The Intelligent Enterprise: Where Data Doesn’t Collect Dust

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The Intelligent Enterprise: Where Data Doesn’t Collect Dust

By Dina Dayal, SAP - 11/01/2018

Guest contributor Dina Dayal is Vice President and Industry Advisor for Consumer Products at SAP

The concept of the "Intelligent Enterprise" is a game-changer for the consumer goods industry. Increasingly, businesses can make smarter decisions and act more intelligently in real time compared to their human counterparts. And this capability only grows stronger as the data we capture and use become more relevant. 

Most executives love to think that their companies run on clean data and "anytime, anywhere" access to analytics. But I often wonder whether their perception actually reflects their reality. 

A new era of intelligence calls for a different perspective on data assets. Are you collecting and using social media data, weather data, geospatial data and machine data? Better yet, are you leveraging the data sitting in your enterprise, ready to help you make critical business decisions? 

If your answer to that line of questioning is “probably not” or “no,” you’re not alone. But that doesn’t mean you can stand still and stay complacent. On the contrary, you should refocus data management and analytics to provide the workforce with: 

  • Stored data that’s also accessible.
  • Data definitions and labels that are uniform across the business.
  • The ability to manipulate and exchange data among multiple applications.
  • Innovative scenarios that optimize the value of your data assets.

By addressing these critical needs, analytics paint a detailed picture that allows decision-makers to understand what’s happening in real time. They'll also be able to look at the emerging horizon without the influence of unconscious and conscious bias.

Let’s consider common business scenarios in which getting a better handle on data can be incredibly advantageous.

1. Responding to social media sentiment
Take, for example, a food and beverage company that's receiving negative feedback about a product. If the business is not collecting or sensing its social media feeds, it will never know the underlying problem. Worse yet, it won't be able to fix the issue before the news is reported by The Wall Street Journal

By leveraging all social media sentiment, consumer products companies can take immediate, targeted, and deliberate action to create a positive experience for all consumers.

2. Protecting the supply chain
For two years in a row, the southern and eastern coastlines of the U.S. have been hit by a series of powerful hurricanes. For food and beverage companies, such natural events can keep executives awake at night watching The Weather Channel for hours.  

How can the company ship a product to locations in advance of the storm? Will distributors, retailers, and customers be well stocked? Will retail outlets experience out-of-stocks within hours? If so, is there a distribution center nearby that can replenish them in near-real time?

Instead of letting these questions swirl around in the back of executives’ minds, analytics that combine weather and geospatial data can be highly insightful. This information enables decision-makers to experiment with scenarios to determine how to adjust inbound and outbound flows of goods to the right place at the right time — and act accordingly long before the hurricane makes landfall. 

3. Realizing the full potential of machine data
For years, manufacturing plants have been collecting operational technology data. They know when the machine is active or inactive, whether the temperature and vibration level is too high or low, and whether it is scheduled for maintenance. 

But what if the business took that data and converged it with its ERP data? The picture of plant-floor operational needs can be vastly different than initially believed. For example, machine assets can be placed offline for maintenance when an imminent malfunction is predicted, as opposed to scheduling a date when there is no danger of a breakdown on the horizon. 

With this approach, companies can save millions in asset maintenance costs. Now, the operations manager can predict when an asset will fail, order the right part, and schedule the maintenance technician. Most importantly, production uptime and productivity are significantly improved. 

The stakes are too high to keep data “dusty.” As long as data is not hoarded in a one-dimensional, siloed manner, consumer products companies stand to gain capabilities that are considerably competitive. So I urge you to look within your organization to dust off the data that’s being collected and start using it to make better business decisions and uncover new insights you never could have imagined before.  

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