Business Agility Demands In-Line Analytics

For businesses large and small, the rate of change in markets and global supply chains is constantly increasing. The traditional “plan-execute-analyze-respond” cycle is getting so compressed it requires these steps to be virtually simultaneous. In addition, disruptions are hitting supply chain operations on a seemingly daily basis, requiring immediate attention to minimize impact.

As a result of these speed and time pressures, a premium has been placed on business agility. Business leaders want not only the ability to monitor their supply chain operations 24/7 and immediately respond to changes and disruptions, but also the ability to see what is coming at them just over the horizon so they can be prepared. Achieving this level of business agility requires integrated business processes and technology with embedded, real-time analytics.

Analytics Done Right

Unfortunately, many supply chain solutions either don’t have analytics as part of their core functionality, or analytics is an external module which typically runs in batch mode after the fact. That’s fine for analyzing what went wrong in the past, but doesn’t give you the agility to correct small problems before they impact service and profitability.

Agile supply chain platforms must have real-time analytics embedded within the supply chain process flows in order to keep pace with the fast-changing marketplace. These in-line analytics continuously monitor and interpret the data flowing through the supply chain to immediately detect changes or disruptions and provide managers the global, cross-functional information they need to make informed decisions. The combination of integrated supply chain suites with cross-functional process flows and in-line analytics provides new levels of insight and business agility not possible before.

Advanced supply chain platforms with in-line analytics can also use historical trends, modeling and risk analysis to simulate likely outcomes of a wide range of scenarios to identify the best paths to improvement. These predictive analytics foster innovation and new levels of strategic decision-making.

Leveraging Big Data

Any discussion of analytics today would be incomplete without mentioning “Big Data.” The availability of massive amounts of data from online, mobile and social networks presents intriguing new opportunities to better understand customers, get a jump on marketplace trends and tailor responses to more granular market segments.

But there are challenges to any attempt to leverage big data. The sheer volume of data can overwhelm many systems. Traditional analytics systems are not typically designed to accept and manipulate unstructured data. And interpreting unstructured, social data to draw business insights requires a new set of capabilities.

Don’t feel bad if you’re not there yet. This is a new frontier for everyone. The key is to look for systems well positioned to leverage big data. Integrated systems with in-line analytics, especially those with in-memory processing, are best positioned to scale to the needed volumes and interpret the data flowing in from disparate sources. The ability of these integrated systems to analyze cross-functional data positions them well to interpret and synthesize the data coming from multiple external sources.

Business Agility Demands In-Line Analytics

The speed of the marketplace and the speed of change are increasing. This requires businesses to be more agile in responding to change. To be agile, businesses need visibility to what is happening in real-time to respond quickly, and the ability to predict what will happen next to be prepared and beat the competition in meeting customer expectations. The lynchpin in this process is analytics embedded within the supply chain platform managing your business. In-line analytics provide the real-time analysis on which to make well-informed decisions quickly. That creates business agility.

What do you think? Is your supply chain ready?

No Comments

Be the first to start a conversation

Leave a Comment