5 Mistakes in Datacenter Design and Planning (And How to Avoid Them)

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Planning & building a data center is a major undertaking. What are the 5 most common planning mistakes? And what are the best ways to avoid them? 

Constructing a data center requires reconciling numerous complex interdependent factors – capacity, redundancy provisions, energy efficiency targets, budget constraints, and scalability needs. This multifaceted challenge leaves room for oversight even among seasoned field veterans.

Such oversights impose steep remediation costs, whether from upgrading undersized infrastructure or contention arising from unanticipated density levels. Let’s get down the road of catastrophic Data center planning mistakes and find our way around them.

Overlooking Total Cost of Ownership (TCO) in Data Center Design Phase

Data center consulting teams know the fundamentals – facilities built to last balance three spending pillars:

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  • Capex: (Capital Expenses) set the floor. Rack costs, construction bids, and contingency cushions.
  • Opex: Operational Expenses) keeps things running, this includes Staff, parts, and repairs through the decades.
  • Utilities: The monthly energy bills to power and cool it all.

So, as you may imagine, Ignore any leg and the stool topples. When expansion’s on the table, reassess the triangle with equal weight. If capex crowds out lifecycle views, future-you will feel the pinch. Being generous with opex and energy profiles minimizes surprises.

Maybe there’s a strong case to outsource operations entirely. Doing so redirects focus from facilities management to strategic initiatives. Regardless of the approach, the outlook must span multiple budget cycles.

Balance Your Financial Planning

Striking the right balance controls costs and risks over the long haul. Get lopsided, and either capabilities or finances wind up compromised. By holistically assessing expenditures from start to finish, data centers retain flexibility to support an organization’s ever-evolving needs.

Poor Estimation of Construction Costs

Data center teams often present overly conservative cost estimates to get projects greenlit. However, trimmed budgets frequently create cost overruns down the road from:

  • Construction bid inflation
  • Equipment/material price hikes
  • Inadequate contingency provisions
  • Unexpected delays compounding timelines
  • Scope creep from unplanned complexity

The result is budget shortfalls, quality sacrifices, scaled-back resilience, or outright cancellation – all eroding projected value.

Thorough upfront analysis bakes in realistic buffers and trends to allow for volatility. While perfect foresight is impossible, honest projections aligned with market forces demonstrate responsibility. This minimizes the potential for nasty financial surprises or credibility damage when unforeseen events inevitably emerge.

Even if it means longer waits for approval, accurate cost planning upfront gives data centers the strongest foundations for serving long-term needs despite continuous uncertainty.

Mismatched Design Criteria and Performance Features Definition

Organizations often mismatch their data center design criteria to actual performance needs, leading to overbuilt or misaligned facilities. Two common errors occur:

  1. Pursuing max tier certifications regardless of workload criticality. Gold-plated redundancy wastes capital if unsupported by risk profiles.
  2. Setting capacity benchmarks detached from measured demand. For example, mandating 300+ watts per square meter without data-based projections strands power density capabilities.

These errors result in low utility infrastructure with costs unjustified by value. The prudent approach is inverting typical planning steps:

  1. Analyze essential performance thresholds based directly on workplace outputs and risk tolerance.
  2. Right-size specifications to these need-driven criteria around capacity, redundancy, efficiency, and tier level.

While resisting over-specification requires discipline, facilities tailored to measured needs optimize capex/opex to practical returns. Data-driven design matching genuine business requirements right-sizes data centers to an organization’s reality.

Site Selection Before Design Criteria Establishment

It’s easy to let the hunt for ideal data center sites start before nailing down what makes one ideal in the first place. Eager development teams tour potential builds, assess acreages, and calculate power grids in regions of interest without baselining must-have specs grounded in workflow realities.

But these well-intentioned site searches too often waste precious cycles. Because they lack guardrails on minimum space, network proximity, seismic resilience, or accessibility needs among other glaring gaps. Missing criteria transform site tours into fruitless guesswork unable to validate fits.

To wrap up, we know that defining design criteria isn’t attractive, but doing so lights the path for site searches by establishing goalposts. This prevents wasting resources assessing locations lacking must-have infrastructure or risk mitigations mandatory to support defined workloads.

With non-negotiable capabilities guiding property evaluations, technology leaders can then select locales complementing data center needs both on day one and years down the road.