Cost optimization is a business-focused, continuous discipline to drive spending and cost reduction while maximizing business value. It includes: Obtaining the best pricing and terms for all business purchases. Standardizing, simplifying and rationalizing platforms, applications, processes, and services. Finding an alternative with the most cost-effective or highest achievable performance under the given constraints, by maximizing desired factors and minimizing undesired ones. In comparison, maximization means trying to attain the highest or maximum result or outcome without regard to cost or expense.

IT cost optimization

The classical optimization techniques are useful in finding the optimum solution or unconstrained maxima or minima of continuous and differentiable functions.

These are analytical methods and make use of differential calculus in locating the optimum solution.

10 cost optimization ideas

  • Create a shared-service organization for some or all IT services
  • Centralize, consolidate, modernize, integrate and standardize technologies
  • Leverage cloud services
  • Increase IT financial transparency to better manage both supply and demand
  • Utilize zero-based budgeting on the right cost categories
  • Rationalize and standardize applications before cost-saving initiatives
  • Optimize software licensing management and IT asset management capabilities
  • Improve procurement and sourcing capabilities
  • Invest in Mode 2 capabilities such as agile and DevOps
  • Re-examine how end-user computing is delivered

Cloud cost optimization

The value of cloud is in its on-demand nature, which frees up developers and IT to instantly gain access to resources to solve business problems. But at the same time, the lack of cloud cost optimization processes is resulting in significant waste in public cloud spend.

Cost optimization strategies

Implementing a cost optimization strategy is not a one-time initiative. Successful organizations view cost optimization as a continuous improvement exercise that results in a healthy balance of cost savings and innovation to help the business achieve extraordinary results.

Optimisation techniques

The classical optimization techniques are useful in finding the optimum solution or unconstrained maxima or minima of continuous and differentiable functions. An act, process, or methodology of making something (such as a design, system, or decision) as fully perfect, functional, or effective as possible; specifically: the mathematical procedures (such as finding the maximum of a function) involved in this.

List of some well-known heuristics:

  • Memetic algorithm.
  • Differential evolution.
  • Evolutionary Algorithms.
  • Dynamic relaxation.
  • Genetic algorithms.
  • Hill climbing with a random restart.
  • Nelder-Mead simplicial heuristic: A popular heuristic for approximate minimization (without calling gradients)
  • Particle swarm optimization.

Network optimization tools

The use of optimization software requires that the function f is defined in a suitable programming language and connected at compile or run time to the optimization software. The optimization software will deliver input values in A, the software module realizing f will deliver the computed value f(x) and, in some cases, additional information about the function like derivatives.

Optimization tools and techniques:

  • Protocol substitution or protocol proxy
  • Hardware compression
  • Compression/symbol dictionaries (aka deduplication)
  • Object caching
  • Traffic shaping and management
  • Traffic prioritization and grooming
  • Forward error correction