Different organization require different types of analytics
Data is like garbage. You’d better know what you are going to do with it before you collect it – Mark Twain
Very aptly so. All data that is collected unless relevant and useful for our analysis would turn out to be a pile of garbage. Hence data has to be carefully screened, ideally at the source and with an intent to turn them into insights. Analytics is not a one size fits all. Different organizations have different needs and the analytics employed has to cater to and be tailor made to meet these needs of the organization. The analytic tools are chosen based on the value proposition they offer, and the difficulty level of task assigned to it. Hence organizations would benefit if they narrow down on their prerequisites based on the level of growth.
So, At first lets dwell into what are the different classifications of analytics? It is classified into descriptive, diagnostic, predictive and prescriptive based on the different requirements of the organizations. They vary from identifying the problems faced by the organization to predicting the future outcome awaiting the organization and one step further sometimes to making the outcomes favorable.
1. Descriptive Analytics is the kind that focuses on the WHAT It analyses what has happened with regard to an organization. This classification of analysis emphasizes on the reasons behind a success or failure. Most social analytics are descriptive analytics. For e.g: no. of page views, average response time etc.
2. Diagnostic – This kind of analysis focuses on the WHY question and goes a step ahead with regard to understanding the underlying problem. This helps to see detailed and in-depth attributes and characteristics of the data.
3. Predictive – Predictive analysis tries to draw out predictable conclusion. Here past data is utilized to draw out these reasonable scientific predictions. These can help in setting realistic goals and helps reduce expenditure. It is almost as similar to reading into your future. Predictive analysis helps to chalk out possible outcomes by using statistical and machine learning algorithms.
4. Prescriptive – This method of analytics takes the essence of predictive analytics and suggests ways to achieve a desired outcome. They can give insights into how to tilt the predictions to our advantage. When implemented right and with the adequate data points, prescriptive analytics can suggest actions to provide desired outcomes with a high degree of accuracy. Prescriptive goes a step ahead of predictive to manipulate outcomes that are favorable to the organizational context.
Next, we dwell into organisation levels in the context of implementing analytics. We have classified organisations into 4 levels considering the complexity of business and volume management. Complexity of business involves the organisation reporting structure how many levels of reporting are present, involvement of top management, depth of mid-level management, no of offices, no of employees, etc. None of these parameters are golden rules but only indicative factors. None of them are aspirational. We believe these organisation levels is an outcome of processes and strategy employed by a company.
1. Small business / Start up – Characterized by low volume and less complex activities. These are businesses who deal with very less data that can be processed at the lowest lead time. These organizations are highly agile and changes to processes and strategies can be implemented swiftly. Descriptive and Diagnostic Analytics can help in reinforcing the instinctive view of the management. These businesses can truly benefit by looking at Predictive analytics in the form of Market research and industry reports to help them scale and develop better disruptive products / services.
2. Evolving Organization – As any small business or startups grow, so does their data grow in size exponentially and the analytics employed should be tweaked to ensure it supports the aspirations of the organization. They should focus on developing a strong data strategy which involves collection of maximum data at its source effectively and efficiently. Such organization should focus on improving their diagnostic analytics efforts and plan for predictive analytics as the data patterns grow.
3. Opportunistic Organization – These organizations are superior and can benefit from choosing opportunities that can reap maximum benefits. Data can be used as a measuring tool for these organizations to take decisions. They can develop models and perform detailed diagnostic analytics to grab the first mover advantage and maximize their growth. They should focus on building a process which compels usage of strong analytic frameworks with a mindset that data begets information and information is liquid currency.
4. Large and Complex Organization – These organizations are characterized by large volume of data, with high level of complexity in processes to ensure smooth functioning and typically have data strategies including analytics at department or team level. Most of these organization tend to have implemented high level of diagnostic analytics at department levels as individual silos. The real magic happens when these silos are connected, and a holistic analytic approach is developed for the organization as a single entity. This gives the benefit of leveraging data collected, analysis performed and insights from individual silos. These organization should focus on an organization level analytics strategy for accomplishing their long-term goals. They should use predictive and prescriptive analytics to maximize their strengths and mitigate risks. This however, is easier said than done and is often a challenge for the top management to put in action. A highly successful approach would be to start with an Exploratory Data Analytics which can help in identifying the internal data generated, analytics performed, analyze the extend of external data that can be used to corroborate the internal data and recommend the most suitable course of action.
“An organization’s ability to learn, and translate that learning into action rapidly, is the ultimate competitive advantage – Jack Welch”
Author: Jerrin Thomas; Co-author: Benila Jacob