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The Intersection of Digital Transformation and Data Privacy

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The Intersection of Digital Transformation and Data Privacy


Imagine for a moment your social security and driver’s license numbers are stolen – and not by your own devices.

You didn’t leave your purse in an unlocked car nor drop your wallet at the store. No, this thievery happened under someone else’s watch. Add to that, the breach happened within a company you once worked for or currently patronize. You are not alone in feeling violated; more than five million people are affected, although that doesn’t provide any sense of comfort.

Like many unexpected crises, your other worries now seem small. With your personal information at risk, you wonder: How do I keep my information safe as digital transformation unfolds and cloud computing becomes the norm?

The scenario outlined above is a true story. The personal data of customers and former employees of Infinity Insurance were breached in December of 2020. The story underscores the growing importance of data privacy impact. It’s a different kind of security issue. There is no easy fix when personal data is stolen. You can’t call someone and get a new driver’s license or social security number like you can with a credit card. It’s much more complicated.

Stories of data misuse take many different forms. What if your sensitive information got out because a company you worked for or purchased from sold its data? Or because an employee at that organization copied your info over to another location to use a different analysis application? How much worse would you feel then? There is a growing concern around how much of our private personal data is being sold or used under our noses, who has access to what information, and how information from multiple sources can be used in conjunction to identify the original individual.

The impact is, however, much bigger than we think. In its coverage on the topic, CRN magazine cited “more than 98.2 million individuals were impacted by the 10 biggest data breaches in the first half of 2021, with three of the 10 largest breaches occurring at technology companies.” This insight, collected by the ITRC and the U.S. Department of Health and Human Services, demonstrates the precarious intersection of digital transformation and data privacy. On the flip side, the penalty for breach of data privacy is hefty. Amazon’s fine of $886 million from the Luxembourg’s National Commission for Data Privacy Is unprecedented. I see numbers like these rising in the future for companies unprepared or unconcerned about data privacy.

The Data Privacy Imperative

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Source: Infopulse 

Freedom is a topic I often talk about. What I mean here is cultivating freedom during a time when we are experiencing a data explosion and evolution of technology, one where opportunities from data and the risks are both enormous.

We see this delicate balance between freedom and protecting data privacy all around us. For example, in the field of healthcare, how do you anonymize sensitive information about patients while enabling data to be used to optimize patient care? Or in the banking industry, how do you protect personal information while creating a seamless customer experience?

Worrying about security or privacy of information erodes our personal freedom by creating anxiety and distrust. So we must ask ourselves: How do we turn knowledge into wisdom? Data into insights? Our values into trust?

There are four areas to consider:

“Build” It: Establish data governance goals and objectives by making it part of the business strategy. Define and implement a data stewardship program to align with business outcomes, streamline and standardize data to ensure quality and improve efficiency, establish master data management, and track on-going improvement. Understand who is consuming what data, who will have the access to what data and why the data is important. 

“Share” It: Upskill and educate your workforce to meet the demands of data privacy across the organization. Make everyone a “data expert” so that employees understand their responsibilities and the role they play to ensure privacy standards are upheld. This includes learning lessons when failures occur. Infinity Insurance vowed to look at the results of its security investigation and strengthen its network security and cybersecurity program.

“Own” It: It’s not about data senders, it’s about impact. What will you drive and how do you maximize outcomes? Accountability is critical. With all these different data available, the key is to gain actionable insights for more effective business decisions – and hold leaders accountable. They must “own” it. Imagine what your customers, peers, employees and supply chain partners would think if they are 100% confident you would be willing to defend data privacy. It takes the idea of explainability to the next level and forces people to consider how they would justify the usage of personal information.

“Set” It: Make policy a priority by setting down a precedent for monitoring data privacy. More companies are prioritizing data privacy at the board level with dedicated committees created to help solve this problem.

