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Manish Sood, CEO & Founder, Reltio
Apple CEO Tim Cook’s call for a U.S. privacy law, similar to GDPR (General Data Protection Regulation), is appropriate and timely. Five years ago this initiative would have been too big of a burden for companies because customer data is siloed throughout organizations in dozens or hundreds of separate systems. But today modern data management solutions that include technologies like machine learning empower organizations to implement data governance and privacy initiatives at scale, and are an essential part of their overall Customer 360 data strategy.
GDPR has irreversibly changed the landscape for single customer view data projects for companies doing business in Europe. And there are lessons we can learn from businesses that have gone before us. Early efforts to comply with data mandates at the application level have come up short. Upholding GDPR principles, as companies have quickly realized, requires an enterprise data layer approach to PII (Personal Identifiable Information).
Virtually all companies have customer data scattered across multiple networks and lines of business — the only way to manage this data sprawl so that customer data privacy compliance is assured is to discover, organize and control all customer data from internal, external and third-party sources. If that sounds like a tall order, the good news is that we at Reltio have already developed and implemented best practices that include the essential ingredients for ensuring customer data privacy for some of the largest global enterprises by:
Identifying all systems managing customer data
Blending different types of data
Understanding data ownership
Identifying data shared outside the organization
Maintaining data lineage across all customer attributes
Managing different types of consent, and their sources
Providing customers a way to make data-related requests
Deploying processes for required data access, change and deletion
Implementing a mechanism in place for timely reporting of a data breach
Whether it’s correlating omni-channel transactions to customer master records and understanding, to determining how each customer is related to other members of a particular household, to whether those disparate household members have consented to their data being used and for what purpose. Maintaining data lineage to data sources and tracking to downstream applications so we know from where a customer profile attribute originated and which applications are using it is critical. This is the power of technology that enterprises already have to ensure customers are protected under the right to be forgotten stipulation. (As an aside, the right to be forgotten is a bit of a misnomer. The regulation actually stipulates that a company is required to retain evidence that they ‘forgot’ a customer. Make sure you pick a vendor who understands these nuances or your efforts may be undermined.)
Under GDPR, individuals are entitled to data erasure, which means that at their request, all traces of their information must be purged, including legacy transaction data that might reside in activity logs. In sum, this mandates a comprehensive customer profile with a 360-degree view that can accommodate data-change requests and the ability to generate privacy compliance reports fast.
Organizing data with a modern data management platform for growth strategies like new revenue models, improved customer experience, or other initiatives results in clean, reliable data with built-in customer data privacy compliance.
A comprehensive customer-centric data management strategy that delivers data privacy capabilities is built on four pillars:
Consolidated profiles: Organizations need the ability to collate all data from internal, external, third-party and social sources. At the same time, they must have the power to trace and maintain data lineage across all attributes. This sweeping level of visibility is invaluable in the event of a data breach.
Managing relationships: Graph technologies play a unique role here — they offer a deeper and more accessible understanding of relationships between stores, locations, channels and types of consent. It also helps to trace the adult consent for capturing the data of a minor.
Data change requests: This is a critical requirement for GDPR compliance, and companies need to step up. Built-in workflows in the systems used should accommodate all customer data change requests, deletion requests, review requests and more.
Data as a Service with traceability: Drawing from third-party sources is a major benefit, but GDPR compliance requires tracking which attributes came from where.
Those that view a U.S. privacy law as a regulatory burden rather than an opportunity have not yet internalized what it means to be a customer-driven company. Your customers’ privacy is already table stakes today and is part of your responsibility as you serve them. Compliance towards protecting customers’ privacy is a journey not a destination – get the right platform in place today so you can meet any regulation or concern that they might have. You’ll find that it will improve your brand, and customer loyalty, and that’s just good business.
I’m proud that Reltio has been a pioneer in empathizing, understanding, anticipating and embracing customer privacy concerns, and that we’ve embedded product capabilities into our Reltio Customer 360 solution. I completely agree with Tim Cook’s call for a similar U.S Privacy law and as Reltio customers can attest they are already ahead of the game, with Reltio governing their sensitive customer data at scale throughout their organization using master data management, graph, and machine learning technologies.
Manish Sood, CEO & Founder, Reltio
Last week we saw some exciting announcements on the subject of Customer 360 and customer engagement. First Adobe, Microsoft, SAP and announced a new partnership: the Open Data Initiative, the intention to create a single data model for consumer data that is then portable between platforms. Then Salesforce announced Customer 360 at Dreamforce 18, to help brands identify who their customers are and how they previously interacted with them. The single customer 360 ID will enable companies to access customer information through Salesforce’s various applications including Sales Cloud, Service Cloud, Marketing Cloud, and Commerce Cloud.
