Biggest Challenges for CTOs in 2023

Digital transformation has reached a pace that’s increasingly made the Chief Technology Officer (CTO) position more significant. I mean, if you consider the prevalence of technology in business today, it makes sense that those responsible for overseeing all technology-related matters within the company would carry a burden. 

Nonetheless, the contribution of CTOs and technology managers is indispensable in enhancing a company's competitiveness through innovation and optimizing workflows. The question is; What daily obstacles do these new technology experts currently confront, and what hurdles lie ahead in the months to come?

The effects of the pandemic have acted as a catalyst for digital transformation. Companies that once viewed the adoption of new technologies as a novelty found themselves abruptly transitioning their operations into the digital realm. Now, as the journey of digital transformation advances, CTOs encounter a set of new challenges in 2023. Here are the top 5 obstacles they are currently navigating:

Big Data

As businesses continue to digitize their operations, the volume of data they generate daily grows exponentially. Handling this data influx is a significant challenge, demanding a meticulously crafted strategy and a specialized infrastructure. The primary goal of initiatives in this realm is to ensure the efficient and secure internal movement and curation of data. 

Managing the Big Data landscape efficiently poses big advantages for the company, whether that’s through reduced operational expenses or more streamlined processes. Naturally, this is another facet that falls under the purview of the Chief Technology Officer, working in collaboration with the IT department.

Ongoing Advancement of IT Infrastructure

Closely intertwined with most of the challenges we’re looking at is the perpetual evolution of the IT infrastructure itself, a huge responsibility of CTOs. To ensure the organization's sustained growth, you have to establish a comprehensive strategy for expanding the infrastructure well in advance, thus laying the groundwork for what’s to come, both in terms of cost and operational efficiency. Equally important is preparing the team for what’s to come, fostering an awareness that continual adjustments and enhancements are on the horizon, all implemented for the collective benefit of the organization (It’s a mistake more common than you’d think).

The Digital Transformation Blueprint

For CTOs, particularly when they're new to an organization, a key challenge is formulating a digital transformation strategy. In the daily tasks of technology managers, this process of devising and subsequently executing the strategy takes center stage. What we looked at with the pandemic shifting workflows online, is something today that’s multiplied and is now a factor that everybody in a company needs to be trained on. So how does a CTO navigate this?

Well, they’ll need to conduct a thorough analysis, set goals for the team, formulate a strategy, and then create a process that can be broken down into elements, which only then can be rolled out into the organization. Simple, not easy. As much as the CTO needs to have a clear vision behind the initiatives, they more importantly need to ensure the team is aligned with that vision, and that the benefits encapsulate the whole company. 

Identifying Marketable Talent

By 2031, the IT labour market in the United States alone is expecting to add more than 680,000 new jobs. The IT industry has always found it difficult to find talent that’s keeping up with trends and that can quickly be brought on to the team. To be clear it's not merely about filling job openings; it's about sourcing talent capable of adapting and excelling in a rapidly changing environment. Because of this, CTOs have to be proactive and implement measures to attract and retain marketable talent.

For a CTO, this can be difficult to balance with everything in the industry they need to keep up with and the trends they need to stay on top of. 

Safeguarding Data and Systems

Ensuring the security of IT systems and data stands is one of the most formidable challenges facing organizations worldwide. Cyberattacks happen about once every 40 seconds nowadays, companies today are in a perpetual battle against potential data breaches, which are exacerbated by the escalating activities and ingenuity of hackers and cybercriminals. “Human error” tends to compound these threats.

How Can CTOs Get The Most Out of Their Team in 2023?

The answer to this question starts with a simple note: Be a leader. CTOs play a pivotal role in spearheading initiatives that drive innovation. Whether it’s leading the creation of new products and services, or internal architectures to optimize output, the team's alignment starts with you. Especially when it comes to AI, CTOs are at the forefront of ensuring successful adoption within their company, which ultimately dictates their longevity.