In Gartner’s “Predicts 2021: Data and Analytics Strategies to Govern, Scale and Transform Digital Business,” two compelling predictions further support the perfect storm created when digital transformation, data privacy and cloud collide

  • By 2024, 60% of the data used for the development of AI and analytics solutions will be synthetically generated.
  • By 2025, 80% of data and analytics governance initiatives focused on business outcomes, rather than data standards, will be considered essential business capabilities.

A look ahead tells us that there will be more threats, more AI-driven data, more people impacted (especially with the growing number of devices worldwide) and more vulnerable entryways as we enter a multi-cloud world.

IBM Driving Solutions for Data Privacy

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Source: IBM

There are several tech innovators who are developing solutions at the intersection of digital transformation (cloud) and data. IBM is one of them.

IBM Cloud Pak® for Data allows organizations to deploy a unified privacy framework designed to help companies fully understand and manage how sensitive data is used throughout their organizations. Key attributes include data governance, data privacy, risk management and data security within a collaborative platform, providing users a universal view of PII across their businesses. It answers the who-what-where-when questions behind data access. 

One critical point of difference for IBM Cloud Pak for Data is that data remains stationary, meaning data can be used without moving it from its source for AI and analytics initiatives. Advanced capabilities such as automated masking of highly sensitive data and de-identification of data support data privacy. Automating data protection – especially for high-risk data – lessens the possibility of human error or misuse.

Conclusion

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Source: Crownpeak

Hopefully, walking in the shoes of those impacted by the Infinity Insurance security breach showed you how data privacy becomes top of mind for people when a crisis occurs. Future-forward leaders, however, will prepare. They will lead with accountability, realizing that protecting people as well as staying ahead of growing regulations and public perception on data usage leads to stronger data privacy with accountability. 

James M. Strock, author of Serve to Lead, writes: “In the wired world of the 21st century, advancing shared values creates value.” It is not often values and technology are written in the same sentence – but they should be. I can’t think of a better viewpoint than values to guide our companies while making IT decisions, setting down IT policies and supporting the business strategy. 

Disclaimer: From time to time, IBM invites industry thought leaders to share their opinions and insights on current technology trends. The opinions in this article are my own, and do not necessarily reflect the views of IBM & BBN Times.



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Daasity builds ELT+ for Commerce on the Snowflake Data Cloud

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Cloud Computing News

Modular data platform Daasity has launched ELT+ for Commerce, Powered by Snowflake.

It is thought ELT+ for Commerce will benefit customers by enabling consumer brands selling via eCommerce, Amazon, retail, and/or wholesale to implement a full or partial data and analytics stack. 

Dan LeBlanc, Daasity co-founder and CEO, said: “Brands using Daasity and Snowflake can rapidly implement a customisable data stack that benefits from Snowflake’s dynamic workload scaling and Secure Data Sharing features.

“Additionally, customers can leverage Daasity features such as the Test Warehouse, which enables merchants to create a duplicate warehouse in one click and test code in a non-production environment. Our goal is to make brands, particularly those at the enterprise level, truly data-driven organisations.”

Building its solution on Snowflake has allowed Daasity to leverage Snowflake’s single, integrated platform to help joint customers extract, load, transform, analyse, and operationalise their data. With Daasity, brands only need one platform that includes Snowflake to manage their entire data environment.

Scott Schilling, senior director of global partner development at Snowflake, said: “Daasity’s ELT+ for Commerce, Powered by Snowflake, will offer our joint customers a way to build a single source of truth around their data, which is transformative for businesses pursuing innovation.

“As Snowflake continues to make strides in mobilising the world’s data, partners like Daasity give our customers flexibility around how they build data solutions and leverage data across the organisation.” 

Daasity enables omnichannel consumer brands to be data-driven. Built by analysts and engineers, the Daasity platform supports the varied data architecture, analytics, and reporting needs of consumer brands selling via eCommerce, Amazon, retail, and wholesale. Using Daasity, teams across the organisation get a centralised and normalised view of all their data, regardless of the tools in their tech stack and how their future data needs may change. 

