ClimSystems

We'd like to urge businesses, local authorities, and members of the public across Aotearoa New Zealand to heed weather warnings released by MetService on ex-tropical Cyclone Vaianu 🌀 this weekend. This is turning out to be a significant wind event, with similar wind gust profiles to the 2022 Cyclone Dovi event that caused significant treefall and infrastructure damage across the upper North Island. Our homebase, Hamilton, a landlocked city relatively sheltered from high winds, paid over $1 million in recovery costs. Read more here: https://lnkd.in/eHPX_MrR Image credit: earth.nullschool.net | Wind | 10 April 2026 15:00 #cyclonevaianu #extremeweather

You're now equipped to choose your climate data provider. For the past 20 weeks, our #ClimSystemsDataCheck series has guided you through the critical questions to ask any provider. We've moved from Data Indicators to Methodology and finally to Suitability. Today, we're bringing it all together in our final post. ➡️ Swipe through our carousel for a summary of the 3 key pillars of your due diligence: ✅ Data: Is it accurate, transparent, and fit for purpose? ✅ Methodology: Is the science robust, defensible, and unbiased? ✅ Suitability: Is the solution usable, scalable, and supported? Thank you for joining us on this journey. The right questions lead to the right data. The right data leads to real resilience. 💬 What was the most useful indicator from this series for you? Let us know in the comments! #ClimSystemsDataCheck #DueDiligence #ClimateRisk #DataIntegrity #ESG #Sustainability #RiskManagement #ClimateAction

Is your climate data provider's pricing as clear as their data? "You get what you pay for" is only true if you know what you're paying for. A low-cost solution with hidden fees, poor support, and non-defensible data is more costly than a transparently-priced, high-value partnership. This week, #ClimSystemsDataCheck tackles the final Suitability Indicator, cost and value. ➡️ Swipe through our carousel to explore: ✅ Why "value" is more important than "price." ✅ The hidden costs of "cheap" data (think unusable formats, poor support, and reputational risk). ✅ Key questions to ask to get a transparent, all-in price. Don't just ask "how much?" Ask "what's included?" 💬 What's the worst example of "hidden fees" you've ever encountered in a B2B service? #ClimSystemsDataCheck #ROI #TotalCostOfOwnership #TCO #ClimateRisk #DueDiligence #Transparency

When your team has a critical question about your climate data, is your data provider a good partner? Climate science evolves. A "set forget" approach to climate data is dangerous. You're not just making a one-time purchase; you're entering a long-term partnership. This week, #ClimSystemsDataCheck looks at a crucial Suitability Indicator, support and maintenance. ➡️ Swipe through our carousel to learn: ✅ Why access to human experts—not just a helpdesk—is essential. ✅ The difference between a "data vendor" and a "science partner." ✅ Key questions to ask about data updates, expert support, and ongoing maintenance. Your provider's support system is a direct reflection of the quality of their data. 💬 When it comes to technical support, what's one thing that makes a company stand out (good or bad)? #ClimSystemsDataCheck #CustomerSupport #ClientCentric #ClimateScience #DataGovernance #RiskManagement

Your climate strategy will grow. Can your data keep up? A solution that works for one asset is great, but what about 100? Or 1,000? And will it "talk" to your existing systems? Data that lives in a silo is a dead end. This week, #ClimSystemsDataCheck moves to two vital Suitability Indicators, scalability and integration. ➡️ Swipe through our carousel to find out: ✅ Why you must plan for scalability before you sign a contract. ✅ The power of APIs and data integration (and why you should ask about them). ✅ Key questions to ensure your climate data can be woven into your existing workflows. Choose a solution that grows with you, not one you'll outgrow. 💬 What’s your biggest frustration when trying to get different software platforms to work together? #ClimSystemsDataCheck #Scalability #DataIntegration #API #GIS #ClimateTech #FutureProof

