---
title: Digitizing the Value Chain
description: Digitizing the value chain combines data and analytics to improve performance in every step of the chain.
image: http://info.ekaplus.com/hubfs/Value-Chain-Charts-v4_Oil-Value-Chain.jpg
---

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[EKA](http://ekaplus.com/) > Digitizing the Value Chain

 May 22, 2017

# Digitizing the Value Chain

[![Value-Chain-Charts-v4_Oil-Value-Chain.jpg](http://info.ekaplus.com/hubfs/Value-Chain-Charts-v4_Oil-Value-Chain.jpg)](https://blog.eka1.com/blog/digitizing-the-value-chain)

![Digitizing-the-oil-value-chain-improves-efficiency](http://info.ekaplus.com/hubfs/Value-Chain-Charts-v4_Oil-Value-Chain.jpg "Digitizing-the-oil-value-chain-improves-efficiency")

New digitally-enabled technologies – 3-D printers used in production, smart products connected through the Internet of Things (IoT), and data tools and analytics across the value chain – are changing how companies design, produce, and service products and equipment. Digital technology connects people and machines in a new “digital thread” that spans across the value chain, enabling companies to draw insights from vast new sources of data. Experts predict that [over 20 billion smart machines will be connected by 2020](http://www.cnbc.com/2016/02/01/an-internet-of-things-that-will-number-ten-billions.html).

## Creating the digital thread

In the past year, more than 200 organizations from industry, government, and academia joined in supporting the Digital Manufacturing and Design Innovation Institute (DMDII) to advance digital integration in the manufacturing economy. In a recent McKinsey poll of participants, [80 percent consider digital manufacturing and design to be a critical driver of competitiveness](http://www.mckinsey.com/business-functions/operations/our-insights/digitizing-the-value-chain), while only 13 percent rate their organizations’ digital capability as “high.” Many respondents said their companies lack the standards, data-sharing, and cybersecurity necessary to implement digital integration.

Participants said that current systems – including computer-aided design (CAD), enterprise resource planning (ERP), and manufacturing execution systems (MES) – are difficult to learn and slow to adapt, and unable to communicate with other systems. You cannot successfully digitize the value chain with systems that cannot communicate with other systems. The continuous flow of data across the value chain is essential. Solutions also must be easy to use and adaptable, or people will resist using them.

While some software vendors are trying to adapt their solutions, users are looking for more than just updated versions of existing software. They want a step-change improvement in usability and integration, app-based platforms modeled after those available in consumer markets. Eka Analytics delivers.

## **Connecting the digital thread with Eka Analytics**

[Eka Analytics](https://www.ekaplus.com/analytics/commodity-analytics-cloud-overview.aspx) extracts data from disparate sources throughout the value chain – internal systems such as ETRM, CTRM, ERP, CRM, spreadsheets, smart machinery, and IoT sensors, plus external sources such as market curves and weather data. The program analyzes the data using advanced algorithms, artificial intelligence, and machine learning to deliver unprecedented business insights to commodity market participants.

Eka’s easy to use apps span multiple categories including position consolidation, risk, supply chain, P&L evaluation and attribution, procurement, margin analysis, and plan performance. It’s easy to use. It’s fast. And it provides a clear and comprehensive analysis of performance, answering the questions you need answered and enabling better, faster, fact-based decisions. This level of data analysis is a game changer – improving efficiency, decreasing costs, and saving time.

[![Commodity Analytics Cloud provides a competitive advantage](https://no-cache.hubspot.com/cta/default/455947/ee29f675-8524-417a-8d52-326477a7b435.png)](https://cta-redirect.hubspot.com/cta/redirect/455947/ee29f675-8524-417a-8d52-326477a7b435)

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