Key Messaging
- Precisely, the leader in data integrity
- Accuracy, Consistency, Context
- Unique blend of software, data, and strategic services
Data Integrity for:
AI Ready Data
- Idea: Garbage in, garbage out. Data Integrity is step 0 for any AI initiative.
- Question: What is your AI strategy? What strategic initiative does it support in your organization? What Data is feeding your AI initiatives and how are you ensuring it is AI ready?
- Data Integrity for AI Success
Analytics and BI
- Idea: If your data isn’t fit for purpose and automated then you’re falling at the first hurdle in regard to analytics and BI
- Question: What data is driving your analytics insights? Do you trust this and how do you ensure data quality?
Location intelligence
- Idea: Businesses struggle with poor-quality addresses, disconnected datasets, and limited real-world context – leading to inefficiencies, missed opportunities, and increased risk. Precisely’s location data management solutions help you correct, enrich, and analyze location data with geo addressing, data enrichment, and spatial analytics-turning raw data into actionable insights.
- Questions:
- How confident are you in the quality of your location data?
- What questions are you trying to answer with your existing location data?
- Is your location data part of operational processes? Which ones?
Compliance
- Idea: Lack of infrastructure, process and reporting creates compliance blind spots.
- Question: How do you prove compliance and what challenges do you face in delivering that proof?
Data Modernization
Mainframe Modernization
- Idea: Manual and siloed data across the organisation creates inefficiencies in downstream processes.
- Question: How are you ensuring the data moving to the cloud has high quality?
Data Mesh & Data Fabric
- Idea: A World Drowning in Data is exploring modern data management architectures to manage their data more effectively and efficiently.
- Question: What are your organizations plans or considerations for exploring architectures such as a Data mesh or Data Fabric?
- Data Mesh is a modern architectural strategy that empowers domain experts and owners to create, organize, and manage data products for more agile and trusted business insights and outcomes.
- Data Fabric is an innovative data architecture that facilitates seamless data access, management, and sharing across an organization through a combination of data management components.
Your data is meant to be loved
- Idea: Businesses often face challenges with data quality, integration, and context, leading to inefficiencies and missed opportunities. Precisely’s “Data is Meant to be Loved” campaign emphasizes the importance of trusted, AI-ready data. Their solutions focus on integrating, improving, governing, and contextualizing data, enabling organizations to make confident decisions based on accurate and enriched information. Within this campaign we look to swap the adjective ‘love’ for the most appropriate in the given conversation.
- Questions:
- Would you say you love your data, if not then why?
- What challenges do you face in integrating and governing your data across various sources?
- How is your data prepared to support AI initiatives and drive better business decisions?
Horizontal Discovery Questions
- What is your core data strategy and where are you within this now?
- Where are some of the opportunities you see for development/improvement within this strategy?
- What tools & systems are you currently using to support this strategy?
- Is your data strategy business or IT driven?
- How reliant is your business/team on SMEs.
Start the Story
Data Integrity means you have truly useful, trusted data that you can rely on to support critical business decisions and activities …
Continue the Story
… Achieving data integrity means you can centrally manage master data across all your systems and enrich and enhance that data for even greater insights and value, unlocking the true potential of your data.
Customer Challenges
- Accessing, integrating, cleansing, and enriching data requires a highly skilled SME or external resource.
- Data is difficult to find or access.
- Business generated data only tells part of the story, without context confident data-driven decision making is not possible.
- Not able to get a full view of the customer relationship.
Differentiators
- Data enrichment capabilities with over 400 curated data sets that allow us to expand with your business.
- Expansive global data sets meaning less time prepping data and more time meeting business goals.
- Easy enrichment of addresses with valuable context using a PreciselyID.
- Interoperable datasets with a quality standard, consistent documentation, and support.
- Data experience through deep-domain expertise
- Our data graph API helps make data more accessible, ensures that only relevant data is accessed, and boosts operational efficiency. Available data categories include address, property, business, natural hazards, boundaries, demographics, and more.