The announcement is great news for the industry, and I’m excited to share today that Reltio will be supporting both initiatives. This means that our customers, who are already in production using Reltio Cloud for Customer 360, as well as any future customers and partners, will be able to use Reltio to take full advantage as both initiatives evolve while benefiting from significant additional capabilities.
Standardizing on a common data model, and having a single Customer 360 ID is important, but such efforts have historically been limiting. Common IDs and tight coupling of apps can solve some immediate problems, could provide a quick fix for small organizations but in the long run, can create new islands of data that can create challenges for larger enterprises. Reltio will help both initiatives by continuously unifying and organizing all data within their respective models while making it universally accessible for collaboration and consumption across the enterprise. Our philosophy has always been that standalone customer profile data reconciliation is insufficient without the benefit of understanding relationships across more than just the customer domain. Unlocking the value in relationships across multiple domains such as customers, households, stores, locations, products, parts, suppliers is essential to a true Customer 360, and Reltio delivers this at an enterprise scale.
The Open Data Initiative announcement mentions a data model with over 50 different open source schemas stored in a data lake. These schemas require companies to stitch together the relationships across attributes, schemas, and profiles. Reltio helps this effort through logical metadata that combines all 50+ schemas into one unified canonical model and view of the customer data while ensuring continuous data quality that prevents a traditional data lake from turning into a data swamp.
We started Reltio on the idea that customer data will always be distributed across dozens of application sources with different formats; that companies will keep on adding new sources; that understanding relationships across all data types, not just customer profiles are important; that agility is key, and that future-proofing from changes in technology investments is critical. It’s the reason why we adopted a multi-cloud, multi-model data storage architecture, rather than an arguably easier approach of committing to a single NoSQL, RDBMS, or a graph database. For over seven years, we’ve been delivering on the promise of the complete customer 360-view, through a foundation of trusted, reliable data, powered by open, next-generation modern Master Data management (MDM). We’ve delivered this by not just creating a better MDM in the cloud, but creating a true 360-view that includes master data, relationships across all data entities and correlating omnichannel interactions, transactions. But we didn’t stop there. We architected a platform that brings together analytical insight and operational execution using advanced analytics and machine learning to continuously correlate insight, action, and outcomes in a closed-loop, to extract the maximum business value out of data.
Our customers – which include eight of the 10 largest life science companies, two of the top 10 cosmetics companies in the world, a global hotel and hospitality group, a U.S.-based healthcare insurer, one of the largest U.S.-based pet retailers, one of the largest mortgage providers – rely on Reltio for their digital transformation and customer engagement initiatives. From globally harmonizing customer 360-views across 140+ countries to bring together customer data from hundreds of millions of organizations, to real-time personalization, marketing segmentation of millions of consumers, Reltio continues to deliver on the promise of Customer 360.
Speed, performance, and scalability are key. Over 4.3 billion mission critical master profiles, representing well over 1 Petabyte of storage under management in Reltio Cloud, is being accessed by business teams globally to the tune of over 85 million real-time API calls per day. As these numbers are growing by the second, our multi-cloud platform supported on both AWS and GCP provides the elastic and scalable horsepower to meet demanding workloads, and the aggressive growth objectives of global enterprises. They look to their “Reltioed” data as the trusted source for their analytics and machine learning (ML) initiatives, compliance requirements such as GDPR, and next-generation customer engagement and experiences.
Reltio partners, including Salesforce, Mulesoft, IQVIA, AWS, GCP, Accenture, Cognizant, Wipro, ZS Associates, and Dun & Bradstreet, have all been part of successful Reltio for Customer 360 deployments, which bring together data across applications and sources in multiple Salesforce, Adobe, Microsoft, and SAP environments.
These are exciting times for enterprises looking to transform themselves and leapfrog the competition. But it’s not easy, with a shifting landscape of technology choices, continuously evolving regulations such as GDPR, CCPA (California Consumer Privacy Act), and the need to operate at scale most cost-effectively. To companies considering how the Salesforce and Open Data Initiative announcements might impact their plans, please reach out to us to learn more about our support of both initiatives, and how we can get you on a path to future-proofed Customer 360 in a matter of weeks. To our current customers who have placed their faith, and most importantly their critical customer data assets into Reltio, I’d like to say thank you, and assure you that the best is yet to come.
Ramon Chen, Chief Product Officer, Reltio
On May 25, 2018 GDPR (General Data Protection Regulation) went into effect. The primary objectives of the GDPR are to give control back to their EU citizens and residents over their personal data, to simplify the regulatory environment for international business, and to unify regulations within the European Union.
