On how to become a data-driven organisation
Olufemi Adedamola Oyedele, MPhil. in Construction Management, managing director/CEO, Fame Oyster & Co. Nigeria, is an expert in real estate investment, a registered estate surveyor and valuer, and an experienced construction project manager. He can be reached on +2348137564200 (text only) or femoyede@gmail.com
December 12, 2023379 views0 comments
All business organisations want to pave their ways to better and more accurate decision-making. In order to do these, they strive to redefine the business decision-making process in their organisations. A 2018 IDC study presents the top 10 predictions and key drivers for the information technology (IT) industry for the next five years. It highlights the mid-term and long-term challenges that enterprise IT teams face as they define, build, and govern the technologies required to thrive in a ‘digital-first’ world. The fourth prediction states that “CIOs will aggressively apply data and artificial intelligence to IT operations, tools, and processes”. These predictions were made based on data collected in the IT market. All organisations require authentic and adequate data for their successful operation. Among numerous business organisations that depend strictly on data for their operations is the oil and gas industry.
There are many cases in which real time and fast processing of data is crucial in the oil and gas industry. For example, fast processing of well data during drilling can result in identifying kicks and preventing destructive blow-outs efficiently. Data is like crude oil. It is invaluable, but if not well refined, it cannot be valuable. Supermarkets are business hubs that rely much on customers’ data, especially their purchasing power parity (PPP) and their shopping behaviours to stock and exhibit wares on shelves. Restaurants are other data-driven organisations that depend more on data for their predictions. Restaurateurs depend on data to establish at the locations where they locate their businesses and to prepare desired foods for customers. Construction companies are data driven organisations that depend on data like prices of building materials, unit cost of labour and weather (rainfall) forecasting.
Real estate developers require data like income of residents, housing needs, housing deficit and rent-passing to determine their developments. They also need the cost of construction and market value of their property development. Ceteris paribus, market value minus construction cost will give profit. A data-driven organisation is an organisation that uses data insights to guide its decision-making process. Data-driven companies rely upon data-driven processes, data analytic tools, and data-driven culture to generate business insights that help inform their decisions. Being a data-driven organisation means culturally treating data as a strategic asset and then building capabilities to put that asset to use not just for big decisions (big data) but also for everyday action on the frontline. All organisations require data for operation but some organisations use data effectively more than others. Examples of data-driven organisations include Globacom, Coca cola, Lagos Bus Rapid Transit, Mega Chicken, Independent National Electoral Commission (INEC) and Federal Road Safety Commission (FRSC).
There are small, medium and big data organisations. Big data organisations are extremely data-sets that may be analysed computationally to reveal patterns, trends, and associations between two or more factors, especially relating to human behaviour and interactions. Big data basically refers to data sets that are too large or complex to be dealt with by traditional data processing application software. Data with numerous entries offer greater statistical power and data with greater complexity may lead to a greater false discovery rate. There are four types of data – nominal data, ordinal data, discrete data and continuous data. Data can also be classified into two general types: quantitative and qualitative. While quantitative data deals with quantity and numbers and other quantifiable data, qualitative data deals with description and can be expressed in terms of language. Data analytical tools, software and machines are evolving every day!
Data can be analysed in tracking the shopping behaviour and habits of consumers to deliver hyper-personalised retail product recommendations tailored to individual consumers. Banks also monitor withdrawal patterns of customers and analyse them against historical customers’ activities to detect fraud in real time. Insurance companies deal with big data and function well based on efficient data analytics. Nigeria Railway Corporation (NRC) which deals with transportation of passengers and cargoes also depends on big data for its network of lines and transit of passengers and cargoes to their different destinations. In developed countries, all forms of transport like road, water, rail, air and cable are being integrated under a programme known as transport as a service (TaaS). TaaS, like Microsoft, Starbucks Coffee, Uber Transport and Amazon, depends on big data for efficiency, effectiveness and economy of operation.
Data-driven organisations exhibit the following features: (1) Data-driven culture – A data-driven culture is anchored by the leadership of the organisation. (2) Easy accessibility of data – All members of the organisation can access data easily and at any location and time. (3) Remarkable achievement with the use of data – There is remarkable achievement when data is applied in decision-making during business processes. (4) Data used to determine certainty in an uncertain business environment – Data is used to make more decision certainty in an uncertain future of work. (5) Data is the driver of decision-making – In all the organisations, data is the main input of the decision-making. Without data, these organisations cannot achieve their goals.
To become a data-driven organisation, (1) organisations must identify what they expect from their decisions; (2) they must align with key stakeholders on the role of data and analytics (D&A) in their decision-making process; (3) organisations must define, articulate and communicate the business value of D&A in their decision making process; (4) They must ensure they back the impact of their data on decisions in their business process; (5) They must articulate data-driven decision-making in their organisations.
Any organisation that does not use data in the present dispensation is an archaic organisation and may go the way of the dinosaurs. Data is relied upon for fast and accurate decision-making. According to Rick Villars, the group vice president of worldwide research at IDC, “Digital is now a permanent, yet dynamic fixture in the modern world, and the IT and communications industries themselves will be among the most transformed in the next few years. CIOs must establish procurement, development, and operation teams that align with as-a-service and outcomes-centric technology delivery models while ICT providers’ primary task is to help enterprises share, use, govern, and increase the value of data.” More corporate organisations are turning to ICT organisations to assist them on how to harvest, analyse and interpret data for their business gains.
Data-driven decision-making processes and strategies still need a strategic approach. To improve the quality of organisations’ decisions, organisations must first set goals and expectations for what their decisions must deliver. They must then align these objectives with execution of the decisions. This exercise involves the identification of the right data, correct analysis and interpretation of the data for an improved process. The most interesting thing about modern business organisations is that there is no business that does not depend on data for operation.