Data-Driven Decision-Making – Driving Continuous Improvement through Analytics

Posted on by Pradeep Sahoo

Did you know that the vast majority of organizations invest in technologies and tools to manage business operations but only recognize a small percentage of potential benefit? Even though “data” is the DNA to business decision-making, the root cause of most data challenges is getting the right data, to the right user, at the right time. With capable business intelligence and data analytics tools, organizations can achieve data-driven decision-making and pursue continuous improvement.

Overcome data shortcomings

Complex business processes, legacy asset maintenance and inadequate IT resources hinder transformation initiatives. In many cases business users end up deploying their own “Shadow IT” or manually maintaining their own version of their data. This is often due to inaccuracies in the data, their own limited access, and lack of availability of the data when it is needed to make decisions. In addition there are many other common reasons for data shortcomings:

  • Resources are occupied with maintaining legacy applications and databases
  • IT resources are not familiar with real-world business challenges
  • The process is so convoluted and risk-full to change unless there is a major top-down budgeted initiative
  • The data is there somewhere, but the stakeholder cannot get an accurate insights for their timely decision making
  • Data truths may vary, depending upon who, when and how the facts are generated.

Due to these data shortcomings, by the time the information is conveyed or visible, it could already be outdated and unusable. When data is inaccurate, it is often because the analytics cycle time – the time required to detect a problem in process, translate or transform the analytic insights into actions, monitor what just happened, and analyze the trend to predict what should happen – is not observed. Stakeholders and business users may fail to spot opportunities for improvement or test scenarios to bolster strategic choices.

Track results and make adjustments

Even when a decision is made, the job isn’t finished. It is important to monitor the outcomes of the choices and determine how they will impact the future. Some decisions might make operations more efficient, enabling repeatable processes and automation. A Gartner study noted that tracking results will help ensure decision-making models and metrics are working correctly. If anything looks unusual or isn’t providing the necessary information, organizations can simply modify rules and analytics to get the right results. Leaders should frequently review their strategy to ensure that it is conducive to continuous improvements and is yielding valuable information.

Analytics tools should also be built to immediately send alerts or notifications pertaining to potential issues. Some automatic responses can be built into the data-driven analytics system, but initially it is important to take a hands-on approach. With quick identification and warnings, organizations can deliver fast solutions to fix the problem.

Transform and drive profitable growth

A number of industries have taken on data analytics as a means to drive profitable growth. For example, more than 79 percent of firms in the banking sector have already implemented these solutions, according to PricewaterhouseCoopers.  For most industries, supply chain and logistics optimization is complex and costly; therefore, data analytics provides the biggest opportunities to reduce costs and improve efficiency. For example, Amazon, the leading online retailer, leveraged analytics to provide insights into their focus on the customer experience. The results were an increase in customer satisfaction and customer loyalty, which in turn drove revenue growth.

Continuous improvement of processes and analytics must be aligned with governance and business goals as a whole. Organizations that are completely aligned will have increased buy-in and create more collaboration for data-driven decision-making. Activities with a customer-centric focus and those with high financial impacts should be prioritized to benefit from analytics first. Putting analytical insights to actions for these items will affect more parts of the business and help transform supply chain responsiveness in order to deliver better cost savings and revenue opportunities.

As customer needs shift, organizations too must aim to continuously improve their service delivery and products. Data-driven decision-making can help leaders identify what products are popular and predict future trends based on emerging consumer transaction behaviors. With analytics solutions, organizations can easily parse through massive data sets and glean actionable information. For more information on how to use analytics for better decision-making and continuous improvement, contact Inspirage today.

Pradeep Sahoo | Key Contributor

Pradeep Sahoo leads Inspirage's BI & Analytics Practice in North America. As an experienced Manager in Solution Architecture and IoT Innovations, he has led numerous supply chain application implementations in BIA with world-class companies across various verticals. Pradeep has a passion for solving complex Supply Chain challenges and believes that the solution to these are often based on out-of-the-box thinking and simple & continuous process improvements with guaranteed success.