Business analytics (BA) is the iterative, methodical exploration of an organisation’s data, with an emphasis on statistical analysis. Successful business analytics depends on data quality, skilled analysts who understand the technologies and the business and an organisational commitment to using data to gain insights that inform business decisions. Industry experts share insights on the types of business analytics and how organisations should go about selecting the best suited type for their business.
Data-driven companies treat their data as a corporate asset and actively look for ways to turn it into a competitive advantage. The success of business analytics largely depends on data quality and skilled analysts who understand the technologies and the business, and an organisational commitment to using data to gain insights that inform business decisions.
Once the business goal of the analysis is determined, an analysis methodology is selected and business data is acquired to support the analysis. Data acquisition often involves extraction from multiple business systems and data sources, then cleansing and integrating data into a single repository such as a data warehouse or data mart.
Compared to the West, the Middle East has been relatively slow in its widespread adoption of analytics, especially among small and medium-sized businesses (SMBs). While remote work has served as a catalyst to drive businesses in the SMB segment to explore analytics tools to offer better visibility and measure productivity, industry pundits expect to see a rise in the adoption of analytics solutions among SMBs in the Middle East and also increased adoption within individual departments of an organisation at enterprise level.
Stephen Gill, Academic Head, School of Mathematical and Computer Sciences, Heriot-Watt University Dubai, said business analytics is the process of applying Big Data, statistical analysis and data visualisation to extract meaningful insights needed to make informed business decisions. “Business analytics is an indispensable tool in today’s highly competitive marketplace. Companies across most industries are spawning vast amounts of data which, in turn, has spurred the need for people who know how to interpret and analyse that data,” he said.
Ghaith Ghazi, Regional Vice President – Mediterranean, Middle East and Africa, Tableau Software, said Middle East companies that increasingly rely on data analytics can make better decisions and often see a positive change in culture too. Ghazi said a data culture interacts with changes in corporate culture and processes. “This means a profound change in mentality and in practice, makes data-driven decision-making the standard and ideal at all levels of a company. Such a transformation does not happen overnight, but in the long term it benefits the entire company, especially during periods of change,” he said.
Nauman Qureshi, VP, Product at STARZPLAY, said business Analytics is not anything new to the Middle East as companies in the region have long been using technologies which enable businesses to analyse their performance.
Qureshi said the difference largely has been with the shift towards using cloud platforms such as AWS, Google Cloud Platform or Azure. “The ability to collect data from multiple sources and push in a central cloud data warehouse has introduced a robust set of new possibilities. A lot of companies in the region are still using older business analytics tools which restrict real time analysis of Internet services,” he said. “The newer, Internet age, companies in the region are natively setup with these cloud technologies and equipped with flexibility of utilising the latest and greatest functionalities offered by the global cloud providers. This pattern is not just limited to the Middle East but globally we see companies that are yet to move over their data warehouses into the cloud are limiting themselves.”
According to Gill, deploying the right business analytics strategy is not something that you can achieve overnight. “However, there are specific best practices that can help ensure that organisations are successful with their business analytics implementation as much as possible. These best practices include: establishing the business use case and the goal before implementing business analytics.
Determining the specific criteria for success and failure, validating models using the chosen criteria for success and failure and designing a methodology, narrowing down data, and identifying the internal and external factors needed for making a precise projection,” he said.
Types of analytics
Given the many types of business analytics in the market today, how should CIOs pick the type that suits their business environment?
Gill said the three primary types of analytics – descriptive analytics, predictive analytics and prescriptive analytics – are interconnected solutions that help companies leverage data. “Each type of business analytics provides a different kind of insight and choosing what to employ depends on the business situation at hand,” he said. “Descriptive analytics is the interpretation of historical data to discover trends and patterns while predictive analytics is the usage of statistics to predict future outcomes. Prescriptive analytics on the other hand is the application of testing and other techniques to establish what outcome will produce the best result in a particular scenario.”
Gill explained that CIOs need to choose the type of business analytics based on the stage of the workflow and the requirement of data analysis. “While the different kinds of analytics are usually implemented in stages, no one type of analytics is better than the other,” he said.
Rakesh Jayaprakash, Product Manager, ManageEngine, said business analytics can be broadly split into descriptive, diagnostic, predictive and prescriptive analytics. “Descriptive analytics involves interpretation of data in an understandable form, diagnostic analytics helps answer why something happened, predictive analytics helps forecast the most likely outcome based on historical data and prescriptive analytics suggests favourable outcomes for various courses of action,” he said.
Jayaprakash said for an organisation beginning its analytics journey, a good starting point would be to get descriptive analytics right because that forms the basis for the other stages. “Humans are good at looking at historical data and figuring out why something turned out the way it did; however, they’re not great at forecasting the future. Forecasting future trends helps a lot in making crucial decisions,” he said. “Predictive analytics can fill this gap. These are the two main areas CIOs should focus on while designing their analytics strategy and choosing the right analytics platform that suits their business needs.”
According to Ghazi, the transformation to a data-driven enterprise often starts in different places for different businesses – from the management board to individual departments. “Data analysts might see the growing need to expand self-service analytics within the company, for example. Companies should see this as an opportunity. By empowering employees with data, they can act more independently, assume more responsibility, hierarchies become flatter, and decisions are made more democratically,” he said. “In the long term, the entire company benefits from this, because traditional company processes are put to the test and often innovated.”
Business analytics pitfalls
According to Qureshi, one of the common CIO pitfalls is to keep acquiring more technology and not have the right understanding of how to structure the architecture and the business rules from the start. “The technology is only as good as the business logic that is provided to it. You cannot expect the data to be accurate if you have the wrong business logic setup from the start. There needs to be a strong sense of business understanding among the technical data team. Hire someone who is well aware of both the technical and business side,” he advised.
Skills challenge
While a data-driven approach to business can provide incredible business opportunities, many companies still struggle with the lack of staff skilled in analytics. Gill said one way CIOs can help address the skills challenge is by taking the existing staff and training them in new methods, new processes and new skills. “The other way is by acquiring new people who have the right skills to support the analytics transformation of a company,” he added. “Degree programmes such as Heriot-Watt’s MSc Data Science help you learn how to model, store and process data sets using the latest algorithms and techniques, and help you acquire the skills applicable to business applications, industrial applications and also scientific data exploration.”
Qureshi explained that data is a field that is growing really fast and it is a constant challenge to hire the right skillset with the right experience for your business. “There is a lot of input of new resources entering this field and even veterans of this industry are reskilling themselves on the newer cloud technologies. AWS Data Architecture certifications are becoming the go-to certifications in this field which equip people on how to use the latest and greatest cloud data functionalities offered by Amazon’s AWS,” he said.
Looking ahead, industry specialists point out that when choosing a business analytics tool, organisations should consider the sources they will be drawing data from, the nature of the data they will be analysing and usability. A good business analytics tool will be easy enough for the common business user, but also enables more advanced users to take advantage of its features.
