The rise of artificial intelligence is forcing companies to take a look at their data strategies, realizing that to enable data-driven projects you need correct, consistent and well-managed data. While AI is the goal post of the future, there is much to be desired in making the digital and data landscape at a company fully functional.
Unifying data across the organization provides an opportunity to remove both technical and organizational silos and enable better business outcomes, although achieving this can be a challenge.
Enterprise architects have long struggled with managing the digital journeys between various systems holding similar data, like Customer Relationship Management (CRMs), Customer Data Platforms (CDPs), Master Data Management platforms (MDMs).
Data that has traditionally been kept separate due to security concerns, like Identity and Access Management (IAM) data is a major part of the silo challenge. If you pull the data out from an IAM system, how do you ensure appropriate protection is applied to the various data points (i.e. personal identity information should be handled differently from anonymized behavioral data)? Business data can provide helpful context to IAM data, but how can you ingest and leverage it in an IAM system that doesn’t offer data management tooling, or contextualized identity?
This is a tooling gap that many try to solve with workarounds, like DIY. The challenge with this approach is it often becomes too much to manage, the data is static and the logic brittle. This quickly becomes unsustainable and unscalable.
But there is another way, one that can enhance the performative actions of IAM, while going much further and presenting real value to the business and end user.
For IAM, the ultimate goal should be total interoperability of the identity fabric, where a unified and holistic view of the customer is the starting point. Bridging the gap of data silos across the organization with an identity-first mentality provides a foundation of trust for solution creation that keeps customer experience at the core.
From an identity perspective, unifying business and identity data means you can leverage more information as ‘context’ for authorization decisions. This allows much more complexity and flexibility to be built into access policies. It also means you can leverage a unified customer view in your analytics and recommendations, along with enabling new products and seamless customer experiences.
For example, we are working with a client who wanted to enable faster time to market and deliver more thoughtful customer journeys, however they were hampered by the limits of their current tooling and inflexible DIY access control.
This requires a centralized data model to unite their products and services and allow them to externalize authorization at scale.
With IndyKite’s solution, all authorization decisions could be externalized from the applications for centralized granular management. This results in simpler management while also enabling much more intelligent and complex access decisions.
By unifying identity data (of people, systems, APIs and digital products) with business data, the customer could then leverage a contextualized view of each data set and identity.
Knowledge Based Access Control (KBAC), enables you to design authorization protocols to support complex use cases, including delegated authorization. This means you can better manage your partner network and enable more intelligent decisions at scale.
With IndyKite’s solution, the company could achieve growth, while driving better user experiences for its end customers and partners.
To learn more, download the Whitepaper: Improving IAM capabilities with Identity Data Management.