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Data

IT Service Management (ITSM) Challenges

There are many challenges/issues commonly faced within ITSM. Some of these may not even seem to be a problem until you can see the impact they could be having. More often than not, the root cause of these concerns will be data quality based.

ITSM Challenges

So how are ITSM challenges linked to data?

  • ITSM covers activities that are performed by an organisation to plan, design, deliver, operate and control IT services offered to other departments. They are usually the central ‘go to’ point for queries. There is an expectation that this area will be able to provide the information being asked for.
  • Asset data fundamentally underpins multiple ITSM activities and decision-making actions but doesn’t fully determine the level of asset data management needed. If the data is either not accurate or unavailable, ITSM activities are often impacted. Such data is of little use in its raw format; held in the source repositories, it must be made to work for the organisation and provide intelligent information with supportive reporting.
  • There is fundamentally a reliance on accurate, comprehensive asset data to achieve this. Where data is captured and stored there must be adequate processes in place to ensure it is correct. A regular activity of data reconciliation and cleaning should be in place to keep errors to a minimum.

For advice on what data to capture, how to improve your data quality and the processes needed to support ITSM, please visit Data Hub or email your enquiry to info@itamsolutions.com.

The Importance of Managing Data Quality Effectively for IT Asset Management

Let’s face it, there are many challenges and hurdles to jump over when it comes to setting up, maintaining and maturing the IT Asset Management (ITAM) service within an organisation.

What causes the biggest issue? Is it the lack of resources, processes, policies or centralised technology?

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For further information on managing IT Asset Data Quality please visit: Data Hub

Case Study: The Golden Record

Inaccurate IT asset data can affect multiple areas of the organisation such as outsourcer billing optimisation, CMDB and ITSM controls, licence management optimisation, security and far more.

For organisations to have complete confidence in their IT asset data we recommend creating a ‘Golden Record’.

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For further information on managing IT Asset Data Quality please visit: Data Hub

Case Study: Outsourcer Billing Optimisation

If IT asset data is not accurate then it could mean that assets are not being correctly billed for. The IT asset data used for billing will also support a multitude of other functions within the business, such as refresh, service desk, procurement and software asset management/audits. It is therefore vital that there is complete confidence that the data upon which the billing is based is true and accurate.

Using a real life case study we explore the issues caused by inaccurate IT asset data within the context of Outsourcer Billing.

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For further information on managing IT Asset Data Quality please visit: Data Hub

Case Study: Configuration Management Optimisation

Find out how Configuration Management can be optimised and the benefits that can be realised by improving the overall accuracy of IT asset data.

Using a real life case study we explore the issues caused by inaccurate IT asset data within the context of Configuration Management.

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For further information on managing IT Asset Data Quality please visit: Data Hub

What is an ELP?

ELP stands for Effective Licence Position and is related to a specific software vendor or product.

Being able to create an ELP is fundamental to keeping on top of your product compliance for audit defence and to support ongoing SAM activities such as optimisation and cost control.

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The Importance of Data to your SAM Service Line

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Is your software asset data providing you with the right information to help you make informed decisions for your business?

In this post, ITAMS’ consultants define “data”, what data elements support IT asset management (ITAM) and what the data model comprises of for effective licence and compliance management.

Accurate, complete, and timely data is essential for reliable licence and compliance management. Regardless of how many sources you have, data coming into your asset repository must be of sufficient quality, quantity and coverage.

Data quality is the measurement of the correctness and completeness of data elements across all entities and the applications of standards, including attributes therein. When data is generated across multiple systems and then brought into the repository, where there are multiple data elements mapped to a single attribute, the data should, according to best practices, have the same format, i.e. Date = DD/MM/YYY.

Data quality also refers to the age of the data; it must be generated and transported in a timely fashion which supports the asset needs. Timeliness of data will depend on the asset (licence) and business requirements.

Data quantity then, is the measurement of the number of relevant data elements you have available to map against each entity. For example, if you are trying to create an asset profile, but all you have available to you is the product name and the date acquired, then you have insufficient data quantity. In order to create an asset profile, you would also need: PO number, SKU number, cost etc. Without the correct data quantity, your assets will not be complete.

Data coverage refers to the measurement of the availability of data elements, entities across the entire organisation in all environments and platforms. In order to generate a correct view of your assets, you must have data on Wintel, UNIX, Development and Test, Production, Disaster Recovery, Infrastructure, Regional Data etc. Unless you limit the scope of your SAM Service, you must have sufficient coverage for asset data.

Data elements in support of ITAM (of which SAM is a subset), must:

  • Include all relevant data, not just software asset and licence data.
  • Support all IT asset views resident in different technologies:
  • – Acquired (IT asset & licence repository).
    – Installed (inventory discovery).
    – Used (usage metering).
    – Entitled (access authorisations).

  • Support specific requirements for analysis and reporting.

The data model is comprised of:

  • Entities – e.g. asset, contract.
  • Elements (fields) – e.g., asset name, asset type.
  • Definitions (purpose, intended content).
  • Standards for key data elements – e.g., asset status.
  • Attributes – e.g., alphanumeric, character.
  • Links between entities – e.g., assets to licences to contracts.
  • Relationships amounts entities – e.g., ‘installed on’, ‘assigned to’.
  • Sources (systems-of-record) for each entity, possibly element.