Customer Stories
AON
- Leveraged the data graph API specifically buildings and parcel data to efficiently and comprehensively assess properties so that they could deliver trusted underwriting recommendations to their commercial risk customers.
- Were able to streamline data discovery and retrieval saving time and resources.
- Were able to enhance customer experience due to rapid delivery of risk assessments that enabled a reduction in underwriting and claims leakage.
Keller Williams
KW App leverages extensive curated content directly from internal systems while also supporting direct communications and interactive decision making with their agent.
International Streaming Service – Disney/Hulu
Roll out a “Unified Platform” leveraging location data to grow revenue opportunities
Leading Fast Food & Beverage organizations – Starbucks, McDonalds
Roll out a “Unified Platform” leveraging location data to grow revenue opportunities
- Gain clarity on spending and behavior
- Captured 8% increase by understanding history of purchasing
Largest Social Media Apps – Meta/Twitter
Leverage essential data such as boundaries for location quality and verification when interacting such as ‘checking in’
Capability Specific Discovery Questions
- What does your data vendor landscape look like? Are you working with multiple suppliers across the business/departments?
- How does data enable your understanding of the risks and opportunities associated with different locations?
- What is your current exposure to static and/or dynamic data in your decision making?
Continue the Story
… The data integrity journey continues with integrated data governance and continuous quality checks and improvements for all data types and sources. Allowing you to find, understand and trust your data.
Verify use cases that apply
- Discovery & Assessment: Discover what data exists, assess its level of quality, and proactively identify anomalies.
- Business-first governance & stewardship: Operationalize and monitor quality, policies and standards to ensure trusted data is accessible across all teams.
For Government agencies:
- Precisely Data Governance services is in the process of being FedRAMP certified
Customer Challenges
- Data asset ownership, content, lineage, and meaning are unclear causing inaccurate and inconsistent business outcomes. (Verify use case Business-first governance and stewardship)
- Data assets are not understood or linked to company KPI’s or objectives causing missed business opportunities. (Verify use case Business-first governance and stewardship)
- Our data catalog/data governance solution is too technical and is hard for users and data stewards to work with. (Verify use case Business-first governance and stewardship)
- I don’t know what data I have or can trust (Verify use case Discovery & Assessment)
- Visibility into data quality scores, rules, and metrics to drive confident, trusted data-driven decisions. (Verify use case Discovery & Assessment)
- Do not know what data assets exist causing wasted operational expense looking for it. (catalog)
Differentiators
- Business-friendly features (flexible framework, 3D diagrams, and streamlined workflow) to increase ROI & adoption by business & IT teams (Verify use case Business-first governance and stewardship)
- Unique catalog card views share lineage, technical data details, and DQ scores to easily understand the data (Verify use case – Discovery and assessment)
- Embedded tracking and metrics linked to goals and KPI’s to bring visibility to real business value. (Verify use case Business-first governance and stewardship)
- User-friendly card catalog views in the data catalog empowers users to easily view technical details, lineage, and quality scores at a glance (Verify use case – Discovery and assessment)
- Precisely Data Governance services is in the process of being FedRAMP certified within the year.
Customer Stories
Northwest Bank
Trusted data for compliance & revenue generation
Central Insurance
Improve confidence in data as an asset strategy
Vantage Towers (one of the largest Telco in Europe)
Struggled with financial compliance around lead to cash process. Leveraging a single vendor for DG, DQ and Strategic services sealed the deal over Collibra.
Capability Specific Discovery Questions
- What are your goals for data governance? Are you looking to increase data literacy or data discovery?
- In your opinion, where do the challenges lie in helping your team understand the data? Are we talking about data meaning, ownership, quality, lineage? How do you monitor those things now?
- We can bring all of those together in a single business-friendly interface to increase data literacy and understanding.
- What specific compliance standards or regulatory frameworks are you currently required to meet with your data? What are the consequences of non-compliance?
- We can bring visibility and accountability around internal and external compliance requirements reducing risk and fines and expediting reporting.
- Who are the main users/stakeholders around this business use case? Are they more business-focused, technical – or both?