GDPR is relevant for any organization doing business with EU citizens, regardless of where the company is based. Personal data includes a wide range of personal identifiers, from addresses and public information, to social profiles, images, IP information, device IDs and medical and financial details.
Consumer personal data collected within your company is often distributed to multiple systems and organizations, resulting in duplication. Your organization may be considering master data management (MDM) solutions to address various data management needs including compliance challenges. Legacy MDM systems may comply with a small part of the regulation by managing profile data, but they also leave it to you to figure out how to manage the transaction and interaction information distributed across systems and channels.
Complying with GDPR should be part of your day-to-day operations. One philosophy is that a Modern Data Management platform should organically support the key elements of GDPR by managing your customer’s profile information, lineage and succession through your day-to-day data management activities.
RIGHT TO BE FORGOTTEN – GDPR guidelines require your organization to support your customer’s Right to be Forgotten and purge their records upon request. Your business will also need to support your customer’s request for a copy of their information in a portable format. Any GDPR solution needs to guarantee purging of all traces by customer entity type in support of data erasure, including the removal of any attributes and historical transactions made by individuals captured as part of their digital activities, which is outside of the scope of traditional legacy MDM tools.
CONSENT MANAGEMENT – Your company must also support a provision to produce any proof of consent provided by your customer on request, and a way for customers to withdraw the consent. Explicit consent is required before information is collected, and adult consent is mandatory when the collection of data involves children below the age of 16 years. Any solution that supports the management and maintenance of rights and consents must have the ability to capture and store consent types. Graph technology provides a great way to store relationships so you can easily capture and prove that an adult provided consent regarding the collection of information for a minor.
AUDIT & LINEAGE – The new GDPR legal framework requires your company to support the ability to demonstrate the deletion of your customer’s private information. built-in audit and data lineage to support accountability for your business to demonstrate compliance. Attributes must also traceable back through lineage to the internal and external data providers they came from. In the case of a change request, the request can be routed back to its original source.
While there are many tools being offered to meet GDPR and other regulatory requirements, companies should use a Modern Data Management platform that supports both offensive (e.g. improve operational efficiencies, deliver better customer experiences) data strategies, and has defensive (e.g. maintain compliance, reduce costs) data strategies built-in.
Facebook has stopped short of promising GDPR level data compliance for US users. If you are a US company, even if you have no EU data, you should consider implementing a Modern Data Management platform that gives you GDPR-ready capabilities. Imagine the branding and goodwill you’ll get with your customers when they realize that you are taking measures above and beyond (exceeding that of Facebook) to respect their privacy and data.
Finally it won’t take long for the US and rest of the world to catch up, the State of California recent enacted The California State Assembly’s passage today of the California Consumer Privacy Act (CCPA) which has many elements of GDPR. My article listed three very basic GDPR requirements, there are certainly many many more. Regardless of the solution or tool you put in place today you know that many more regulations are coming. A Modern Data Management platform does the heavy lifting for you today, and protects you into the future, allowing you to focus on your business.
Ankur Gupta, Sr. Product Marketing Manager, Reltio
A modern Master Data Management (MDM) Platform helps businesses manage data like leading digital companies, leveraging continuous data organization and recommended actions to measure and improve their operations. Here are the seven reasons why enterprises should invest in a modern MDM Platform to drive ongoing business value.
A leading PC & printer manufacturer & re-seller created a single global view of accounts. Reltio Cloud delivered an Account 360 solution to manage complex relationships and hierarchies among their business units, customers, and partners. It helped the client improve their territory alignment, multi-channel campaign execution, and field incentive compensation planning. Reltio has helped increase their data load performance by 577X and is expected to save them more than $12M over 5 years through improved IT and data management operations.
A top 5 global pharma reduced cost of ownership by $3.6 million per year, and improved user query response time by 10X. Reltio Cloud was deployed to replace the client’s 67 MDM on-premises instances with just 3 regional cloud tenants. It allowed them to execute multi-channel marketing campaigns and simplify capabilities for cross-market queries on healthcare providers (HCPs). With Reltio Cloud’s simple configurability and ease of use, the business teams were able to give its field sales reps the ability to submit updates through the Reltio UI via mobile phones, allowing them to contribute towards overall data quality.
A top used car retailer consolidated data from 155+ store systems in less than 15 weeks to drive omnichannel customer experience. Reltio Cloud supported a Consumer 360 solution, managing the client’s multi-domain data (customers, vehicle stores, accessories) in a holistic manner while integrating real-time predictive analytics with full visibility into all customer interactions. The Customer and Vehicle Master helped the client’s marketing team execute better targeted campaigns and allowed the merchandising department refine inventory acquisition targets based on more complex demand analysis.
