Full-Time

Governance

Risk, And Compliance, GRC, Analyst

Posted on 7/16/2024

aPriori

aPriori

201-500 employees

Cloud platform for manufacturing cost insights

No salary listed

Mid

Belfast, UK

Requires onsite presence in Belfast, Northern Ireland for two to three days per week.

Category
Risk & Compliance
Legal & Compliance
Required Skills
Communications
Requirements
  • 1-3+ years’ experience in a similar role
  • Proficient in documentation, including policy creation and data flow diagrams
  • In-depth knowledge of security frameworks, standards, and regulations (e.g., NIST, ISO 27001, SOC2, GDPR, etc)
  • Experience with security tools and technologies
  • Strong analytical and problem-solving skills
  • Excellent communication and interpersonal skills
  • Ability to work independently with minimal supervision
  • Ability to prioritize tasks and projects to meet deadlines
  • Professional certifications are a plus
Responsibilities
  • Assist with the ongoing development of the governance, risk, and compliance program
  • Develop and maintain information security policies, procedures, standards, and guidelines
  • Manage the Privacy Program, including compliance with GDPR, CCPA/CCRA, Privacy Shield, etc
  • Create and maintain data flow diagrams, network diagrams, and other illustrations as needed
  • Develop and deliver security awareness and training programs
  • Establish and support ongoing monitoring efforts for compliance
  • Support the development of Business Continuity and Disaster Recovery plans
  • Collaborate with internal teams to perform risk assessments
  • Identify areas for process improvement within the GRC program
  • Develop an understanding of identity and access management processes
  • Support SOC2 compliance activities
  • Stay current with industry trends in information security
  • Foster a culture of security awareness throughout the organization
  • Contribute to achieving business and departmental goals

aPriori provides a cloud-based platform that helps manufacturers improve product profitability and sustainability by offering insights into costs, manufacturability, and carbon impact. The platform streamlines the manufacturing process through digital factories, allowing companies to quickly generate Bill of Materials (BOMs) and automate cost analysis. aPriori stands out by emphasizing sustainability, enabling manufacturers to assess a product's environmental impact early in the design phase. The company's goal is to help clients achieve significant savings and a strong return on investment while aligning with global sustainability targets.

Company Size

201-500

Company Stage

Debt Financing

Total Funding

$137M

Headquarters

Concord, New Hampshire

Founded

2003

Simplify Jobs

Simplify's Take

What believers are saying

  • Recent investments enhance aPriori's resources for expanding digital manufacturing solutions.
  • The demand for digital twin technology offers market expansion opportunities for aPriori.
  • Cloud-based solutions trend aligns with aPriori's platform offerings, boosting its market appeal.

What critics are saying

  • Increased competition from AI-driven negotiation tools like Arkestro poses a threat.
  • Reliance on cloud platforms exposes aPriori to data privacy and security risks.
  • Rapid technological advancements may render aPriori's solutions outdated without continuous innovation.

What makes aPriori unique

  • aPriori leverages digital twin technology for manufacturability and cost insights.
  • The platform offers comprehensive product cost management solutions for discrete manufacturers.
  • aPriori emphasizes sustainability by providing carbon insights for environmentally conscious companies.

Help us improve and share your feedback! Did you find this helpful?

Growth & Insights and Company News

Headcount

6 month growth

3%

1 year growth

2%

2 year growth

-2%
Spend Matters
Jan 23rd, 2025
Why Should-Cost Models Aren’T Sufficient To Drive Market-Competitive Cost Structures

This content does not express the views or opinions of Spend Matters.Apple has made famous the use of ‘should-cost’ modeling and benchmarking as a cornerstone of effective procurement organizations for the past few decades, which has led many companies, big and small, to adopt the practice. The momentum around this ‘best practice’ has been further accelerated by the marketing efforts of market intelligence companies selling data and even a few purpose-built software platforms to make these efforts more efficient and accurate.While these models offer valuable insights into cost structures that are useful for driving an understanding of market dynamics and setting category strategy, especially when used in conjunction with other tools like SWOT and Porter’s Five Forces analyses, they also come with significant limitations when companies attempt to use them to guide negotiations and evaluate negotiation outcomes.This article will outline those limitations and propose that invoking competitive negotiations with machine learning solutions such as Arkestro is the optimal way to evaluate the market competitiveness of price quotes.These models don’t scale to all categories or all items within a categoryTo get to the level of sophistication for a should-cost to be effective as a true measure of a competitive market price requires both a high amount of category expertise, as well as time to create the model and back-test it against past results. This, given the productivity constraints of modern strategic sourcing teams, means that they often must choose between refining the assumptions and calculations in their model and doing other things, like studying the broader market, building supplier relationships or solving tactical challenges like shortages.Even where benchmarking data sets do exist and little modeling is necessary, it still requires bandwidth and a skilled eye to vet the models and data sets across every item within a category for every category of spend. This is a cost to the organization on top of the ‘hard’ cost required to evaluate, purchase and operationalize an accurate, vetted dataset for the many categories a typical company might be buying.Then, if a company has developed models and/or benchmarking data for a set of their categories, when used as the target, or measure of a ‘good’ quote from a supplier, it requires additional human attention if the cost that is quoted from a supplier is different from the modeled cost. Whether it is higher or lower than the ‘should’ cost, the question is always, is the model correct or is the quote competitive? Finding the answer to this question across tens, hundreds, or thousands of parts can create a wasteful cycle of time-consuming analysis.The core assumption of should-cost analysis is flawedShould-cost models assume cost-plus pricing, but most companies, especially in competitive industries, use value-based, dynamic, or competitive pricing strategies to optimize profits by focusing on customer value rather than production costs.IP-dependent products like microprocessors and pharmaceuticals are priced far above production costs to recover RD investments and reflect consumer value. Similarly, Apple commands higher margins than competitors like Dell due to its brand and the loyalty of its customers, even for functionally similar products

Cointelegraph
Jul 30th, 2024
Binance Labs invests in liquid staking platform aPriori

Binance Labs invests in liquid staking platform aPriori.

The Defiant
Jul 26th, 2024
Monad-based DeFi Projects Unveil Flurry of Funding Rounds

Kuru Exchange, Kintsu and aPriori have raised a combined $16 million as parallelized EVM Monad gears up for its testnet launch.

Blockchain News
Jul 26th, 2024
Pantera Capital Invests in aPriori, Enhancing Digital Manufacturing Solutions

Pantera Capital invests in aPriori, enhancing digital manufacturing solutions.

NFT Gators
Jul 25th, 2024
Kintsu Secures $4M Seed Round to Build Liquid Staking Protocol on Monad

The announcement comes the same day as another Monad-based liquid staking protocol, aPriori announced a $10 million funding round led by Pantera Capital.

INACTIVE