Banner Image

Business and Technology Insights

Leveraging Analytics to Build Tomorrow's Supply Chains

 
February 13, 2017

In todays connected world, understanding what your customer wants should be getting easier. Now, you can collect more data about their choices and actions, online and in-stores than ever before. You can also monitor every machine, process, and function in your supply chain and factories; and capture all the data they generate. But, can you really say that you understand your customer?

Organizations have invested heavily in building cloud and Artificial Intelligence (AI) capabilities to harness the power of the new data sources, but theyre unable to tap into the multiple sets of data in fragmented repositories that are poorly connected, and owned and managed by a variety of different stakeholders. What if we could? It would transform how you manage your supply chains. Unfortunately, many simply dont know where to start.

Start your analytics maturity journey here
Companies now realize that collecting data is not the hard part. Its the sharing and analysis of data, collected by different business units and different businesses across the supply chain that is the challenge.

You cant overcome this challenge alone because your business doesnt operate in isolation. It is part of an ecosystem that comprises customers, competitors, suppliers, and partners.

Fortunately, sorting out how data is shared is part of the problem that is becoming easier to solve. Global standards organizations are bringing together all of the constituencies and are establishing rules, models, and standards around ownership and privacy, which will naturally facilitate access to data.

Analyzing that data, on the other hand, requires a level of analytics maturity that most organizations lack. In practice, this is the real challenge that businesses within an industry need to work on collectively if they are to find a solution that is sustainable and future-proof. There are three distinct stages of analytics maturity that your industry must transcend if it seeks to share and use customer data to improve its supply chains.

Descriptive Analytics: This is the first stage of analytics maturity. You must focus on harmonizing data identifiers (labels, tags, and codification) across the various departments of your business and with other organizations in your industry.

Predictive Analytics: At this stage, having reviewed and decided which data sets, structured and unstructured, are important for analysis, you must find a way to capture them. These can originate from within your organization or from outside. Insights generated by analyzing this data can help everyone across your supply chain make better decisions.

Prescriptive Analytics: Reaching this stage is your aspiration. It is here that your analytical capabilities will be mature enough to collect historical data, analyze trends, and provide intelligent solutions to problems, without requiring management intervention.

To learn more about the three distinct stages of analytics read our paper titled Building and Turbocharging Tomorrows Digitally Integrated Supply Chains.

Today, customers have all the power and they expect you to give them what they need, when they need it, and at the lowest cost. To meet their changing demands, you have to collaborate with other participants in your market ecosystem to work on improving how you share and analyze data, and use the insights to reimagine your supply chains.

Since you know there is no way to avoid this digital transformation, the time to act is now. The longer you take to get started on this journey, the greater the risk of losing market share to your competitors.

Tags

Matthew Lekstutis is the Supply Chain Consulting Lead for Tata Consultancy Services. He has over 20 years of experience as an industry executive and advisor including COO level P&L management responsibility. Matt helps clients to capture business performance improvement opportunities and drive growth by enabling new business models and technologies across the supply chain.