A leading pet specialty retailer leveraged data to tackle Amazon Effect and transform into a customer-centric service company. Reltio Cloud delivered a Consumer 360 solution that supported a single view of pet parents across all the client’s brands, joint ventures, and multiple systems. Reltio’s unique approach to modeling relationships with graph technology, combined with big data science, enabled the client to unlock the critical intersections of interactions and information by creating a single repository of trusted and mastered pet parent profiles in real-time.
A leading health insurer created a single view of their members across multiple systems to execute a member-centric omnichannel strategy. Reltio Cloud enabled a Member 360 solution, providing visibility into the entire touch-point history for each member and optimizing member experience while meeting HIPAA compliance requirements. It helped the client do segmentation, targeting, and direct-to-consumer (DTC) campaigns with higher precision. With Reltio’s cloud-based platform, flexible modern data architecture, and agile deployment the client delivered lower TCO and quicker time to value for their IT, sales, and marketing teams.
An American diversified global insurer created a holistic view of their brokers for better segmentation, compensation elasticity and retention analysis, all in four weeks. Reltio Cloud for Account 360 helped the client create a single view of their brokers (firms and captive agents) for effective commission management. Reltio’s Self- Learning Graph capability enabled the client uncover relationships among brokers, distribution channels, products, employers and insured employees to identify top brokers and find upsell and cross-sell opportunities.
A global colocation provider ensured the ‘Right to be Forgotten” for their customer contacts with an implementation that took twelve weeks. Reltio Cloud for Account 360 helped the client create a single view of their enterprise customers with built-in audit, data lineage, and workflows. It ensured ongoing purging of all traces by customer entity type in support of data erasure, including the removal of any attribute, historical activities made by individuals and activity logs on the Reltio Platform. In addition, Reltio Cloud’s Self-Learning Graph enabled them to reveal relationships among people, products, locations, and consent types.
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Ramon Chen, Chief Product Officer, Reltio
Reltio’s inclusion in the The Forrester Wave™: Machine Learning Data Catalogs Q2 2018, by Michele Goetz with Gene Leganza, Elizabeth Hoberman, and Kara Hartig, Forrester Research, June 2018, sparked (pun intended) several questions. Such as why was Reltio included, how did we receive such strong marks, and why were we the only Master Data Management (MDM) vendor in the Wave?
The simple answer is that the Wave’s qualification criteria includes several key areas in which Reltio is naturally strong. As the only Master Data Management platform recognized in the Wave we believe our core MDM capabilities contributed to our strong showing. In fact, Reltio had already been included, together with 23 other excellent companies, in Forrester’s Now Tech: Machine Learning Data Catalogs, Q1 2018 report preceding the Wave.
That report outlined key 3 characteristics of Machine Learning Data Catalogs (MLDC):
Reltio is used by companies globally to define logical business schemas, capture and discover relationships through the Reltio Self-Learning Graph, suggest ongoing improvements, and to organize and bring siloed data together across the enterprise to meet their business objectives. This continuous reliable data foundation feeds better operational execution, predictive analytics, and sets them up to evolve towards a self-learning enterprise.
Reltio Cloud’s built-in data security and privacy, regulatory, life-cycle, and data quality policies coexist to adapt data for multiple uses through a powerful audit trail, and role based access to data. This is critical in the face of evolving compliance measures such as GDPR. Flexibility and agility to ensure that you can track not just where the data originated, but how it’s being used and the outcomes it generates, is a critical component of any forward looking ML strategy.
Reltio is particularly well suited to meet this requirement through frontline business user facing data-driven applications and workflow and collaboration capabilities that come OOTB with Reltio Cloud. It allows teams to submit comments, suggestions, filter and easily segment information through a UI that’s as easy to use as Facebook and LinkedIn.
Data science teams are then able to use Reltio IQ, with Apache Spark to run their algorithms without the pain associated with cleaning and onboarding data in separate environments. This is increasingly important as enterprises deploy machine learning systems, with data scientists requiring relevant, curated data sources to train algorithms to improve results.
As this video illustrates, the true value comes from being able to synchronize ML-algorithm derived IQ scores back into master profiles as aggregate attributes. Making them available for segmentation by marketing, sales, and even data stewards and compliance teams. Teams can then continuously reconcile results to recommendations in a closed loop to self-learn and improve outcomes.
We are tremendously proud and honored to have been included in the MLDC Wave as it reflects our core belief that machine learning cannot be used in isolation from the overall data organization and management needs of the business.
Whatever your desired outcome, MDM forms the backbone of high quality, reliable data which allows ML to thrive.