- We can support technical and non-technical users and data stewards and encourage collaboration through our business-friendly interface and flexible no-code framework.
Continue the Story
… Precisely’s Data Integration breaks down data silos by enabling real-time data replication to cloud applications. Our “design once, deploy anywhere” approach allows you to build and deploy data pipelines seamlessly—on-premises, in the cloud, or both—without restrictions. We offer flexible deployment options, including hybrid SaaS, private cloud APIs, and customer-deployable solutions. With deep expertise in connecting legacy systems like mainframe, IBM i, SAP, and Oracle to modern cloud platforms, we ensure real-time data delivery for all your business needs.
Customer Challenges
- Lack of access and incomplete data – difficulty integrating between on-premises and cloud platforms creates data silos
- Living with legacy tech debt has increased pressure for delivery of real-time insights to improve decision making, customer experience/channels, and applications
- Time and money being spent on maintaining legacy architectures and systems
- Pressure to expand into modern technologies creates a need for a strategy and technology stack that will not isolate current investments
Differentiators
- Ability to handle highly-complex, file structures including mainframe
- Real-time, resilient, fault tolerant data replication pipelines
- High performance with low latency
- Reverse sync captures cloud and app data changes and syncs them back to the mainframe
- Partnerships: AWS (OEM relationship), Azure, Confluent, Databricks, Google, Snowflake, etc.
Customer Stories
Objective:
Deliver a real-time data product using mainframe data that could serve as an internal anchor/centralized resource for data used within processes across its business
Outcome(s):
Enhancing customer experiences by feeding transactional data from their mainframe in real-time to a centralized data lake for use by multiple business units and external partners.
Problem(s):
1) Mainframe data was siloed away from the rest of the business, but most customer transaction data lived on this system.
2)Data delivery was done through homegrown APIs that were not reliable.
3) Customer experience was not competitive since information was delivered on a delay.
Tech Solution:
Precisely data replication to Microsoft Azure via Confluent
Objective:
Improve gaming revenues, provide new strategy recommendations, and streamline hospitality operation by leveraging their IBM i data for advanced analytics
Outcome(s):
1) Time and cost savings through the automation of data delivery, removal of 3rd party contracts and homegrown applications.
2) Modernization efforts were no longer stalled, and able to make gains towards AI readiness.
3) Business is no longer waiting for data – it’s delivered in near real-time
Problem(s):
1) Homegrown and third-party applications to move data from legacy systems to Google BigQuery were: unreliable, time consuming and costly 2) Manual processes prohibited automation and meant business operated on an information delay.
Tech Solution:
The Data Integrity Suite – Data Integration Service for Google BigQuery
Objective:
Replicating data from mainframe to Kafka on AWS to power modern digital banking experience
Outcome(s):
1) enhanced customer experience for both internal teams (adoption of services across business and faster response times) and external customers (reduced customer churn and improved NPS score)
2) improved operational efficiency with a shorter response times and reduced manual / redundant system processing.
3) cost reductions with 80% reduction of MIPS usage and 6% overall cost reduction
Problem(s):
1) Larger transition in Citizens to using the cloud meant that they wanted their data to reside closer to cloud applications in AWS
2) mainframe presented roadblocks including network stability issues and prolonged efforts to move data to the cloud
3) high costs associated with mainframe usage
Tech Solution:
Connect CDC
Objective:
Create a centralized data warehouse to enable faster onboarding of new data sets and delivery of new applications.
Outcome(s):
1) Grow value-add business services from 50 to 300+ new business services helping to build new forms of revenue and offerings to customers
2) Enable over 20 downstream projects with real-time data delivery from mainframe to cloud ensuring all services have complete, accurate data to make decisions or enhance services.
Problem(s):
1) Integrating new platforms with existing mainframe application was extremely costly
2) Unique architectures and requirements made it hard to access data from other systems.
3) Cloud modernization strategy was incomplete/on hold due to a lack of real-time data integration between mainframe and cloud
Tech Solution:
The Data Integrity Suite – Data Integration Service
Capability Specific Discovery Questions
- What data sources are you working with? What business value do these provide? What business applications do they drive?
