Back to blog
/Simulation

Why not simulate?

Why simulations remain underproduced and underconsumed
November 29th, 2020
HASH
HASH
Why not simulate?
Why is my business not already using simulation? This post is a quick guide to some commonplace historical hang-ups and where they've left us…

Simulations are exceptionally powerful tools for optimizing systems, guarding against risks, and ultimately for making better-decisions. In spite of this, adoption remains a fraction of what it could be, and many organizations fail to utilize simulation at all.

The lowest-hanging fruit within data science and decision-support has, for a long time, been simple regression analysis and anomaly detection. Neither of these require any form of 'simulation', and both may yield relatively high-payoffs (or cost savings) when applied properly.

As companies look to increase the sophistication of their data-driven operations and ask where future value may lie, simulation offers the next-best bet.

Why, though, hasn't simulation taken off to date?

Historically expensive to build, as well as time-consuming and costly to maintain, "digital twins" of organizations, their people, and their processes have been out of reach for all but the largest of players -- and even then they have rarely found their way out of siloed applications.

The most common forms of simulation modeling today are:

  1. partial-implementations of things like Monte Carlo methods within software such as Excel; and
  2. highly specialist, domain-specific applications (such as Finite Element Analysis software) which carries with it a high barrier to entry, and typically lacks interoperability with other analytical frameworks.

Tooling around simulation has additionally been expensive, and hard-to-use, all but ruling out simulation modeling for everyday, general-purpose and cross-organizational use.

Modern simulation

Our mission at HASH is to eliminate information failure, and as part of that we're working to democratize access to powerful simulation tooling through a free-to-access, vertically-integrated simulation platform.

Simulation finds itself broadly-speaking where Machine Learning was approximately ~15 years ago. Proven out in academia, utilized by defense departments of advanced nations, and adopted by quant-hedge funds -- but beyond the reach of everybody else.

HASH aims to address this by being:

  • Easy to get started with -- no development environment setup is required (thanks to hCore), and no DevOps experience is necessary, even when running large models in a distributed fashion (see hCloud). This means that data scientists with minimal knowledge of Python, and those within organizations who have even only rudimentary knowledge of JavaScript, can create hyper-realistic multi-million agent simulations.
  • Fast to build meaningful models with -- identifying data in, and transforming data to, an "agent-mapped format" has historically been time-consuming. Through hIndex, and Flows in HASH respectively, we make this easy. hIndex additional contains community-published simulations and behaviors which can be forked and cloned for use in one's own business, covering a wide range of supply chain, logistics, cloud computing, social distancing, and other key business concerns.
  • Free to use in most cases, and low-cost at enterprise-scale (pricing);
  • Built atop an open-source core (hEngine);
  • Reproducible and verifiable at heart, earning the trust and confidence of users who may not be familiar with, or otherwise open to, simulation-backed decision-making.
  • Production-ready: through scheduled runs, background recompute, and programmatic outputs, insights from HASH simulations can be continuously incorporated into real data-science workflows, and algorithms.

This latter point is perhaps most important. Productionizing simulation outputs has long been a manual, time-consuming process. Outputs of simulations have, at best, sometimes been seen as mere "cool visualizations". With HASH, simulations of all kinds (including system dynamic and agent-based models) can become first-class citizens within data scientists' toolkits at last.

Create a free

account

Sign up to try HASH out for yourself, and see what all the fuss is about

By signing up you agree to our terms and conditions and privacy policy