ROI/TCO Analysis and Migration

Return on Investment (ROI) is the Return on Invested Capital of a company literally, i.e., the company’s total capital is divided by the company’s income. It helps in measuring the company’s performance. ROI is also sometimes referred to as Return on Assets, i.e., a company’s income for a particular period divided by the value of assets. In the business scenario, when one potential investment is compared with another, the term ROI is used to describe cash flow analysis.

Cost of Ownership means the total cost of acquiring, installing, using, maintaining, changing and getting rid of something over an extended period of time. Cost of Ownership figures are often developed for computer systems, medical test equipment and a wide range of other expensive capital items.

Cost of Ownership (sometimes called “Total Cost of Ownership”, or (TCO) usually means:

The total cost of acquiring, installing, using, maintaining, changing, and getting rid of something across an extended period of time (most or all of its useful life).

Cost of ownership figures are often developed for computer systems, medical test equipment, and a wide range of other expensive capital items. Note especially the following:

Cost of ownership is always more than purchase price, sometimes many times more. Total five year cost of ownership for computing equipment, for example, can be 3 to 10 times the original purchase price.

Naming the cost of ownership subject does not fix the boundaries for the cost of ownership analysis. You must still decide and communicate which costs belong in the analysis and why. IT costs of ownership comparisons from publishing analysts tend to have a rather narrow scope, focusing on purchase price, maintenance, and very direct operational costs (here the emphasis is on “Apples-to-Apples” comparability). IT cost of ownership analyses from sales people, consultants, or managers for specific settings tend to have a broader scope, aiming at the “Total” or “Comprehensive” cost of ownership (here the emphasis is on completeness and predictive accuracy for this setting).

Data migration

Data migration is a key element to consider when adopting any new system, either through purchase or new development. One would think that any two systems that maintain the same sort of data must have performed similar tasks. Therefore, information from one system should map to the other with ease. However, this is rarely the case.

Although migrating data can be a fairly time-consuming process, the benefits can be worth the cost for those that “live and die” by trends in data. Additionally, old applications need not be maintained. This section includes a discussion of the following topics: Data migration definition, Migrating legacy data decision, and How to migrate data.

What Is Data migration?

Some key terms in understanding data migration are:

- Legacy data is the recorded information that exists in your current storage system, and can include database records, spreadsheets, text files, scanned images and paper documents. All these data formats can be migrated to a new system.

- Data migration is the process of importing legacy data to a new system. This can involve entering the data manually, moving disk files from one folder (or computer) to another, database insert queries, developing custom software, or other methods. The specific method used for any particular system depends entirely on the systems involved and the nature and state of the data being migrated.

- Data cleansing is the process of preparing legacy data for migration to a new system. Because the architecture and storage method of new or updated systems are usually quite different, legacy data often does not meet the criteria set by the new system, and must be modified prior to migration. For example, the legacy system may have allowed data to be entered in a way that is incompatible with the new system. Architecture differences, design flaws in the legacy system, or other factors can also render the data unfit for migration in its present state. The data cleansing process manipulates, or cleans, the legacy data so it conforms to the new system’s requirements.

SaaS (Software as a Service), PaaS (Platform as a Service), IaaA (Infrastructure as a Services)

Software as a Service (SaaS) is a software distribution model in which applications are hosted by a vendor or service provider and made available to customers over a network, typically the Internet.

Benefits of the SaaS model include:

  • easier administration
  • automatic updates and patch management
  • compatibility: All users will have the same version of software.
  • easier collaboration, for the same reason
  • global accessibility.


Platform as a Service (PaaS) is a way to rent hardware, operating systems, storage and network capacity over the Internet. The service delivery model allows the customer to rent virtualized servers and associated services for running existing applications or developing and testing new ones.

Platform as a Service (PaaS) is an outgrowth of Software as a Service (SaaS), a software distribution model in which hosted software applications are made available to customers over the Internet. PaaS has several advantages for developers. With PaaS, operating system features can be changed and upgraded frequently. Geographically distributed development teams can work together on software development projects. Services can be obtained from diverse sources that cross international boundaries. Initial and ongoing costs can be reduced by the use of infrastructure services from a single vendor rather than maintaining multiple hardware facilities that often perform duplicate functions or suffer from incompatibility problems. Overall expenses can also be minimized by unification of programming development efforts.

Infrastructure as a Service is a provision model in which an organization outsources the equipment used to support operations, including storage, hardware, servers and networking components. The service provider owns the equipment and is responsible for housing, running and maintaining it. The client typically pays on a per-use basis. Characteristics and components of IaaS include:

  • Utility computing service and billing model.
  • Automation of administrative tasks.
  • Dynamic scaling.
  • Desktop virtualization.
  • Policy-based services.
  • Internet connectivity.