- What are your goals for evolving your IT architecture? What targets are you sending your data to? What are your use cases associated with these targets?
- What gaps are you experiencing with your current data architecture today? How do these gaps impact your ability to meet SLAs or drive innovation?
Continue the Story
… Driving confident data-driven decisions with data quality solutions that meet your unique business objectives helps reduce costs, boost revenue, increase compliance, and minimize risk. Precisely does this while minimizing business disruption and preventing costly downstream data and analytics issues.
Verify use cases that apply
- Discovery & Assessment: Discover what data exists, assess its level of quality, and proactively identify anomalies.
- Data Quality & Remediation: Automate data quality at scale through metadata driven routing, and remediation.
Customer Challenges
- Lack of insight and understanding into what data exists and can be trusted
- Inaccurate, inconsistent, and unverifiable business data that leads to lack of trust in data, poor decisions and reductions in revenue and increased costs.
- Difficulties improving the quality of critical data
- Increased risks due to erroneous analytics that impact business decisions.
Differentiators
- Broad and comprehensive data quality capabilities and expertise.
- Integrated capabilities identify and resolve data quality issues as well as find, understand, observe, and enrich data.
- World class geo addressing and reconciliation capabilities
- Extensive deployment options and data sources for data in motion or at rest.
Customer Stories
NZ Superfund
Lack of data trust and visibility into data quality and availability led to low confidence in investment decisions and inefficient resource use.
Health Plan of Ontario Pension Plan (HOOP), Aflac and Swedbank
Reduce risk and improve accuracy by reconciling and tracking data as it moves across the enterprise
Nationwide Builders Society and Porsche
Manage data quality in CRM and ERP applications including SAP and Salesforce.
PNC Bank & L’Occitane
Identify and resolve duplicates creating a 360 view of customer data to improve customer loyalty and identify risk
Capability Specific Discovery Questions
- How quickly can your teams find the data they need to make decisions?
- What processes do you have in place to evaluate data quality around key data you use for decision making?
- How confident are you in the accuracy, completeness, and quality of your data? Why?
- What do you do if your critical business data is not complete or accurate? How often does this happen?
- When data moves between systems and processes, how do you ensure no data is lost, duplicated, or transformed incorrectly?
Continue the Story
… Such as defending against the increasing sophistication and complexity of today’s data security and privacy threats. Implement solutions and processes that help your organization establish and automate effective, comprehensive, and auditable practices.
Customer Challenges
- Controlling access, maintaining data privacy, and monitoring behaviour.
- Ability to meet visibility to ever evolving regulatory requirements.
- Preventing malware threats which can lead to downtime, loss revenue, and increased costs.
Differentiators
- Comprehensive IBM i expertise that integrates the global enterprise security requirements with the IBM i specific administration workflows.
- Advanced MFA
- Business friendly user interface that allows IT and business users to understand and track data privacy requirements
Customer Stories
Experian
Data is governed for over 22,000 customers to ensure GDPR compliance, and over 4,500 business, and IT users can now track critical customer data across over 1.2M production tables of metadata.
Capability Specific Discovery Questions
- How do you prepare the employees in your organization who have responsibility for security and privacy?
- Tell me what your company has done to prevent ransomware attacks.
- Which data privacy concerns are top priority for your organization right now?
Continue the Story
… Delivering accuracy with verified, geocoded, and enrichment-ready addresses and power decision-making with location-based context to improve resource allocation, enhanced customer experiences, and a more sustainable future.
Customer Challenges
- Poor addressing leads to late and failed deliveries, incorrect taxes collected and an inability to leverage location data for process improvement.
- Slow to recognize market trends, making it hard to recognize what is connecting with customers today or anticipate their needs.
Differentiators
- Combination of hyper-accurate industry-leading global geocoding and enterprise location intelligence.
- Business-friendly spatial analytics equipping users with context not found in spreadsheets to boost customers satisfaction and drive new business.
