Navigating the New Era of M&As in the Energy Sector – A Deep Dive into Data Management Strategies.

The energy sector was hit by a huge, unexpected demand shock during the pandemic. An overhang in supply was caused by COVID-19, which drastically changed the outlook for 2020-2021. As companies struggled to generate breakeven cash flow, a brief flurry of mergers and acquisitions (M&As) took place in the U.S. upstream sector, especially companies investing in lower-carbon assets, particularly renewable energy.

Despite a rebound of around 20% from 2020, M&A activity in the energy and natural resources industries has not yet recovered to pre-pandemic levels. It was attributed partly to companies waiting for demand to stabilize. Once stabilization had taken place, another factor came into play: companies sharpened their capital discipline, which slowed dealmaking as fewer deals met their higher hurdle rates. 

In today’s market, conditions are favorable for an upswing propelled by a resurgence in industry consolidation and portfolio management. There is still a high level of fragmentation in many sectors of the oil industry, and multiples remain low, allowing consolidation to unlock new efficiency levels. In response to the Ukraine conflict, many companies are actively reviewing their portfolios, and some have decided to exit their Russian positions, as BP recently did. Portfolio management opportunities will grow across energy and natural resources, particularly in chemicals. However, this expansion is challenged by a lack of natural synergies among assets and a high degree of complexity in meeting ESG guidelines. In addition to keeping their current businesses running, energy companies are turning to M&A to advance their journey toward a lower-carbon, sustainable future. 

Energy transition deals accounted for 20% of all energy sector deals exceeding $1 billion in 2021. Here are a few ways M&As are speeding up the energy sector’s transition to net zero:

Improving environmental, social, and corporate governance (ESG) assets and going green with existing operations: Carbon emissions from company operations are being reduced aggressively to achieve net-zero targets. An example of this is Occidental Petroleum, one of the country’s top producers in the Permian Basin. It has acquired solar generation assets to power its drilling and completion operations. In addition, Suncor is commercializing carbon-capture technology in partnership with other oil sands producers.

Building green energy hubs: Deals allow companies to go beyond upgrading their existing operations and fundamentally change their inputs, production processes, and products. Eni, National Grid, Shell, and Total are partners in BP and Equinor’s Northern Endurance Partnership, which is aimed at creating a green energy hub within an industrial cluster. By integrating renewable energy sources and production, it will also introduce new fuels and products with lower greenhouse gas emissions.

M&As reshaping business models: To fully monetize energy transition assets, some companies need to buy new capabilities for transformed business models. For example, Shell Overseas Investment, a wholly owned subsidiary of Shell, acquired Solenergi Power and Sprng Energy group of companies from Actis Solenergi Limited for $1.55 billion. This M&A gives Shell the license to sell power to industrial customers. Under Shell’s Renewables and Energy Solutions Integrated Power division, Sprng Energy retains its existing brand and operates as a wholly-owned subsidiary.

The Challenge of Data Management in Mergers & Acquisitions

An M&A may be the key to reclaiming cost efficiencies that asset managers are desperately seeking now, but it also introduces a new challenge: how to integrate two disparate companies into a single effective and efficient organization? Data management is one of the most significant challenges facing asset managers today.

Here’s what enterprises need to keep in mind while preparing for any M&As: 

Understanding the Other Companies’ Data

Most companies aren’t aware of the data they have, which makes merging with another company’s data even more challenging. If firms do not know what type of data they are integrating with, they might miss out on certain important things, like whether the company has PII subject to foreign laws and regulations like GDPR. For a successful transition to occur, organizations need to understand their own data first and then the type of data they are merging with. What is the storage infrastructure, how much of the data is dark, how much is structured, what and where is the data, what is the portion of sensitive data, is it secured, is it compliant, is it optimized, etc.? This makes the transition much easier.

Handling Data Silos
The data structure of organizations involved in an M&A will likely differ. If the M&A company does not have great data management practices, they are prone to having multiple data lakes with redundant and duplicate data. These data silos can only be consolidated into a centralized repository (cloud) through intelligent data lifecycle management that uses automation and analytics to burst open these lakes and identify what’s inside. However, no matter how well both parties break free of silos, there will still be data challenges. Each company is, in its own way, a giant silo. During M&As, enterprises must consider how these files are classified and stored to merge data effectively. Every organization likely has hundreds of terabytes of data and requires unified data management as opposed to individual point solutions with siloed data views.

Knowing Data Risks
Data is more vulnerable to breaches during a merger and acquisition. Employees who are phished or receive emails containing malicious code are among the most common victims of data breaches. Usually, employees are cautious and filter through potentially dangerous emails, but with an M&A, people let their guard down. Why does this happen? Since employees expect emails from an external organization, it creates the perfect opportunity for them to fall prey to cybercriminals. Moving files and changing access permissions can easily result in data loss or omission. One of the ways to reduce exposure and risk of rogue data usage is by isolating data that has personal or business-sensitive information into secure storage with limited access.

Data Integration
The next step is to integrate the data sets of both companies to maximize each party’s potential. In the case of the acquisition of a smaller company by a larger company, the smaller company will likely benefit from the larger company’s vast data stores. However, the organization must integrate the data first before it can reap the benefits. Organizations must understand the data they are integrating to do this successfully. After integrating the data, it is time to simplify the classification process with automation. By identifying and tagging all files between both organizations, companies can decide where everything should be stored, how to control access, and which files need to be deleted. This will allow the company to develop an integrated data ecosystem in which employees, regardless of their roles or technical expertise, can access data easily and gain maximum insights from it securely and governed.

Achieving a successful M&A with Increased Analytics
The integration of data allows organizations to analyze it. Firms can examine a broader range of markets by incorporating data from their M&A company. Data brought about by mergers can now fuel the BI tools of an organization, allowing them to generate new insights. Because of their ability to handle emerging data challenges, mergers and acquisitions no longer threaten a company’s data. A company’s knowledge of its data allows it to make informed decisions about what to keep and delete. Managing data properly can lead to rapid revenue growth for newly acquired businesses.

How can Data Dynamics empower the energy sector with intelligent data lifecycle management during M&As?

Transforming data management in the energy industry has many benefits, including improved operational efficiency and performance. For digitalization and automation, the oil and gas industry is heavily reliant on data. Data Dynamics’ Unified Unstructured Data Management Platform plays a crucial role in improving conventional, unconventional, and midstream operations in the oil & gas industry. The platform encompasses four modules – Data Analytics, Mobility, Security, and Compliance. Each module has been customized to meet the industry’s needs and is helping energy enterprises modernize their data management ecosystems by efficiently managing, processing, and securing immense datasets from upstream, midstream, and downstream operations. Click here to read more.

Here’s an example of how Data Dynamics’ unified data management platform helped one of their customers achieve 96% reduction in customer outage and 100% ROI during data transfer. The company was a Fortune 500 Healthcare Data Science Technology Company that was undergoing an M&A and required a technology refresh, along with data migration and consolidation.

With Data Dynamics, organizations can eliminate the use of individual point solutions with siloed data views. Instead, they can utilize a single software platform to structure their unstructured data, unlock data-driven insights, secure data, ensure compliance and governance and drive cloud data management. Ultimately, the company’s vision is to help organizations achieve data democratization so that users, no matter their technical background, can instantly access, understand, and derive maximum insights from unstructured data sprawls. 

Furthermore, Data Dynamics has recently partnered with Microsoft to help organizations migrate unstructured data into Azure for FREE. Click here to know all about it or reach us at I (713)-491-4298 I +44-(20)-45520800 I

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