ML in turn provides unique capabilities to improve and increase the efficiency of data quality, and enterprise data organization operations. Like the graphic I selected for this post, they go hand in hand, and are interconnected across all points of the data continuum and life cycle.
Ankur Gupta, Sr. Product Marketing Manager, Reltio
Post May 25, 2018, per the General Data Protection Regulation (GDPR), companies with business ties to the European Union need to comply to GDPR standards. The cost of non-compliance is huge, but the regulation is meant to benefit individuals as well as businesses. Let’s look at what it can unlock for you and your brand if you approach it in the right way. What about being able to say that you are the safest enterprise in your marketplace when it comes to data? How about if you can not only reduce operational cost but can also create new revenue streams by being compliant to GDPR and other upcoming regulations?
When companies are taking steps to comply with GDPR, they are required to perform a ‘spring clean’ of their data, which can in turn lead to multiple efficiency gains. Organizing data improves the way firms carry out analytics and take business decisions. To comply with the regulation, companies must be able to illustrate the entire data flow – how data comes into the company; how they store and manage it; and how they treat it at end of life. This will encourage businesses to replace legacy systems by flexible cloud services to be more nimble and transparent especially when regulatory regime keeps evolving. In addition, most large enterprises have grown through M&A. Thus, they can look at GDPR as an opportunity to get rid of obsolete software and accelerate application retirement.
Companies can leverage GDPR to change the landscape from risk mitigation to improving their long-term competitive advantage. They can see early GDPR compliance as a competitive differentiator and position themselves as leaders of an emerging new normal. We trust those businesses who values our privacy beyond mere legal compliance. Thus, GDPR is an opportunity for businesses to get their data in order, get compliant and become consistently transparent with their customers. In a post-GDPR world, data sharing would be seen in the context of mutual respect and value exchange. It is an opportunity to re-connect your business with your current and potential customer base and start a new relationship based on mutual trust and responsible personalization.
The criticism that GDPR compliance might restrict innovations in AI ignores a subject’s right to privacy and consent. In fact, not being GDPR compliant would impose far more constraints on data collection and processing, slow down the ability to leverage innovations in AI and pay an opportunity cost such as market share losses in the future. Read this article for more details – Understanding GDPR and Its Impact on the Development of AI. In addition, in an era of data-driven innovation, business partners need to work together across the value chain. Data-driven innovation requires a clear understanding of the data to be collected and the reasons for collecting it. There are double opt-ins in such value chain: both partners need to be clear about what data they have about each other, and why. It’s very important that their data sharing practices are compliant with GDPR and other upcoming data regulations. As a first step to GDPR compliance, companies must define the scope of GDPR-relevant personal data that is collected, processed, and shared. Once a company identifies the scope of GDPR-relevant personal data, it should catalog all internal and external data sources that fall within this scope.
In the post-GDPR era, personal data protection will become a data strategy issue. To comply, businesses need to have solid data organization and data governance in place. The GDPR gives companies the opportunity to holistically re-assess all their data, not just personal data. Data defense is about minimizing regulatory risk and preventing theft. Data offense focuses on increasing revenue, profitability, and customer satisfaction. Strong regulation in an industry (e.g. financial services or health care) would move the company toward defense; strong competition for customers would shift it toward offense. The CDOs and the rest of the leadership should see GDPR as an opportunity to establish the appropriate trade-offs between defense and offense to support company’s overall strategy. Read this blog post for more details – Is Your Data Strategy Defensive or Offensive? Why Not Both?.
Data is a company’s most important asset, and it’s constantly growing. Taking mandated compliance and turning it into an opportunity to personalize, delight and exceed customer expectations would fuel innovation reliably and responsibly.
The “Healthcare & Life Sciences (HCLS)” track at Modern Data Management Summit 2018 (#DataDriven18) invited industry leaders who shared their thoughts on themes such as data-driven strategies to excel commercial operations in life sciences, collaborative data management and curation across global regions, account-centric approaches, compliance initiatives, and omnichannel engagement with patients.
The Healthcare and Life Sciences track this year included twelve sessions and panels supported by 20+ speakers. Here are some of the key highlights and takeaways from the sessions:
Jamie Yates, Master Data Management Leader, AstraZeneca along with Mona Rakibe, Director Product Management, Reltio presented on AstraZeneca’s “Customer Master Journey: From Global To Local”. Jamie discussed the best practices employed in the AstraZeneca Global Customer Master deployment and provided insights into how modern data management capabilities such as collaborative data management and curation across geographies helped them break functional silos and cross-enterprise boundaries, thus leading to sales effectiveness, data steward productivity and overall data quality. Read more.