- Easy enrichment of addresses with valuable context using a PreciselyID.
Customer Stories
Multinational retail corporation – Walmart
Accurate tax calculations preventing unnecessary tax overcharges and potential penalties
Global Outdoor Product Manufacturer – YETI
Improved overall brand insight across major sales channels
One of largest U.S. commercial property casualty insurance companies – Travellers
- Travelers can run 1 million geocodes in
- seven minutes and 50 concurrent real-time geocodes in
- under 200milliseconds. This is more than twice as fast as
- the insurer’s legacy systems
DoorDash
- Delivery failures reduced revenue and growth
- Inefficient routes delayed drivers and orders
- Drivers struggled to find addresses quickly
- Competitive risk was increased due to lost revenue
- Delays hurt customer satisfaction and retention
- With Precisely they were able to improve delivery success resulting in higher tips for delivery personnel and increased customer satisfaction.
- It was esitimated that they would save $65 million in revenue from failed deliveries
Freddie Mac
- Undergoing a strategic cloud modernization project with AWS and needed a way to accelerate address data processing while also integrating their legacy systems with new cloud infrastructure.
- Precisely provided Spatial APIs, Geo Addressing APIs, and Flood Risk Data
- Were able to decrease costs through elimination of manual data processing, optimized cloud resource utilization, and minimized data movement.
Capability Specific Discovery Questions
- Explain to me where you know addresses or location data is being leveraged within your processes.
- What are the teams/departments that are impacted with the address/location data?
- What type of addressing are you working with today?
- What is the cost of getting an address wrong?
- How do you add context to address data? How do you make this context available to all users within your organization?
Continue the Story
… Poor quality and inconsistent master data when siloed across multiple systems can be overwhelming. However, the pains of fragmented, ineffective data can be avoided with a Master Data Management (MDM) solution.
Customer Challenges
- Lack of master data accuracy and consistency across data silos.
- Inefficient customer relationship management due to lacking a 360-degree view of your customer; missing cross sell and growth opportunities.
- Increased risk exposure due to inaccurate and inconsistent master data across silos, undermining accurate risk management.
Differentiators
- Business friendly with a configure, not code approach.
- Multi-domain MDM promotes cross-domain intelligence and increases adoption across teams
- Open and extensible and built for scale, security, and performance.
- World class geo-addressing capabilities.
Customer Stories
Fender
Single source of truth to manage product, pricing, release packages, and customer master data across global requirements.
Acushnet Company (Titleist, FJ, etc.)
System of record for product and customer master data, verifying addresses with Geo Addressing capabilities from Data Integrity Suite, and automating SAP data processes.
Capability Specific Discovery Questions
- How is your organization currently managing and maintaining master data across different lines of business?
- How do you make sure your master data (e.g. product variation details) are synchronized across your internal systems and syndicated downstream with partners?
- How are you ensuring that the addresses in your system are accurate and not causing unnecessary expenses and mistakes?
Continue the Story
… The journey to data integrity starts with automating & streamlining processes for creating the highest quality data possible. Enable scalability by implementing solutions to ensure that the quality remains when you make changes or updates to that data.
Customer Challenges
- Slow, error prone and manual SAP data entry leading to poor data quality & governance.
- Steep learning curve requiring system expertise at all levels which causes a rigid and inflexible business.
- Poor audit process increases business risk.
Differentiators
- 20+ years domain experience.
- Low-code/No-code resulting in minimal IT engagement needed.
- Business user focussed with flexibility to choose interface for automating SAP master data.
- Scalability across SAP landscape and connectivity through APIs
Customer Stories
Energy Drink Manufacturer
- Excel-based data management process became a major bottle neck for their SAP ERP system.
- Reduced time to market by between 50% and 75%.
Dorman
- Material data changes manually would take about 60 hours per 100 materials and cost $4.5k due hiring & training.
- Now takes about 5 hours with resulting in a 90% savings in both time and costs. Roughly $500k in the first year.
Capability Specific Discovery Questions
- What SAP version are you running?
- How do you handle workflows and approvals for SAP processes?
