Tag Archive for: Stedin

Handling Redress and Remediation

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Redress and Remediation

No organization wants to move into a redress and remediation process. But, once you do, time is of the essence. Launching a redress investigation can happen suddenly. In other cases, it can involve slower planning. In either case, you suddenly have very different needs for organizational data compared to business-as-usual processes. In some cases, you might even need access to data that’s normally stored in the dark or in low-priority servers, which completely changes how your organization is able to access that data.

Redress and Remediation Processes are High Priority

If you’re facing the need to redress, remediate, or provide compensation, you likely have pressing reasons to do so. For example, your organization may be facing dwindling customer satisfaction, supplier de-listing, legal action, regulatory action, or damage to your organization’s reputation.

Redress and remediation processes bring individual case and file details to the forefront. Resolving those details is of high importance. However, without an immediate overview or a way to create high-quality comparisons of those individual or group cases quickly and efficiently, little can be done. For example, you first must manually review to see which cases require redress. And, deciding on what redress, remediation, or compensation should apply will remain difficult. Without those overviews, you could be providing too much or too little compensation.

Resolving this means making data a central part of the process. You must implement processes to direct redress and remediation actions. You also have to keep regulatory stakeholders informed enough so they do not escalate or start proceedings against you.

You Have to Act Fast, but Systems Aren’t Designed for Redress Processes

The default response to a redress & remediation process is to put people to work. Unfortunately, many of those people are called in ad-hoc, without the information and data they need to act upon.

Getting started means creating in-depth overviews of each case, with enough context from similar cases to guide decisions. Putting that into a control framework allows people to get started, while avoiding the risk of overcompensating individual cases or approving fraudulent claims.

Yet, making that shift of switching data management from everyday operations to a full investigation of minute data is not something that IT systems and support is normally designed for. Instead, you must combine data in new ways, to resolve individual cases quickly and fairly. That’s especially true when your cases demand bulk data access and processing, as remediation cases do. Remediation never starts out at a trickle of cases, you always need to address all of them, all at once. The level at which you can handle that bulk data will impact how much damage you can mitigate, how much work and rework is necessary, and how quickly you can finalize the project to the satisfaction of customers, internal and external stakeholders, and regulatory or legal stakeholders.

External Organizations Can’t Work Without Data

Large organizations often rely on third parties, whether specialized service providers, lawyers, consultants, or subject matter experts, to help manage these processes. Often, these include data and IT services as well. However, those consultants still need access to data, which your own IT systems must supply. Further, when you bring in consultants for IT design and implementations, their aim is to provide and build efficient solutions and applications – usually with the goal of running and supporting daily processes inside the organization.

Redress Demands Scaling Up Data-Handling Capabilities

Redress and remediation situations demand support in a very different way. You have to greatly enhance your capacity to manage data. Think of an airplane during an emergency landing. People don’t exit the plane in an orderly fashion using the stairs. Instead, they use emergency slideways, which greatly increase the capacity to empty the plane quickly whilst people arrive safely on the ground.

You cannot afford to lose time to prepare data or build up IT solutions for support during redress and remediation. Ad-hoc tools with query writing and spreadsheets often don’t help either. Instead, they can add to the confusion and make problems bigger, allowing individual cases to slip through the cracks.

If you need an immediate solution to remediation and redress processes, Synerscope is here to help. Our tooling installs quickly onto your Azure tenant, with data kept under your governance, so you can quickly sort, label, and review cases with the microscopic level of detail needed to ensure proper handling. And, with no changes in governance, you can implement the solution quickly and get your redress and remediation program running.

Customer Case: Stedin: MDM remediation

Is Your Organization Prepared to Manage Dark Data?

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The Business Value of Mining Dark Data in Azure Infrastructure

As organizations accelerate the pace of digital transformations, most are moving to the cloud. In 2019, 91% of organizations had at least one cloud service. But, 98% of organizations still maintain on-premises servers, often on legacy infrastructure and systems. At the same time, moving to the cloud is a given for organizations wanting to take advantage of new tools, dashboards, and data management. The global pandemic has created a prime opportunity for many to make that shift. That also means shifting data from old infrastructure to new. For most, it means analyzing, processing, and dealing with massive quantities of “Dark data”.

Most importantly, that dark data is considerable. In 2019, Satya Nadella discussed Microsoft’s shift towards a new, future-friendly Microsoft Azure. In it, he explained that 90% of all data had been created in the last 2 years.  Yet, more than 73% of total data had not yet been analyzed. This includes data collected from customers as well as that generated by knowledge workers with EUC (End-user computing, such as MSFT Office, email, and a host of other applications. As a result, the process of big data creation has only accelerated and (unfortunately) more dark data exists now than ever before.

As organizations make the shift to the cloud, move away from legacy infrastructure and towards microservices with Azure, now is the time to unpack dark data.

Satya Nadella discusses Microsoft’s shift towards a new, future-friendly Microsoft Azure

Dealing with (Dark) Data

The specter of dark data has haunted large organizations for more than a decade. The simple fact of having websites, self-service, online tooling, and digital logs means data accumulates. Whether that’s automatically collected from analytics and programs, stored by employees who then leave the company, or part of valuable business assets that are tucked away as they are replaced – dark data exists. Most companies have no real way of knowing what they have, whether it’s valuable, or even whether they’re legally allowed to delete it. Retaining dark data is primarily about compliance. Yet, storing data for compliance-only purposes means incurring expenses and risks without deriving any real value. And simply shifting dark data to cloud storage means incurring huge costs for the future organization – when dark data will have grown to even more unmanageable proportions.

Driving Value with Dark Data

Dark data is expensive, difficult to store, and difficult to migrate as you move from on-premises to cloud-hosted infrastructure. But it doesn’t have to be that way. If you know what data you have, you can set it into scope, delete data you no longer need, and properly manage what you do need. While you’ll never use dark data on a daily, weekly, or even monthly basis – it can drive considerable value, while preventing regulatory issues that might arise if you fail to unlock that data.

  • Large-scale asset replacement can result in requiring decades-old data stored on legacy systems.
  • GDPR and other regulations may require showing total data assets, which means unlocking dark data to pass compliance requirements
  • Performing proper trend analysis means utilizing the full extent of past data alongside present data and future predictions.

Dark Data is a Business Problem

As your organization shifts to the cloud, it can be tempting to leave the “problem” of dark data to IT staff. Here, the choice will often be to discard or shift it to storage without analysis. But dark data is not an IT problem (although IT should have a stake in determining storage and risk management). Instead, dark data represents real business opportunities, risks, and regulatory compliance. It influences trend and performance analysis, it influences business operations, and it can represent significant value.

For example, when Stedin, a Dutch utility company serving more than 2 million homes, was obligated to install 2 million smart meters within 36 months, they turned to dark data. Their existing system, which utilized current asset records in an ERP was only enabling 85% accuracy on “first time right” quotes for engineer visits. The result was millions in avoidable resource costs and significant customer dissatisfaction. With Synerscope’s help, Stedin was able to analyze historical data from 11 different sources – creating a complete picture of resources and creating a situational dashboard covering more than 70% of target clients. The result was an increase to a 99.8% first time right quote – saving millions and helping Stedin to complete the project within deadline.

Synerscope delivers the tools and expertise to assess, archive, and tag archived data – transforming dark data from across siloed back-ends and applications into manageable and useable assets in the Azure cloud. This, in turn, gives business managers the tools to decide which data is relevant and valuable, which can be discarded, and which must be retained for compliance purposes.

If you’d like to know more, feel free to contact us to start a discussion around your dark data.