Peter Bell and team from Eli Lilly participated in a panel on “Improving Digital Customer Experiences at Eli Lilly”. They talked about how they leveraged modern data management technology to get rid of duplicate customer identities and create an enterprise-wide customer profile across commercial and clinical investigation departments. This helped them not only identify high-value customers but also improve customer experience across various digital touchpoints. Moreover, connected digital omni-channel systems allowed them continuously improve products, processes, information, and patient outcomes, resulting in increased sales. Watch the full panel discussion.
John Hayes and team from Sanofi along with Kanthan Manickam from ZS Associates discussed about how life sciences landscape has changed dramatically over the last decade, requiring companies to change the way they think about customers and develop new go-to-market strategies and commercial capabilities. They talked about how Customer 360 built on top of the Self-learning Data Platform supported them with account-centric approaches, digital marketing, compliance initiatives, and ingesting non-traditional data sources. Read more.
Vincent Ciro, Executive Director, Commercial Intelligence, Allergan and William Gurney from IQVIA talked about how modern data management helped them deliver global insights. Allergan was tasked with modernizing and standardizing their global business intelligence (BI) reporting platform. With disparate systems across 36 countries and 3 regions, in addition to mastering customer data, they had to manage transactional data, generate insight, offer data on-demand and support 24×7 business operations. Allergan utilized modern data management capabilities to achieve this ambitious goal and the solution went live in 16 weeks! Watch the full video presentation.
Vivian Wu and Bernie Tucker from AbbVie participated on a panel “Multi-domain Enterprise Data Management at AbbVie“. They discussed the evolving data strategy at AbbVie, various data management use cases, and lessons learned along the way. They talked about how they leveraged Self-learning Graph capabilities to uncover and manage relationships between HCOs and HCPs to support their compliance and account management initiatives. Watch the full panel discussion.
Nirav Mehta, Senior Director, Enterprise Architecture – Medical Devices IT, Johnson & Johnson and Ram Chakravarti, Associate Partner, McKinsey & Company shared their perspectives on a large-scale data-centric digital transformation. They emphasized the strategic importance of getting the data house in order as poor data can derail any business strategy and digital transformation initiative.
Maria Perkins and team from Optum had a panel discussion on “Data Strategies to Optimize Health Services” where they discussed how healthcare providers are leveraging modern data management to meet changing customer expectations while improving the internal business processes. Read more.
Beata Puncevic, SVP Engineering and Chris Williams, Data Engineering Leader, Healthgrades shared their Consumer 360 journey and how they built a data platform to meet their business needs, evolve rapidly to offer diverse set of products, and operate at large scale. Using modern data management capabilities, they were able to integrate consumer data from disparate data sources and link unknown with known to uncover consumer journey. They created single view of patients and their households, providers, and hospitals to create new offerings such as Consumer Data As a Service, Provider Data As a Service, and Facility Data As a Service. Watch the full video presentation.
Dr. Uli Chettipally, Co-founder & CTO of CREST Network, Kaiser Permanente, Anshul Agarwal, Principal, ZS Associates, and David Rosner, Principal, Deloitte participated on a panel “Will the Rise of the Patient Follow the Rise of the Consumer?”. Patients today expect the same experience as they get from a retailer or a bank and want to be more involved in their care. They expect all relevant parties like providers, payers and pharma to collaborate and recommend the best treatment options. Changing business models, customer expectations and newer regulations necessitate the adoption of Self-learning Data Platform to meet ever-increasing patient expectations serve them better. Watch the full panel discussion.
John Wollman, Chief Innovation Officer, HighPoint Solutions presented on “Applying Advanced Analytics to Detect Medicaid Overpayment”. Pharmaceutical manufacturers often overpay state Medicaid agencies for purchases in the form of duplicate discounts. This session examined the pervasive problem of duplicate discounts and identified how AI/ML and MDM can work seamlessly to enable new and advanced types of analyses such as duplicate discount detection.
The Modern Data Management Summit, 2018 provided an opportunity for healthcare and life sciences (HCLS) companies to discuss the latest trends in data organization, AI/ML, and self-learning and how these trends impact evolving business needs. It also helped them witness how companies in other industries (such as CPG, Retail, Media & Entertainment etc) are leveraging modern data management to stay ahead of the game.
Look forward to seeing you at DataDriven19!
What an exciting data summit to be a part of. As Richie Etwaru, CDO of IQVIA put it, we are still having the intellectual hangover from the event. As a Diamond sponsor of the summit, it was a great pleasure for us at Reltio to welcome all attendees, sponsors, and speakers to what has proven to be the largest gathering of data management leaders and practitioners.
