Measuring The Relevance of Your IT Spending Strategies
by Christian Ofori-Boateng on Aug 10, 2022 4:03:16 PM
For many organizations, the question that keeps their executives up at night is deciding on their IT spending strategy for the next two years. Recent reports indicate that Microsoft is reducing staff in areas such as consulting and partner solutions while adding staff in other -- more technical -- areas. At the same time, Gartner suggests that a tight labor market, rising inflation, and a possible recession have more companies looking to outsource IT to stay within budget. Is there a right strategy?
The best strategy is a data-driven one. Management must look at technology trends to decide what technologies to implement. They have to evaluate the cost and determine what resources are needed to achieve a successful deployment. Without data, executives are only guessing at what the impact of their IT spending strategy will be.
Whether it's McKinsey, Forrester, or Gartner, analysts see the following technology trends evolving during 2022:
- Edge Computing (IoT)
- Automation (AI and ML)
- Cloud Services
Knowing which trends to implement depends on data. Whether it's cybersecurity or cloud services, organizations must determine priorities and then establish key performance indicators (KPIs) to ensure that the investment is producing results.
It's well known that cybersecurity specialists are in short supply. A recent survey found that over 60% of security teams were understaffed and had unfilled positions. The lack of qualified applicants only adds to concerns as cybercrime is expected to increase at a rate of 15% per year. Companies with the budget to hire personnel can wait more than six months to find the right fit.
If businesses are lucky enough to hire an applicant, they may not keep them. Approximately 60% of survey respondents said they had difficulty retaining staff. Employees are leaving for advancement opportunities and better compensation. Some are looking for more flexible schedules or a less stressful work environment.
As companies assess the cyber tools needed to ensure a strong security posture, they have to consider in-house capabilities. Should they purchase more expensive tools that automate processes to compensate for the lack of personnel? Do they have in-house staff who can use advanced tools? Having access to information on in-house skill sets and existing workloads can help determine the best cybersecurity strategy.
According to a Deloitte Survey, senior executives see several barriers to adopting blockchain technology. Two critical concerns are in-house capabilities and an uncertain return on investment. The cost to implement an application on a blockchain platform can range from a few thousand to millions of dollars, depending on the complexity. That doesn't include the ongoing maintenance and platform fees.
Deciding on a blockchain solution requires data. Do you have the necessary in-house skills, or do you need to outsource? What reporting do you have in place to monitor the IT spending strategy? With tight budgets, it's essential that development projects are closely monitored to ensure a positive ROI.
Edge Computing and Internet of Things
While cloud computing has solved many issues related to a remote workforce, it has also uncovered limitations. Centralized data processing can result in latency issues across the network. Sending volumes of data from sensors on a factory floor to the cloud slows the response time to changes. If a sensor reports a heat spike, the data has to travel from the device to the cloud and back before an adjustment can be made. As the data moves, it consumes resources which can reduce bandwidth for video calls, resulting in latency issues.
Locating computing resources closer to where data is collected reduces the strain on the network and provides a faster response time for devices sitting on the network's edge. Whether the devices are physical such as sensors, or virtual such as cyber tools, edge computing provides an alternative to the increasing cost of cloud storage.
As companies assess their technology priorities, they will need to look at their IT spending strategy to determine if the move to edge computing will have a measurable impact on operations. Again, data is crucial. Knowing how the network performs now and what improvements can result from edge architecture enables a data-driven decision.
Automation in the 21st century means adding artificial intelligence (AI) to existing systems or replacing older technology with AI-driven solutions. According to Forrester, companies need to build a data fabric to support the growing use of AI. Any AI-based solution requires lots of data drawn from multiple sources. For AI implementations to work effectively, organizations need an architecture that facilitates the exchange of data across applications.
Most AI deployments require that data be cleansed and presented in a standard format regardless of the source. That has led to multiple data processing engines, each supporting a specific AI solution. Creating a data fabric means eliminating the need for multiple systems making it possible for faster implementation.
The most costly component of AI is preparing the data. By using a data fabric approach, organizations have one data processing engine that can be accessed across the enterprise. The concept ensures a single source of truth for all applications.
Companies are expected to spend almost $600 billion on public cloud services by 2023. Worldwide, growth is projected to grow over 20% in 2022. Hybrid work environments are driving more organizations to look to the cloud for operating solutions. Many solutions operate as a service allowing businesses to access resources for a monthly subscription fee. Depending on the service, enterprises can pay for technical support and expertise if internal resources lack cloud computing skills.
Again, organizations must look at the cost of technology and the staff to support it. Without data on what skills are needed for cloud computing, executives may move forward without experienced personnel. At the same time, executives need information on employees. Is there someone in IT who could gain the skills with a little training? With the right information, companies can find innovative solutions to ensure the maximum return on IT spending.
IT Spending Strategies
Developing an IT spending strategy means prioritizing technology needs in relation to financial constraints. It involves setting KPIs for ongoing evaluation. Using reporting tools that deliver information automatically ensures that KPIs are monitored. Implementing a solution such as ChristianSteven's Power BI Report Scheduler (PBRS) ensures that the right information is delivered to the appropriate people on time, every time.
As you develop your IT spending strategy, make sure you have the tools necessary to measure your strategy's success. Why not start your free 30-day trial today?