Beyond technological advancements, CTOs are supposed to be building a strong employer brand by encouraging engagement within the tech community, sponsoring events, and promoting engineering thought leadership, thereby attracting and retaining top talent in this competitive tech landscape.

The Takeaway

We know that leadership is hard without the right support, especially with the demands of the tech landscape today. We work with companies that have in-house teams and those who need external expertise if they’re looking to scale their business dramatically within less than a year. Talk to us today to find out what we can do for you!

Written By Ben Brown

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ISU Corp is an award-winning software development company, with over 17 years of experience in multiple industries, providing cost-effective custom software development, technology management, and IT outsourcing.

Our unique owners’ mindset reduces development costs and fast-tracks timelines. We help craft the specifications of your project based on your company's needs, to produce the best ROI. Find out why startups, all the way to Fortune 500 companies like General Electric, Heinz, and many others have trusted us with their projects. Contact us here.

Big Data and the 4 Major V’s!

Anything from professional sports to ads and investment management and nearly everything in between. Every day, big data drives thousands of decisions that affect us both in big and small ways. So what exactly is big data, but also how or why does it affect initiatives in the area of health & welfare?

Let's begin with a description of big data. Big data is a concept used to characterize vast volumes of data that have emerged in the last decade or so. I know it's dull. It was originally used to characterize data sets that were so massive that they exceeded the reach and capability of conventional database and analytics tools. When Moore's law progressed, science caught up, but the data was still stored.

Big data is now more clearly characterized by a series of properties, than merely being a large amount of data. The four Vs – Volume, Velocity, Variety, and Veracity – are widely used to describe these characteristics.

Well, what specifically are these Vs, and how do they affect the universe of EHS? Let's take a better look!

Volume

Data can be seen as a significant contribution to the EHS scale today! When researching the size of datasets available to the public today, the Internet is a reasonable place to begin your search!

The number of Internet users in the 21st century has become outstandingly large. Therefore consumer interaction has also become a massive generator for large volumes of data in the interwebs. But, it is not just about people who are contributing to the massive amount of data, according to several statistics found online in the U.S, most businesses generate almost 100 terabytes of business data annually.

What exactly is the information being processed? It is mainly about CRM, financial data, and ERP data. Data on the atmosphere of a workplace, employees’ wellbeing, regulatory enforcement are all important sets of organization data collected in large volumes. 

Velocity

The rate at which new data is generated is referred to as velocity. Certain usage cases, once again, seem to be massive sources of new data production. Take, for example, the everyday events that take place in financial exchanges all around the world. Any exchange and activity generate a steady flow of updates.

So it's not just about stocks and shares when it comes to data velocity. Data is produced at a rapid rate for EHS professionals as well. Not only are safety violations being reported these days. Analyses of accidents and near-misses, disciplinary measures, preparation tasks, and reports are all operations that lead to the rich pool of EHS data you already have.

Variety

There is no longer a centralized source of data. In reality, data isn't entirely generated by computers in the way we think of them. Smartphones, wearable gadgets, and even internet-connected machines are all part of the internet of things. Many of these endpoints add to the mountains of data we already have. There isn't just a lot of choice in terms of devices. Heavy-duty data used to be the domain of the military and banking, but now it's the domain of everybody.

Also, seemingly straightforward business processes from the past, such as event monitoring and reporting, are now monitored in new, purpose-built EHS databases and platforms. The EHS system is no longer limited to event info. Platforms will also capture, compile, and interpret data from accidents, quality control, preparation, and risk matrices, among other aspects.

Veracity

Perhaps the one dark truth of all the evidence we now rely on is its veracity. In either case, how reliable is all of this information? Data accuracy is also a major concern. According to a study, the cost of bad data and the mistakes it can cause, cost the US economy more than $3 trillion dollars last year.

What steps will you take to ensure that your EHS data is of good quality? Use software and technology to ensure that all of the data is entered correctly and on schedule, whether it's event forms, investigations, or imports from foreign suppliers. Some software will also assist in ensuring the accuracy of your data by including external sources such as images and videos. Moving away from paper forms and manual processes in favor of a web-based framework is, of course, the most important step in ensuring the accuracy of your EHS results.