Having the best climate data in the world is pointless if you can't use it. Your team should not need a data science PhD to understand the outputs. True resilience requires data that is accessible and intuitive for the people who use it to make decisions efficiently. This week, #ClimSystemsDataCheck examines a critical Suitability Indicator, usability and accessibility. ➡️ Swipe through our carousel to explore: ✅ Why complex data must be delivered in a simple, intuitive format. ✅ The red flags that indicate a provider's platform may be a barrier to action. ✅ Key questions to ask about data formats, user interface, and team training. Data should be empowering, not frustrating. 💬 What's the biggest usability challenge you've faced with a data platform (climate or otherwise)? #ClimSystemsDataCheck #Usability #DataAccessibility #UIUX #ClimateTech #RiskManagement #DataToAction

Does your climate data speak the same language as your regulators and investors? In a world of increasing climate disclosure requirements, using a non-standard approach is a major risk. If your analysis doesn't align with recognised frameworks like the Task Force on Climate-related Disclosures (TCFD) or International Financial Reporting Standards (IFRS), it may not stand up to scrutiny from boards, investors, or regulatory bodies. This week, #ClimSystemsDataCheck kicks off our look at Suitability Indicators by looking at alignment with global and national standards. ➡️ Swipe through our carousel to see: ✅ Why alignment with official standards is critical for credibility. ✅ How using standardised data simplifies reporting and builds trust. ✅ Key questions to ensure your provider's approach is compliant and defensible. Ensure that your assessments are recognised and auditable. 💬 Which reporting framework is most critical for your organisation right now? TCFD, IFRS, or something else? #ClimSystemsDataCheck #TCFD #IFRS #ClimateReporting #ESG #DueDiligence #Compliance #Sustainability

Is your climate data provider operating independently and impartially? The credibility of any analysis rests on the objectivity of its source. If a climate data provider has a hidden agenda or a vested interest in a particular outcome, their data might steer you in the wrong direction. This can lead to skewed risk assessments and poor investment decisions. This week, #ClimSystemsDataCheck looks at a topic that’s core to trust: independence and impartiality. ➡️ Swipe through our carousel to find out: ✅ Why an impartial, science-first approach is non-negotiable. ✅ The risks of using data from providers with potential conflicts of interest. ✅ Key questions to help you gauge a provider's objectivity. Trustworthy insights must be free from influence. 💬 What are the biggest green flags that tell you a provider is truly independent and science-driven? #ClimSystemsDataCheck #DataIntegrity #ScientificIntegrity #Objectivity #DueDiligence #ClimateRisk #Transparency

Is your climate data the right tool for the job? Using a tool that isn't fit-for-purpose generally leads to poor outcomes. You wouldn't use a thermometer to measure distance. Similarly, using climate data that isn't relevant, valid, and reliable for your specific challenge can lead to flawed strategies and wasted investment. This week, #ClimSystemsDataCheck untangles three crucial concepts: relevance, validity, and reliability. ➡️ Swipe through our carousel to learn: ✅ What these three terms mean in the climate data space. ✅ Why data that’s valid for one purpose might be unreliable for another. ✅ The key questions to ask to ensure the data you're using is truly fit for your purpose. Don't just ask if the data is "good." Ask if it's right for you. 💬 Have you ever encountered data that was accurate but not useful for your specific problem? #ClimSystemsDataCheck #DataValidation #DataQuality #ClimateRisk #DueDiligence #ScientificIntegrity #FitForPurpose

Do you know what's powering your climate data? Great climate data isn't just about the raw inputs; it's about the sophisticated statistical analysis used to process and interpret them. Weak or inappropriate statistical methods can distort reality, leading you to plan for the wrong outcomes. Today, we're looking at how to ensure that your climate data is backed by robust statistical analysis. ➡️ Swipe through our carousel to understand: ✅ Why is the quality of statistical methods a critical sign of a provider's expertise? ✅ The difference between a simple average and a meaningful analysis of extremes. ✅ Key questions to ensure the data you're using is statistically sound and reliable. The devil is in the details — and the data. 💬 What’s one statistical concept in climate data that you’ve found challenging or want to know more about? #ClimSystemsDataCheck #StatisticalAnalysis #DataScience #ClimateModels #DataValidation #ClimateRisk