Altering the IT Costs Dynamic: Making the Case for a Consumption-Based Service Model

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The concept of scalable consumption of technologies is growing in popularity. The idea that companies can alter their IT costs dynamic is attractive to businesses where the amount of space and servers employed exceeds the actual usage. Paying for equipment that sits idle translates into waste, and companies that consider IT costs a fixed expense are under pressure to discover a more agile approach. Innovative consumption-based service models offer the solution.

With the advent of Software as a Service (SaaS), CIOs have an opportunity to integrate greater agility into the company by employing a consumption-based (or “as a Service”) IT model. Rather than pre-committing to IT costs based on full-time equivalent employees (FTEs), seats, or tasks, a usage-based approach relies on a data structure where expense directly correlates to consumption. The ability to scale resources based on usage offers organizations the flexibility and savings present in variable costs as opposed to fixed ones.

Transitioning to a cloud-based infrastructure is the foundation of this new cost reduction concept. Whether it is orchestrated through a dependable third-party provider or internally, getting the organization on board with the shift to consumption-based IT requires outlining the benefits of the efficiency and savings it establishes.

Making the Case

To implement consumption-based IT services and move company fixed costs to the variable column, organizations must sketch the advantages of the switch.

  • Agility: The primary reasons for the shift to consumption-based IT services include greater flexibility, quicker time-to-market, and simplified scaling. When work volumes fluctuate, this establishes a major cost reduction.
  • Cost Reduction: This type of IT service offers the ability to synchronize revenue with cost, calculate the benefits of the IT impact on a service or product, and engage new technologies without being saddled with debt or high capital expenditure.
  • Companywide Integration: Rather than focusing on single-point solutions, cloud-based infrastructure enables companywide pricing structure for an overall reduction in IT costs.
  • Ongoing Improvement: Consumption-based IT services allow for ongoing expense assessments. Enterprises have the power to continually review usage and pinpoint services or specific components that can be more efficient, and alter them as needed.

Moving to a consumption-based service model lowers IT costs. By instituting workable flexibility that gives both components and services the ability to evolve, businesses can establish improved performance in a low-cost framework. An agile, cost-efficient infrastructure delivers cutting-edge resources that improve efficiency and productivity throughout the organization.

Information Management: Data Infrastructure Explained

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Data InfrastructureMany companies experience communication issues that contribute to measurable losses in the form of mistakes. As a business grows, so does the need for a workable data infrastructure that supports productivity. Innovation in technology has altered the traditional business dynamic, changing the way information is processed, and the result is that a large number of companies are suffering from a poorly designed infrastructure. However, by understanding the elements involved in data infrastructure development, businesses have the ability to increase efficiency and lower operating costs.

Defining Data Infrastructure

Data infrastructure is generally defined as the digital means utilized for the consumption and sharing of information. It can be likened to the physical infrastructure of a state. Large cities employ complex traffic controls and intricate roadways, while smaller towns typically rely on simpler designs and still employ dirt roads in certain areas. The same is true for businesses. Larger companies require formal processes for controlling vital information, while smaller companies are more relaxed. Depending on the organization’s size and mission critical tasks, levels of data infrastructure designs include:

  • Tribal—A small company that relies on word-of-mouth communications. Questions are answered by speaking to the person most likely to know.
  • Enforced—An organization that employs the rudiments of controlled processes. Written procedures and data repositories make information available to a larger number of persons. Spreadsheets and software applications are used to facilitate the workflow.
  • Standardized—At this point, growing companies begin to remove duplicate processes and other wastes by implementing a centralized system, such as an ERP system, as a means of stabilizing and controlling data for improved productivity.
  • Actualized—This is the point where an organization begins to discover ways to utilize data to improve efficiency. Vendor management and customer relations management programs offer increased performance and lowered costs.

Once the infrastructure is in place, it is able to support continued growth and improvements by building a foundation that enhances the methods used to gather, use, and distribute information.

Understanding the Importance of Data Infrastructure

When the infrastructure is developed around the type of data used in an organization, it offers the power to limit operating and capital expenditures while supporting productivity. The elements companies must consider when developing data infrastructure include:

  • Collection Procedures—Organizations can collect data from both internal and external sources. Big data is defined as large amounts of information that can be analyzed to predict trends and patterns relative to behaviors and interactions. Companies can interpret data from sales, financial, logistics, and other internal sources, along with social media and external news sources that guide future endeavors.
  • Storage—The space required to keep all the data collected is another element for consideration. Many companies lack the budget to arrange for in-house servers, but the advent of cloud data storage has solved that problem. As a cost-effective, secure solution, cloud storage offers a useful means for storing and accessing data when required.
  • Analytics—Various software tools and specific engines are able to analyze the information most relevant to an organization. The infrastructure design should include an effective method for drawing conclusions based on company needs.
  • Reporting—This involves transferring analyses into a form that offers easy comprehension for decision makers within the organization. The reporting process is where the data enters and positively affects the actual processes.

Building a data infrastructure that facilitates the way companies collect, apply, and share information enables an environment of growth through efficiency. Understanding the methods of development for a specific organization enhances productivity and lowers costs.