With this whole info, the biggest challenge is finding out how to derive the kinds of insights that will help you make real improvements, not only to your EHS systems but to your whole enterprise. That is, no matter how large your haystack is, you'll need assistance to locate the needles of wisdom that might be hidden within.

Valuing Time

EHS monitoring and research software can provide easy-to-use data exploration resources to you, the consumer. You can save time and money by using apps that allow intuitive reporting and move dashboards. You should be able to spend more time finding and visualizing insights and patterns in your EHS documents by using tools that help you to spend less time studying how to use them.

EHS Data Communication

Strictly speaking, EHS data exploration tools can make it possible for you to communicate in that language. Any EHS administrator or manager should be able to convey data, patterns, and problems to management and colleagues in other departments in a simple and succinct manner using a variety of charts and modern graphing software.

Decentralization of Analytics 

Nothing is more frustrating than seeing a department becoming a barrier in your workflow. The big data techniques of the past is developed with data scientists in mind. Most of the use of those early techniques has been refined and updated to make them more available to the rest of us. 

Search for EHS applications that have monitoring and light market analytics capability, allowing EHS administrators and program owners to easily analyze their EHS data in real time without the need for a corporate business analyst to serve as a middleman. This helps you to take care of your EHS data and access the knowledge you need when you need it.

For more insight, contact us today!

Data Quality Management: Best Practices and Processes

Data is important, but the quality of the data collected is more important. With the data collected, you can make business decisions, which is why it’s important to pay attention to your data quality. You should measure the quality of your data based on consistency, accuracy, completeness, timeliness, uniqueness, and so on. Here we will discuss the best practices and stages of data quality management.

Best practices of data quality management

Data quality management is a process that involves rational step-by-step execution. These steps normalize the data management practices which are used to incorporate data quality techniques into the business.

The best practices include:

• Prioritize data quality

Low data quality can cause a lot of issues. The first step is to ensure that your employees understand. Then, you create an enterprise-wide data strategy. Thirdly, design user roles with clear privileges and liabilities. Fourthly, establish a data quality management process and finally, have a dashboard to monitor the status quo. Incorporating all of this into your business process will help prioritize data quality management.

• Data entry automation

Manual data entry is one of the root causes of poor data quality. Human errors are sometimes inevitable, but automating data entry processes can help reduce it. Implementing data entry automation will help increase data quality.

• Preclude duplicates

As you should know, prevention is better than resolution. Precluding duplicates is a better option for improving data quality. Implementing duplicate detection rules and regular cleaning will help identify similar entries that already exist in the database. Then, you can ban creating another one or merge the entries.

Data quality management process

Data quality management revolves around certifying that the data is relevant, reliant, and accurate. It is a process aimed at accomplishing and preserving high data quality. Its main stages involve:

1. Gather data and establish data quality rules

After collecting and analyzing data, tables need to be created in database design. Then you scrutinize what data will be held in each table and what fields will be integrated into each table. In a situation whereby there are massive amounts of data in existence, you have to determine what is relevant to keep and what will be withheld in each table of the database.

2. Assess the quality of data

The business/technical rules that have been created and defined should be checked. The development of quality rules is essential for the success of the data quality management process. You should enforce these rules to make sure they will find and stop compromised data from corrupting the whole set.

3. Resolve data quality issues

At this stage, data quality rules should be reviewed again. The review process will help determine if the rules need to be modified or updated, and it will help resolve data quality issues. Once the data quality issue is resolved, vital business processes and functions should proceed more efficiently and accurately.

4. Monitor and control data

Data quality management is a continuous process that involves regular review of data quality rules. Monitoring and controlling data is very important in this time of constant change within the business environment.

Data quality can be ensured by engaging in effective data management tools. You have to consider a quality management solution that closely aligns with your unique business objectives. Data quality management involves many aspects and most often requires professional assistance. At ISU Corp we are always ready to help, contact us today!