring countries and developed countries despite our need The urgent need to take advantage of the smart and cheap solutions provided by the technologies of the Fourth Industrial Revolution, given the great challenges we face at home. Therefore, we must start by formulating a general framework or a national government system that deals with this matter and work to promote a culture of decision-making based on the data analysis product, and that policy-making, priority planning and the definition of the goals that to be achieved must be derived from this system and accompanied by a systematic time plan.

* Data Science Expert and Dean of the College of Business at Al-Ahliyya Amman University

Leave a Comment