Held on February 26-27 2018 in San Francisco, the second annual summit had over 40 sessions and panels, 60 speakers, and 19 leading data management enterprises as sponsors. There was never a dull moment during the conference. This year there were three tracks – Modern Data Management, Healthcare & Life Sciences, and Artificial Intelligence and Machine learning. Tracks covered a wide range of top of the mind topics such as Master Data Management, Reference Data Management, Big Data, AI and Machine Learning, Advanced Analytics, Data as a Service, and Blockchain.
Presentations and demo sessions reviewed the most advanced solutions for Digital Transformation, Customer Experience, Consumer 360, Account 360, Supplier Management, Product Management, Data Monetization, and Compliance (GDPR, KYC.) Hundreds of senior IT and business executives from life sciences, healthcare, media & entertainment, hospitality, retail, financial services and technology corporations joined to witness and discussed the latest advancements in data management.
The highlight of the event included the introduction of the latest version of the Reltio Self-Learning Data Platform with Reltio CEO Manish Sood kicking off the conference by delivering the keynote address: The Self-Learning Enterprise Era. Learn more about Self-Learning Data Platform by reading this whitepaper. Michele Goetz, Forrester Research Principal Analyst reviewed how “Machine Learning Puts Data Front And Center For Business”, exploring why the technology must operate at the heart of a data strategy, not only at the edge, and detailing how enterprises are turning from data as an asset to data as a business.
Summit also recognized the smartest and most innovative IT and business professionals with The Data Genius Awards. The recipients have blazed the trail for their creative use of data for the benefit of their companies raising their Enterprise Data IQ every day through continuous Data Organization and Self-Learning.
It was not all work but plenty of fun as well! Attendees joined the evening reception and tried their luck at the casino night, keeping their commitment not to gamble with their data! Some quick snippets from the event are captured in this video.
Overall a great event with excellent sessions that offered new ways companies must think about their data to be competitive in the new digital economy. Companies are beginning their journey towards a Self-Learning Enterprise starting with the organization of data of all types and sources at scale to form a trusted data foundation. They are leveraging analytics for operational execution—simple business rules or machine learning algorithms tuned by data scientists—to deliver recommended actions and aspiring to become the Self-Learning Enterprise that measures the outcomes of those actions and use data in a continuous cycle of improvement.
Selected session recordings from the event will be available soon. Submit your request to access the session videos from the Summit here.
If you missed the event this year, watch this space and we will announce the next summit soon! See you at #DataDriven19
In 2017, we saw several of our top predictions come true. AI and analytics M&A vendor activity accelerated, while cloud and data security has gained further importance with the General Data Protection Regulation (GDPR) now in motion. How will data management evolve in 2018?
Here are a few predictions and perspectives from industry experts to learn from and be smarter this year:
The Promise of Artificial Intelligence (AI) and Machine Learning (ML) Continues on
There have been repeated predictions over the last couple of years touting a potential breakthrough in enterprise use of AI and ML. This year is no different as the potential benefits from adding some kind of intelligent AI/ML layer to software emboldens more organizations across industries to adopt these technologies.
Daniel Hong, VP Research Director at Forrester Research predicts that having a successful AI-driven customer service or sales program will depend on the processes that support a blended AI approach. Humans will play a critical role in the ongoing optimization of AI.
Enterprise data-driven applications with a Modern Data Management foundation can blend customer data into one place, so that marketing, e-commerce, customer service and sales teams can get visibility into their customers’ preferences, behaviors, product interests and channel choice.
ML and predictive analytics are leveraged to suggest next-best-actions for sending relevant and timely information to customers and finding opportunities for up-sell and cross-sell. Insights like churn propensity, life-time-value, preferences and abandonment rates can be delivered to relevant teams, along with recommended actions that allow them to capitalize on this information.
GDPR will be Top of Mind for Many Organizations
Bart Willemsen, Research Director at Gartner predicts that by the end of 2018, more than 50 percent of companies affected by the GDPR will not be in full compliance with its requirements.
Effective May 25, 2018, the European General Data Protection Regulation (GDPR) will force organizations to meet a standard of managing data that many won’t be able to fulfill. They must evaluate how they’re collecting, storing, updating, and purging customer data across all functional areas and operational applications, to support “the right to be forgotten.” And they must make sure they continue to have valid consent to engage with the customer and capture their data.
Meeting regulations such as GDPR often comes at a high price of doing business, not just for European companies, but multinational corporations in an increasingly global landscape. Companies seeking quick fixes often end up licensing specialized technology to meet such regulations, while others resign themselves to paying fines that may be levied, as they determine that the cost to fix their data outweighs the penalties that might be incurred.
