May 19, 2020

Three innovative ways Shell is using big data

Amazon
Forbes
Big Data
Analytics
Tomás H. Lucero
3 min
Three innovative ways Shell is using big data

Amid rising costs of extraction and the turbulent state of international politics, the oil and gas industries turn to big data to ameliorate the present-day difficulties of conducting their business.

Big data is the theory and practice of collecting masses of information and using sophisticated computer analytics to make sense of it all. In business, it is used to turn data into purchases. In the case of the oil and gas industries, specifically Royal Dutch Shell, big data has many applications from beginning to end of their product cycle. Bernard Marr enumerates some of these in Forbes.

Since the advent of big data, Shell has been developing the idea of the “data-driven oil field” in order to bring down the costs of oil extraction—the industry’s biggest expense.

Related Story: In Its Acquisition of Careerify, LinkedIn Chases Big Data

1. Surveying and forecasting: Surveying potential oil sites involves measuring seismic movement. When seismic waves travel through the underground distorted, this means it’s traveling through oil or natural gas. In the past, thousands of readings were taken but technology now allows for millions of readings—sharply increasing the amount of data that is recoverable.

According to Marr, “Shell uses fiber optic cables, created in a special partnership with Hewlett-Packard, for these sensors, and data is transferred to its private servers, maintained by Amazon Web Services.”

The increased amount of data creates a sharper, more accurate vision of what lies underneath. This information can be used to calculate more trustworthy figures about the particular oil field’s production capability. As a result, resources can be properly allocated.

2. Monitoring equipment: This application is borrowed from the mining industry, which outfits its mining equipment with sensors collecting data about its performance and comparing it to aggregated data. This “big” data is then used to determine whether parts need to be replaced and when. Shell does the same thing with its exploration equipment. This tactic minimizes the time equipment spends offline due to breakdowns. Consequentially, overheads are reduced.

Related Story: Big data apps can mean big business

3. Increase the efficiency of the transport, refinement and distribution (retail) of oil and gas: Shell is organized “vertically,” meaning that they are involved in each aspect of their energy production from extraction to sale to the consumer for car fuel or home heating. Refineries have limitations and fuel must be produced as close as possible to where it’s sold in order to minimize transportation costs

To this end, “Complex algorithms take into account the cost of producing the fuel as well as diverse data such as economic indicators and weather patterns to determine demand, allocate resources and set prices at the pumps,” writes Marr.

These three dimensions related to oil production: surveying and forecasting, maintaining equipment and transporting it to the consumer form the “big picture” of the business. The more the big picture, of any company, is synchronized the more robust its competitiveness.

Big data analytics allow for the close examination and monitoring of the separate aspects of the big picture. Models can be built and analyzed to determine how minor modifications in one area can make a big impact in another. The more data an organization has about its business components the more realistic a portrait of reality it can create, and thus, the better-backed decisions it can make.

Bernard Marr is a best-selling business author, keynote speaker and leading business performance, analytics and data expert. His latest books are ‘Big Data‘ and ‘KPIs for Dummies‘.

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Jun 12, 2021

How changing your company's software code can prevent bias

Deltek
diversity
softwarecode
inclusivity
Lisa Roberts, Senior Director ...
3 min
Removing biased terminology from software can help organisations create a more inclusive culture, argues Lisa Roberts, Senior Director of HR at Deltek

Two-third of tech professionals believe organizations aren’t doing enough to address racial inequality. After all, many companies will just hire a DEI consultant, have a few training sessions and call it a day. 

Wanting to take a unique yet impactful approach to DEI, Deltek, the leading global provider of software and solutions for project-based businesses, took a look at  and removed all exclusive terminology in their software code. By removing terms such as ‘master’ and ‘blacklist’ from company coding, Deltek is working to ensure that diversity and inclusion are woven into every aspect of their organization. 

Business Chief North America talks to Lisa Roberts, Senior Director of HR and Leader of Diversity & Inclusion at Deltek to find out more.

Why should businesses today care about removing company bias within their software code?  

We know that words can have a profound impact on people and leave a lasting impression. Many of the words that have been used in a technology environment were created many years ago, and today those words can be harmful to our customers and employees. Businesses should use words that will leave a positive impact and help create a more inclusive culture in their organization

What impact can exclusive terms have on employees? 

Exclusive terms can have a significant impact on employees. It starts with the words we use in our job postings to describe the responsibilities in the position and of course, we also see this in our software code and other areas of the business. Exclusive terminology can be hurtful, and even make employees feel unwelcome. That can impact a person’s desire to join the team, stay at a company, or ultimately decide to leave. All of these critical actions impact the bottom line to the organization.    

Please explain how Deltek has removed bias terminology from its software code

Deltek’s engineering team has removed biased terminology from our products, as well as from our documentation. The terms we focused on first that were easy to identify include blacklist, whitelist, and master/slave relationships in data architecture. We have also made some progress in removing gendered language, such as changing he and she to they in some documentation, as well as heteronormative language. We see this most commonly in pick lists that ask to identify someone as your husband or wife. The work is not done, but we are proud of how far we’ve come with this exercise!

What steps is Deltek taking to ensure biased terminology doesn’t end up in its code in the future?

What we are doing at Deltek, and what other organizations can do, is to put accountability on employees to recognize when this is happening – if you see something, say something! We also listen to feedback our customers give us and have heard their feedback on this topic. Those are both very reactive things of course, but we are also proactive. We have created guidance that identifies words that are more inclusive and also just good practice for communicating in a way that includes and respects others.

What advice would you give to other HR leaders who are looking to enhance DEI efforts within company technology? 

My simple advice is to start with what makes sense to your organization and culture. Doing nothing is worse than doing something. And one of the best places to start is by acknowledging this is not just an HR initiative. Every employee owns the success of D&I efforts, and employees want to help the organization be better. For example, removing bias terminology was an action initiated by our Engineering and Product Strategy teams at Deltek, not HR. You can solicit the voices of employees by asking for feedback in engagement surveys, focus groups, and town halls. We hear great recommendations from employees and take those opportunities to improve. 

 

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