Using Data to Stay Ahead

Introduction

If you peek into the history of Science you will not fail to notice that great revolutions in Science were preceded by advancement made in the area of measurement. The pace of data collection was slower even three decades ago and obviously the pace of technological innovations was also slower since Scientists relied very much on data compared to intuition to leap forward. The advent of computer age has revolutionized the measurement processes and the advancement made in measurement in the past decade has helped businesses to capture data about various facets of their business in greater detail which earlier was not possible. This remarkable improvement in data capture technology coupled with afordable pricing, provides an opportunity for business leaders to take decisions supported by large volume of data rather than being driven by intuition. Is every business leader ready to take advantage of this data explosion by bringing changes to the style of their functioning by deploying systems to not only capture data using various data capture tools available but also hiring people who can distil the large volume of data to a form that aids decision making? What is required to become a data driven company is the focus of this essay.

Becoming data driven company

To become data driven company, you need to relook at the critical business processes where intuitive decision making is the current norm. Identify the reasons why data is not available to make the decisions.

Study the technological options that are available to transition to data driven decision making. The technology so chosen should not only meet the requirements of present business but also should be scalable to meet future needs. The technology available today such as ERP or CRM solutions, not only allows organization to collect large amount of data, but data collection 24/7 real time basis at the micro level. This micro level feedback though should help business leaders to initiate changes at quicker pace.

Such micro level data when collected for end customer can provide valuable insight into customer behaviour.

Once the technology is adopted to capture the data, the next step would be to have people in the team who can make sense out of the large volume of data that begins to be captured along with sound understanding of the business. Geting people with understanding to make sense out of large volume of data would not be an easy job compared to adopting the most appropriate technology for data capture. The skill sets that needs to be looked in people handling data has to be on their ability to design experiments, seting the sample size and establishing the data collection protocol. The "mathemagicians" you hire should not only be skillful in distilling the large volume of data that is thrown at them but also able to see the relevance of the data to the business needs. They should also be smart enough to gather data  that are not the usual fnancial indicators but data that helps them to understand customer needs, desires and customer satisfaction. Sadly the market does not have the desired number of people with skills capable to bring the business intelligence from the data.

Lastly the culture shift that needs to come within the teams to use data proactively and not try to rationalize decisions that are already made, through the use of data. At present most of the organisations use the data they capture to justify their intuitive decisions rather than use data in the frst place to arrive at correct decisions.

The data collection process should focus on problems, set experiments to collect data that help in arriving at correct solution. Managers should discourage teams to go by gut feeling but use the data capture tools that are available to capture the data and make use of it to arrive at solutions. This atitude shift would not be easy as this shift would mean, no longer manager's years of experienced judgement would stand by and instead through set of experimentation and results organizations would be taking their business decisions. Arriving at a new confdence whereby you allow data to speak is a trait that has to be systematically built within organization. Such a change in organizational culture whereby data is given prominence to years of experience of managers needs to be pushed by the top management.

Data Audit - The Future

The internal audit within companies would also require a paradigm shift. The auditors need to focus how efectively companies deploy data capture mechanisms, use skill sets to distil the data and take decisions backed by the data. The audit teams within organizations should look for "mathemagicians" who can do an efective data audit and such audits should not be left to conventional fnance or process auditors.

Conclusion

The availability of enterprise information systems such as ERP and CRM alone is not sufcient for organization to a transition to data driven organization. The real push will be to use data for decision making which will happen only in those organizations those are able to integrate the data capture technology with specialists with data crunching skills and culture to use data to back business decisions.