With security and data breaches also making high-profile headlines in 2017, it’s become an increasingly tough environment in which to do business, as the very data that companies have collected in the hopes of executing offensive data-driven strategies, weighs on them heavily, crushing their ability to be agile.
Customer-obsessed, Data-driven Retailers will Thrive
Sucharita Kodali and Brendan Witcher from Forrester Research predict that retail will grow.
“Bolstered by strong consumer confidence, not only will total US retail sales grow, but digital will impact more than half of this $4 trillion market. But retailers will need to be nimble and innovative to grow, right-sizing their store networks and real estate footprints and testing everything from Target-style flexible small-scale formats to service stores (think Nordstrom Local) and urban distribution centers – and more.”
With the Cloud Infrastructure as a Service (IaaS) wars heating up, players such as Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure continue to attempt to outdo each other on all vectors including capabilities, price, and service.
To avoid being “Amazoned,” some retailers have even adopted a non-AWS Cloud policy. For most, however, it’s about efficiency and cost. Multi-cloud means choice and the opportunity to leverage the best technology for the business challenges they face.
Today’s Modern Data Management PaaS are naturally multi-cloud, seamlessly keeping up with the best components and services that solve business problems. Acting as technology portfolio managers for large and small companies who want to focus on nimble and agile business execution, these platforms are democratizing the notion of multi-cloud for everyone’s benefit.
The Deck will be Cleared for Accelerated Enterprise Digital Transformation
Joe Pucciarelli, Serge Findling and Michael Jennett from IDC predicts by 2019, 60% of CIOs will complete infrastructure and application re-platforming using cloud, mobile, and DevOps, clearing the deck for accelerated enterprise digital transformation.
The business landscape is changing like never before. New revenue models, new competition, newer regulations and exceeding customer expectations are forcing organizations to rethink how they do business.
Digital transformation is one of the key initiatives for many organizations looking for ways to leverage digital technologies, become agile, more productive and above all, provide a connected digital experience for their customers. For digital transformation to succeed, a solid data management foundation is a must.
Today’s Modern Data Management Platforms as a Service (PaaS) seamlessly powers data-driven applications, which are both analytical and operational, delivering contextual, goal-based insights and actions, which are specific and measurable, allowing outcomes to be correlated, leading to that Return on Investment (ROI) Holy Grail, and forming a foundation for machine learning to drive continuous improvement. As an added bonus, multi-tenant Modern Data Management PaaS in the Cloud, will also begin to provide industry comparables, so companies can finally understand how they rank relative to their peers.
Digital will Disrupt Siloed Healthcare Ecosystems
Kate McCarthy and Alex Kramer from Forrester Research predict that digital will disrupt siloed healthcare ecosystems in 2018.
“For those who have alarm fatigue from all the times disruption has been predicted for our industry, but never came to fruition, this time is different. All the drivers for change remain –cost, quality, regulatory — but unlike times past, the disruption is already underway … And as cool as this is on its own, it is the proof the industry needed to confidently step forward and build digital experiences to engage our customers the way other industries have for more than a decade.”
With the emergence of IDNs, ACOs and MCOs, the approach to healthcare is evolving. The focus is on overall well-being and quality of life, rather than a one-time treatment. This requires a new patient-centric approach, complete understanding of the patient’s needs, behaviors and preferences, and focus on building long-term relationships.
In this changing healthcare environment, a modern approach to data management that enables complete understanding of patients, physicians and other partners across all clinics and facilities, while guaranteeing HIPAA compliance is necessary.
Whatever the industry or business need, most enterprises will need to first focus on IA (Information Augmentation): getting their data organized in a manner that ensures it can be reconciled, refined and related, to uncover relevant insights that support efficient business execution across all departments, while addressing the burden of regulatory compliance.
Ramon Chen, Chief Product Officer, Reltio
10. Gobble up your data, but make sure it’s more than just well done and reliable
9. Visualize your data, but know it’s just dressing without recommended actions
8. Pluck out relevant insights using a feast of machine learning algorithms, from an open ecosystem
7. Remember there’s always more than meats the pie (chart)
6. Prevent big data indigestion using a multi-model, polyglot storage strategy
5. Expect compliance to be handled by your platform, GDPR is the gravy not the main course
4. Don’t just save dessert room for data-driven applications, they’re part of a complete meal
3. Go multi-cloud, it will ensure every meal is always less filling and tastes great
2. Stop tryptophan-ing over leftover legacy MDM tools, you don’t have the space or time
1. Give thanks to your teams who are data-driven and helping your company be right faster.
If not send them on a field trip to learn how.
Happy Thanksgiving to you and your family!