ELT stands for Extract, Load, Transform, meaning customers can extract data from various sources, load the data into Snowflake, and transform the data into actions that marketers can pursue. For more information about Daasity, our 60+ integrations, and how the platform drives more profitable growth for 1600+ brands, visit us at Daasity.com.

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4 Activities that Automakers Can Digitize Now

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4 Activities that Automakers Can Digitize Now

Digital automaking is supported by technology-driven trends, consumer needs and new developments in artificial intelligence.

Manufacturing, procurement of raw materials, marketing and sales are factors involved in this change.

Digital automaking is a process that combines simulation, three-dimensional visualizations, analytics and several tool partnerships to make automotive manufacturing easier. Since the automotive industry has been undergoing a digital transformation primarily driven by intelligent mobility, it has encouraged the market to adopt new technology and software for modern vehicles. There has also been a growing need to increase industrial processes’ sustainability, environmental friendliness and adaptability. All of this has made automotive digitalization extremely important.

Automotive digitization helps to keep precise control over business operations, which is made possible using modern technologies like ML (machine learning) and AI (artificial intelligence) to improve short- and long-term performance. 

Automotive digitization has also increased the capacity to monitor each component of the supply chain while lowering costs and risks. Digital automaking can offer automotive solutions in terms of better design, time efficiency, and many other industry solutions.

4 Activities that Can Be Digitized by Automakers Now

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1. Manufacturing

Customers desire tailored goods, but they don’t want to pay more than they would for items that are mass-produced. As a result, manufacturing must be more adaptable than ever, leading to mass customization. Thus, the design, fabrication, use and maintenance of products are changing as a result of the digitalization of manufacturing. It is also changing the operations, procedures and energy footprint of supply chains and more. Digital manufacturing enables firms to provide additional options that are tailored to individual customers. Businesses can better understand supply-chain challenges, including inventory levels, delivery status and demand cycles, thanks to digital manufacturing. 

The factories of the future will move from automation to autonomy, strengthening real-time communication between equipment, physical systems, and people. These factories are referred to as smart factories. The most notable advantages of a smart factory are its shop floor connectivity, advanced robotics, flexible automation, augmented and virtual reality systems, and efficient energy management. The general manufacturing sector’s global standards are established by the automotive industry.

Over the past two decades, the automotive sector has expanded tremendously. However, the main elements that will affect whether digitalization is successfully implemented are the significance of realizing a return on investment (RoI) and the willingness of employees at both the top-most and lowest levels of an organization.

2. Supply Chain

By removing the functional barriers that divide different areas, the digitization of the supply chain is a cross-functional process that spans the entire lifecycle of a vehicle or product and involves all company divisions. It allows for an ecosystem that connects all stakeholders, from raw material and component suppliers to logistics companies, dealers and customers.

Utilizing digital technology throughout the entire supply chain allows for real-time monitoring of all supply-chain stages, be it either procurement of raw materials or finished products ready to be delivered or purchased. The evaluation and management of each event’s impacts on the supply chain can help the automation of procedures and the avoidance of potential interruption.

3. Design

Design plays a significant role in the automotive industry. By digitizing design activity, design professionals can test multiple hypotheses before proceeding with the design phase. Digitalization in the designing of products has been enabled by a digital model known as Digital Twins, which represents tangible assets in 3D. Digital twins mirror the complete car or one of its components’ appearance and behavior. With great assistance from sophisticated software, businesses can collect information about configuration, sensors, inspection data, and other details to improve the product’s design.

Automobile manufacturers are among the many industrial firms that recognize digital twins’ possibilities and the potential it has to bring in the best in the business of automobiles. The design and production processes are simplified by 3D representations, improving vehicle performance and cutting costs for the manufacturers. The twin technology is quickly rising to the top of the list of software solutions used in contemporary auto manufacturing, with applications ranging from car design to predictive maintenance to boosting sales using digitally generated models.

