Data Quality Management (DQM) to consolidate your CSR policy

Over and above its direct impact on business, data quality has a clear environmental dimension, especially in a context where the volume of data collected and consumed has been increasing at a dizzying rate over the past decade. How can you activate the leverage of Data Quality Management (DQM) to consolidate your CSR policy, in addition to its impact on your marketing and sales performance?

The energy weight of Data: the figures that make people angry

The unbridled digitization of businesses, purchasing paths (B2B and B2C) and communication habits has been accompanied by an unprecedented explosion in the volume of data generated and consumed. According to a study by the International Data Corporation (IDC), the "digital world" was estimated at 33 zettabytes in 2018 and is expected to reach 175 zettabytes by 2025, a more than five-fold increase in just seven years.

These staggering figures reflect a logical and predictable trend that began with the democratization of the web in the late 1990s. But they also have a significant energy counterpart, which is growing at an exponential rate every year. Storing, processing, analyzing and transmitting this data consumes energy, mainly electricity, and contributes directly to greenhouse gas emissions. According to an estimate by Think Tank The Shift Project, the digital sector alone consumes around 4% of the world's energy, with annual growth of 9%. And according to RDA France, by 2030, data will be responsible for more than 15% of global greenhouse gas emissions.

On the other hand, the production and disposal of digital infrastructure (servers, data centers, network equipment) also generates electronic waste, or "e-waste", which also has a consequent environmental impact. In 2019, the UN reported that 53.6 million tonnes of e-waste had been generated worldwide, a figure that is again steadily rising.

Finally, it is essential to take into account "grey" energy, i.e. the energy consumed during the manufacture and end-of-life of digital equipment, which represents a significant part of Data's carbon footprint. The world of Data is dematerialized in the collective imagination, but its impact on the planet is very real.

The environmental impact of poor-quality data

Data's energy weight is not limited to its overall volume. There's also a "quality" criterion that weighs heavily in the equation.

Incorrect, obsolete, duplicated, incomplete, inconsistent and/or useless data not only represents a loss of efficiency for companies (mainly in sales and marketing), but also has a considerable environmental cost.

Firstly, the accumulation of poor-quality data requires additional storage space, which translates into high energy consumption. A considerable proportion of data stored in the cloud can be considered "Dark Data", i.e. unused or useless data that consumes energy throughout its lifecycle, from storage to disposal.

Secondly, poor-quality data, which is not identified as such, generally gives rise to a more or less extensive workflow (storage, analysis, processing, etc.). 

Worse still: as a rule, poor-quality data will take longer to process than reliable, valid data, as the company will have to challenge the data to realize its poor quality, for example after noticing the rising hard bounce rate in an email campaign, or the rate of undelivered parcels at the end of a postal campaign. This increase in processing time translates into additional energy consumption.

Finally, the consequences of poor data quality are not limited to energy consumption. Errors or misunderstandings generated by this data can lead to unnecessary actions, such as sending mail to incorrect addresses or processing duplicate orders. These actions also have an environmental impact, adding to the company's carbon footprint.

 

Data Quality Management and its impact on data volumes

Data Quality Management (DQM) is a systematic approach to improving data quality within an organization. Essentially, it involves data collection, validation, cleansing and analysis to ensure accuracy, consistency, relevance, security and accessibility.

DQM tackles both the upstream and downstream sides of the problem, filtering data before it is entered into the system, then cleaning up existing databases where necessary (curative). Summary :

 

1. 1. Data verification and correction during form submission: DQM solutions can be integrated into online forms to verify the accuracy and correctness of information entered during lead generation. For example, checking email addresses, telephone numbers, zip codes or company identification information can help avoid the collection of incorrect or unnecessary data. Not only do you reduce the volume of data stored, but also the errors that can lead to unnecessary actions and additional energy consumption.

1. 1. Batch processing of poor-quality data: DQM tools can be used to clean up existing databases, identifying and removing incorrect, duplicated or obsolete information. This reduction in data volume translates into lower energy consumption for storage and processing, and improved energy efficiency for business operations. 

1. 1. Database deduplication: the DQM can also identify and delete duplicate records in a database. This avoids wasted storage space, as well as the unnecessary actions these duplicates can entail, such as sending several e-mails or letters to the same address. 

1. B2B database enrichment: in a more indirect way, the database enrichment process, which enables information to be added or updated from reliable sources to complement existing data, enables marketing and sales efforts to be more precisely targeted, avoiding, for example, unnecessary mailings or telephone calls to irrelevant companies. This approach reduces the volume of material resources consumed (paper, electricity, fuel for deliveries), thus helping to reduce the company's carbon footprint.

Data Enso: DQM for your global performance

Data Enso has developed a wide range of intuitive, high-performance and RGPD-compliant Data Quality Management solutions. We can help you mobilize your Data capital to enhance your performance in the broadest sense of the term:

 

• • Marketing and sales performance: optimization of lead generation and customer acquisition efforts, improved targeting, optimization of campaign resources, accurate and reliable information for the sales force. 

• • Cost optimization, by eliminating unnecessary or redundant data to reduce storage and data processing costs, but also by improving the efficiency of sales and marketing operations.

• • Reputation of your domain name, by avoiding sending emails to non-existent or obsolete addresses 

• • CSR policy: by reducing your energy consumption through better data management, you can contribute to the global effort to reduce carbon emissions. By communicating this commitment, you contribute to your corporate image and employer brand.

Ready to boost the ROI of your marketing campaigns, stimulate your LeadGen and boost your CSR policy? Test our solutions for free!