- How do you create and manage SAP master data in complex, data-intensive processes?
- What tools do you use for mass data maintenance/data migration scenarios?
Continue the Story
… Every customer communication created by an organization begins with data. Precisely offers a simple solution to help teams leverage data to improve customer experiences, deliver faster services, and drive more customer spending.
Customer Challenges
- Slow to consolidate and analyze customer data efficiently.
- Slow to make template communication updates due to an IT dependency.
- Struggle to have visibility and governance in communication processes.
- Lack of real-time capabilities results in slower service and a less personalized customer experience.
- Poor data quality limits data-driven personalization and the ability to deliver high-quality customer experiences.
Differentiators
- Fully integrated end-to-end Customer Communications Platform
- 300+ people and 15+ years of migration experience and knowledge
- A simple SaaS interface for everyday business users to create and update communications.
- Hosted Managed Service offering takes care of the complexities of updates and day-to-day management for the client.
Customer Stories
Blue Shield of California
- Problem: Providing health plan information in a format people can easily absorb is an ongoing challenge for this insurer.
- Result: After watching the personalized, interactive video, 73 percent of viewers indicated that they are likely to choose a Blue Shield plan.
A Fortune 500 Financial Services Company
- Problem: A complex siloed legacy environment requiring extensive IT involvement for each change request.
- Result: Consolidated over 34 million communications annually into a single system, saving $12 million on 4,000 non-IT changes each year.
Top 5 Online Bank
- Problem: Changes to customer communications were too costly and time-consuming
- Result: Reduced time needed to make a communication change by 98%, from 140 days to 1-3 days
Capability Specific Discovery Questions
- How quickly can your business team implement changes to customer communications? What impact would it have if IT roadblocks were minimized?
- How empowered are your business users in making content or communication changes without heavy reliance on IT support?
- What goals do you have for improving customer engagement through more dynamic or personalized communications?
- How well does your current system integrate with other customer data platforms to provide a holistic view of each customer?
- How does your current communication process support your broader customer experience or digital transformation goals?
Continue the Story
…Precisely Strategic Services provides end-to-end expertise—from establishing AI-ready data governance to optimizing cloud and SAP migrations and advancing analytics—guiding businesses from strategy to implementation to full enablement with clear and actionable roadmaps
Customer Challenges
- We struggle to understand how to begin or gain momentum on our AI, analytics, or governance initiatives.
- We lack a clear definition of success and best practices for AI, analytics, and governance initiatives.
- We face challenges in ensuring that our AI, analytics, or governance initiatives are directly tied to measurable business outcomes and value.
Differentiators
- End-to-end in-house services (strategy, implementation, and enablement)
- We are the only company that offers software, data, and data strategy consulting services
- Our team of former CDOs and senior executives brings 25+ years of hands-on experience leading successful data initiatives, including SAP. We’ve faced the same challenges, learned from the mistakes of complex data transformations, and are ready to share those lessons to help you avoid pitfalls and accelerate success.
Customer Stories
Northwest Bank
- Problem: Needed trusted data for compliance and revenue generation
- Result: Leveraged our consulting to enable their data to be collected, managed and communicated – meaning they could now catalog the data in a way that helped identify the most critical data in need of attention.
Vantage Towers
- Problem: Had a lot of mergers and acquisitions which resulted in fragmented systems. Financial systems did not have the governance and quality they needed to track payments.
- Result: Leveraged our consulting and implementation teams to optimize financial expense management and increased agility with timely reports.
NZSUPERFUND
- Problem: Wanted to understand what data was available and the quality of it
- Result: Leveraged our data consulting team to increase trust in the quality of their data through pro-active profiling and data governance across the organization.
Capability-Specific Discovery Questions
- Can you walk me through your organization’s experience with implementing successful AI, data analytics, or governance programs? What lessons or best practices have you gained so far?
- What strategies do you have in place for governing your data in an AI-driven environment?
- How would you describe your team’s expertise in implementing AI programs? Are there any areas where you feel additional support or skills are needed to achieve your goals?