Without data, your technology will not support your business requirements and be unable to provide you with the reporting and analysis information needed to make qualified decisions regarding your assets.

For more information about SAM data analysis services, please contact ITAMS.

Oracle Licence Inventory Uncovered

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ITAMS’ Licensing Analyst Sergiu provides an insight into the Oracle Licence Inventory.

The Oracle audit process represents a series of steps. The basis for this is Oracle’s so called “Licence Inventory”, although other software vendors may refer to it as ‘licence repository’/ ‘entitlement’, etc.

The Oracle licence inventory report is an excel spreadsheet summarising the licence products purchased by a particular customer and also a comprehensive overall picture of the historical support and licences.

How is this report used?

The report is used by Oracle Licence Management Services (LMS) consultants as a primary verification tool against which the original contracts are checked, in order for them to build a clear, simple and complete software repository. Later on, this will act as a guide for Oracle field consultants when managing their clients’ software accounts.

Grouped in several tabs, the information is based on the contract migrations report data and product migration rules. As a customer, special attention should be paid to your reference information, such as the correct spelling of names and ensuring that the address you have registered is the correct one. Also, pay particular attention to the status of your licences (if they are active or inactive) and the licence metric name of each licenced product.

Can the customer obtain this information from Oracle?

In 90% of cases, the customer will receive a “customer facing document”, where details about Oracle’s licencing audit report can be found. Included is a licence table (a simplified format of the licence inventory), nonstandard clauses (found in the original contracts), definitions of the licence metrics that the customer is licensed on (taken either from the original contract or from Oracle’s price lists) and finally, the minimum number of users /devices required for every software product (so these can be correctly licenced).

Gotchas

As Oracle consultants build the customer repository using different systems, sometimes the information lacks accuracy, so the customer should pay extra attention to ensure that the details contained in the inventory are correct.
For the customer, the most sensitive information to check is related to:

  • Product name
  • Licence Level
  • Licence Term
  • Metrics
  • Quantity
  • Support status
  • Licence ownership
  • Duplicate products.

Recommendations

For a customer to have a clear licencing position, they should ensure they have:

  • A tool that is capable of tracking all software licences currently in use.
  • Identified all the deployed licences across the organisation’s network. (Oracle uses measurement scripts which may be provided (but not in all cases). Customers must ensure that they know what the outputs are and that an expert is working on that.)
  • Built and maintained a report with detailed information on licence use. In other words, keep track of licence use internally.
  • Started comparing entitlement and deployment on a regular basis in order to have a strong compliance position.

After all the above are taken in consideration, the customer should have a clear view of whether they are under-licensed and need to acquire extra licences or whether they are over-licenced and need to uninstall licences.

Managing software assets can feel like an endless maze if you don’t know how to approach licensing information. Remember creating an efficient SAM process takes a lot of time and needs dedicated resources.

If you would like to listen to the pre-recorded webinar on Oracle Licence Inventory Uncovered, please click here. For further information, please contact us.

Is your data fit for consumption?

ITAMS’ Strategic Advisory Services have been designed to help you navigate through the difficult challenges of controlling and managing software asset ownership and utilisation

Amongst the variety of services we offer the “Data Fit for Purpose Testing” Service in particular is pertinent to helping you understand the quality of your data.

The service performs a high level review of the data quality in your major data sources and highlights any data quality issues. Once these are identified ITAMS’ experts are able to make informed recommendations on how these issues can be addressed. To find out more about the, “Data Fit for Purpose Testing” service please call: 0870 4050508 or email: info@itamsolutions.com

ITAMS always delivers its services as an independent service provider. For more information or expert advice on any of the topics above please contact ITAMS.

Get Real Value from Disparate Data Sets

Are you using the right asset to manage your licensing entitlement?

A common issue ITAMS’ consultants come across when helping clients build a SAM / licensing programme is the conflicting records found for a given asset, normally from different data sources. The data sources often include various tools such as discovery, security, patching and software distribution, results from physical audits or barcoding solutions, as well as entries in CMDB etc.

The conflicted records provide limited coverage and are most likely to be out-dated, posing a threat not only to its accuracy but also its integrity. As a result many clients are left in a difficult position in terms of deciding which set of the conflicting records should be used to run compliance calculations or against which data CMDB CIs should be validated.

ITAMS’ best practice recommendation is for clients to consolidate and normalise the disparate asset data sets into a “golden source” and to use only this common record across the organisation and on which to base licence and configuration decisions.

Case Study:

Hardware data reconciliation supporting licence, configuration and outsourcer management

With help from ITAMS, a recent client in the finance sector successfully consolidated, compared, normalised, visualised and reported against 15 hardware data sources. The results were spectacular. They assumed the worst case for calculating hardware maintenance contract by including all identified machines from a number of data sources as input to their assumed estate.

In fact, less than 70% of these machines were real and still present. Analysis showed that the largest contributor was that discovery tools continued to routinely report machines they had last scanned years ago as active. As many of these tools were outsourcer managed with neither a mandatory nor a ‘3 month aged device’ policy applied, the reported data was evidently inaccurate and accounted for unnecessary overpayments in various categories (hardware and software related) to the tune of £10M’s.

The value from the project goes beyond cost avoidance and supports many areas of operational and cost management. It provides a full audit trail of how the “golden record” is derived against which reports on complex data sets can run.