4. Marketing

Any marketing strategy aims to tailor the right message to the right set of audiences at the right time. A marketing campaign that appeals to a 45-year-old countryside man might not affect a 23-year-old lady residing in an urban area. Therefore, the impact of marketing combined with the effectiveness of Artificial Intelligence (AI) can be the biggest boon to any business. The automotive industry can enormously benefit in how they market their brand/product by adding the power of artificial intelligence to their current data. It can lead to a strong possibility of purchasing your products early in the sales process, possibly before customers even begin looking for their new car, which is indicated by specific online activities. 

As a result of recent advancements in third-party cookies and mobile advertising identifiers, AI can now assist brands in finding new prospects much more quickly by utilizing data to identify customers with similar characteristics and behaviors. This strategy can potentially increase your prospective customer base and give you an advantage over your competitors. You can identify high-priority targets by identifying the demographic categories that overlap. These solutions don’t require cookies and are more likely to comply with escalating privacy requirements because they rely on behaviors rather than personal data.

The automotive sector has modified its strategy and is now embracing digitization. Digital transformation in the automotive industry still has a lot of gaps to be addressed, but the trend toward digitization is a sign that the stakeholders in the automotive sector will be properly supplied with digital solutions in the coming days. With intelligent technology, and operations across the entire company and all departments, including manufacturing, supply chain, marketing, and sales, digital automaking will help the automotive industry to flourish in this digital era. An increasingly digital supply chain will also dismantle established barriers and greatly enhance communication. Undoubtedly, businesses must adopt a more significant digital transformation to be ready in this competitive automotive industry.

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The 10 Worst Cybersecurity Strategies You Need To Know

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The 10 Worst Cybersecurity Strategies You Need To Know

Employees should be trained on basic cybersecurity practices and the dangers of phishing scams.

Granting too many privileges to user accounts can lead to security breaches. Failing to update software on time can leave vulnerabilities open to attacks. 

Organizations should have a disaster recovery plan in place to ensure quick recovery in the event of a cyberattack.

Counting down to the absolutely worst cybersecurity strategies. 

Sadly, these are all prevalent in the industry. Many organizations have failed spectacularly simply because they chose to follow a long-term path that leads to disaster. You know who you are…

Let’s count them down.  

10. Cyber-Insurance

No need for security, just get insurance. Transferring risk is better than mitigating it!

Famous Last Words: Sure, it should be covered

9. Audit Confidence

Conducting a comprehensive security audit. …and ignoring the results

Famous Last Words: We will close those gaps later…

8. Best Tools, Left Unmanaged

Deploying several good tools, set to autopilot. No need to manage or maintain anything 

Famous Last Words: Security is not that difficult…

7. Regulatory Compliance

Meeting the minimum requirements (defined 2 years ago)

Famous Last Words: Relax, we are compliant!

6. One Good Tool

We just need one good tool (ex. AV) and we are set. 

Famous Last Words: That should do it.

5. IT Dependence  

Cybersecurity is a tech problem, it’s IT’s responsibility. 

Famous Last Words: The IT dept has it covered.

4. Security by Marketing  

Believing the snake-oil (deceptive marketing) salesperson that will ‘solve‘ your security problems

Famous Last Words: We are totally protected now! (or similar derivative from the sales brochure)

3. Default Security Settings  

Products and services come with security built in! 

Famous Last Words: It’s new, shiny, and looks secure. Don’t worry, we should be fine!

2. Security by Obscurity

Nobody knows or cares about us. We are too small to be targeted.

Famous Last Words: We haven’t been attacked yet…

1. Hope, as a Strategy

I hope we don’t get attacked. Let’s move on with more important things.

Famous Last Words: <meek inner voice>> Just don’t think about security because it is too scary, expensive, and complex!

 

This is the menu that evokes anger, frustration, and pity among cybersecurity professionals around the globe. Eventually it always ends in despair, blame, and a side of tears.

A solid long-term strategic plan is a necessity for an efficient and capable cybersecurity capability. Cybersecurity fails without a proper strategy. 

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