Subramanyam S, founder, president and CEO of AscentHR, is an entrepreneur with immense experience in Finance, Legal and Business management. He is a corporate lawyer and a fellow member of “The Institute of Company Secretaries of India”. A finance and business management specialist, it was Subramanyam’s quest for bringing innovative solutions and services in the HR industry that led him to build AscentHR. His experience includes exposures in Advani Oerlikon group, Shonk Technologies in finance, HR and corporate legal services.
At the core of all enterprise-level decision-making is valuable, processed, organized information. It is gathered in an orderly fashion over a well-defined period. The availability of this usable information is no coincidence. It is made possible through relentless work invested into collecting data, organizing it into searchable formats, and maintaining the repository of information in a query-ready state. This process of ensuring that data is kept ready for use comes under the contemporary moniker ‘Management Information System’ or simply MIS.
Importance of MIS to a business
No business in modern times tries to get by without an MIS. And for those that are convinced of its efficacy, the applications to be harnessed are plenty. The reliance on MIS reports has only grown in the past two decades and is not likely to dip anytime soon.
An MIS combines both the software and hardware capabilities for housing an organization’s data repositories. All operations required to keep the MIS in working order require specialized knowledge of Computer Systems. The outputs of an MIS are the reports it offers. A business could maintain databases and MIS related to Finances, Sales figures, HR metrics, Budgets, Trend reports, or Exception reports. Across an organization, various middle and top-level executives would require these reports periodically to make the best possible decisions in line with established organizational goals.
Analytics in the scheme of a business
Much has been written about data-led insights being the in-thing. It continues to be valued because Analytics is the broad-range area of study that has made quantitative, instructive decision-making possible. Data-led decisions stand the test of varying business cycles. Accumulation of data with a specific purpose in mind, and the utility of the said data further downstream are the prerequisites of effective analytics.
Analytics are used by businesses to get answers to deeply-specific queries. Using past-data, future trends and projections are made to help a business make crucial estimates and preparations for resources. With the pull and push of demand and supply underscored by a multitude of factors and drivers being what they are, analytics is the lone ‘sensible’ way of making decisions.
Analytics and MIS – the invariable meeting point in business strategy
If the maintenance of MIS is the core on which all decision-making is based, Analytics is the process of manipulating the reportage gathered over time to produce usable insights. Predictably, these two efforts are all the better for a keen sense of business understanding to guide the avenues along which they are deployed. This intangible skill is called ‘Business Intelligence’.
Business intelligence is central to the use of MIS and Analytics to optimize results. The tenets of Project Management may be used to coordinate all these activities and proceed gradually towards the listed goals.
The use of data-led techniques like Analytics on the MIS where Business Intelligence is employed to drive decision-making is sometimes lumped together under the umbrella term ‘Business Analytics’.
Enter Automation in Business Analytics
Automation of oft-used processes reduces time and resources expended on it. The stakeholders involved in the decision-making worry less about the time taken to separate insights from the noise when automation is on point. Instead, they focus on the import of the insights, and how they can be deployed towards greater efficiency of their operations in the future.
The freed-up cerebral equity is then diverted to creative exploration, planning, and analyses which do not fall under the purview of numerical quantities. Examples of areas that stand to benefit from effective deployment of Automation are Corporate Social Responsibility, Sustainability, and Environmental, Social, and Governance (ESG) criteria.
Cost-savings are only a part of the picture. The amount of trouble saved in repeated tasks, especially across distributed teams, contributes directly towards process harmony and outcomes are optimized. Where errors enter the workflow, their origin can easily be flagged and corrections can be enforced within moments. The configuration required for these additional checks and balances is programmable within a few extra steps.
Automation is scalability-friendly. Like any good piece of tech, Automation in MIS and Analytics can cushion dramatic shifts in demand, with little or no loss. Housed on cloud platforms or proprietary storage databases, automated workflows run predictably for pre-defined sample sizes, but can also be altered with minimal effort when the size changes.
These facets of Automation prove that it’s not just a good-to-have feature, but a necessity. Forward-looking businesses cannot afford to miss out on the many advantages Automation offers.
Automation of workflows and task families across MIS and large datasets on which analytical procedures are usually carried out is open-ended. There are virtually few limitations to its applicability. With the right infrastructural capabilities, the full scope of automation across data sets can be envisaged by corporations. The transferability across applications and environments becomes possible by virtue of API-integrations and plug-and-play automation systems.
As such the applications for automation are only set to increase in a largely-digitized business panorama. The true extent of it is, at the moment, only limited by the human elements that play the role of facilitator-and-master-controller.