WIRC Bulletin - July 2018

Cost-Time-Quality of Data Driven Decisions by CMA Anil Kshatriya

Cost-Time-Quality of Data Driven Decisions

CMA Anil Kshatriya, Associate Professor of Accounting, Institute of Management Technology Nagpur

Interdependence of Global Economy has posed several challenges. One of them is an acute and urgent challenge of Cost Management. Time has come when countries, and particularly developing countries, have shifted their focus from ‘price’ to ‘cost’. We have several examples. China is a cost competitive nation. Korea is also is an excellent example of cost competitiveness. For India there is a need to become aware of this trend and take immediate steps to overcome this phenomenon. One of the reasons identified and discussed in this exploratory study is the use of traditional costing system in India. This has lead to erroneous decisions my several large and small companies that are trying to make their mark in the global landscape. This paper further discusses the role of effective cost management through the use of modern costing approaches like ‘Value Chain Analysis’ and ‘Activity Based Costing’.These approaches have been adopted my large companies all across the globe but there remains a substantial gap in their use with companies in India. This paper brings-out their contribution in making strategic decisions and their effective implementation. This is a concept review paper which can be further extended to empirical data analysis based on information collected from manufacturing and service based companies in India.

Herbert Simon, a Nobel Prize winning social psychologist, classified decisions into programmed and non-programmed decisions. Organizations create control systems to synchronize programmed decisions. But what they need for non-programmed decisions is intelligence and insight of their managers. Today business organizations across the globe are facing tremendous intellectual shortage. The rate of change in business environment is much faster than the rate at which businesses can adapt to this change. It is therefore imperative for innovative companies to use technical tools which can augment the cognitive bottlenecks in decision making process.

There are three dimensions to any decision which attempts to forecast future trends of the market. These dimensions are Cost, Time and Quality of data used in the decision making process.

  1. Cost – The cost of acquiring data can be substantially high. The high impact of data on decision outcome makes it valuable. Companies are willing to invest shareholder wealth in creating infrastructure which can capture relevant data. Companies try to minimize data acquisition cost. Costly data may not be necessarily more profitable. A cost-benefit analysis is essential to measure the financial contribution of data driven decisions.
  2. Time – Decision making during uncertain times has to be fast yet fairly accurate. One wrong step in estimating possible scenario can prompt to decisions which lead to dwindling sales. Timing of acquiring and using data is extremely critical. Value data obtained late can be more damaging than not getting access to data at all. Time translates into money. Any delay comes with opportunity cost which only escalates at every stage of decision.

 

  1. Quality – Quality is a relative term. In times of hyper competition, quality of decisions depends on quality of data. People can be only as intelligent as the data they process. Analytical tools can derive business intelligence but they cannot create competitive advantage if the quality of information they process is inferior to that of your rivals. In a non-linear digital economy it is very difficult for companies to differentiate themselves from competitors. Innovative solutions will result out of quality of decisions which are increasingly becoming data driven.

Cost-Time-Quality Intersection:

The decision making process is intersection of these three dimensions of data. Each of them affects the other. When cost and time is managed, quality of data improves and so do the decisions. This interaction becomes stronger with time. In mature organizations the bonds of cost-time-quality of data are very strong. But for evolving businesses the opportunity to connect these three dimensions is widely open.

Scientific decisions making is no longer a buzz word. It is real and it has started paying-off. From online e-tailers to large scale manufacturers, decisions are driven by data analytics. This is the new language of doing business and perhaps the new currency too.

 

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