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Ivanti Asset Discovery
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Data is everywhere
Do you feel organizations know accurately what’s in their environment?
How many sources do you think organizations have to typically handle?
Rex: thought 32bit platforms go away,….opposite, more complex, expect to get more diverse, Raspberry Pi, …. Robot… everything is impacting assets, management state, security and financial impact.Suspecting higher than that, 24! – Remote worker impact!
Arlen: on the network stuff, but what about procurement data?
to manage assets effectively, not only discovery, also need sources of procurement what was purchased, when, for whom, delta what was purchased and owned.
Analyst Enterprise Management Associates did a study a while back stating that 50% of organizations on average have 12 or more discovery and inventory tools. On average, IT spends 10 hours per week resolving data-accuracy issues.
It’s tough to normalize the data, reconcile it and make sure you understand the delta, and where the data is coming from. Good tools are able to automate this process for you, to give you robust data you can work with.
Arlen: detective work, ….
Rex: you bring up a good pt. , procurement, challenge is how do you reconcile this, AD, purchase data, not many attributes that are the same across…
Unique ID, leads to immense challenges without a proactive approach, problem spirals out of control, customers tried, but many failed $$$ and hours
Arlen: no effective correlation, all accounting in excel ..
Recent survey shows that 43% are still tracking their IT assets with spreadsheets?
Why do you think so many organizations have not yet got a good handle and system to manage their IT assets?
Rex: 1 quarter of a man year just spent on reconciliation. Can’t afford with labour shortage. Keeping lights on, no time to be strategic.
Project success story: rule based engine for reconciliation
When they first start out, without proper planning, really not prepared for the complexity
We asked respondents how much time was spent per week reconciling inventory/assets.
29% said “too long”
24% spend HOURS per week reconciling
17% reported “hardly any” as they are fully automated
Good for the 17% having a good handle on it. For many it’s taking a lot of time as data can be in so many different places. In the procurement system, in IT endpoint and network management systems, discovery, etc.
Analyst Enterprise Management Associates did a study a while back stating that 50% of organizations on average have 12 or more discovery and inventory tools. On average, IT spends 10 hours per week resolving data-accuracy issues.
It’s tough to normalize the data, reconcile it and make sure you understand the delta, and where the data is coming from. Good tools are able to automate this process for you, to give you robust data you can work with.
Arlen:
Rex: TV example
Chris: pallet of hardware nobody knew where it came from, tempted to use…security threat!!!! Preloaded with malware
Chris: lost data / data privacy angle
Chris: ton of data sources, try to solve with tools that are ineffective, every asset that we don’t catch, are security risk, attacker…
Casino/Fish Tank example
Arlen: true asset management is not just about assets, bring together different data sources to do it right…ALM, financial/budgeting and negotiating with vendors
Rex: inventory is good data, assigned owner story, risks involved
Arlen
Rex: passive discovery from a manage side – one critical insight, highly secure government site, network response team, off by double digits
Chris: you need good virtual and cloud discovery – hyper V, state of templates, outdated from patching perspective; cloud systems
Arlen: Reconciliation, represented in a way that minimizes overhead – ITAM as detective/investigator – devices off warranty, off support policy.
Rex: in IoT devices, less capability to interrogate devices and learn, monitor traffic and using ML/AI to determine what type of device is it, and is it doing expected behavior, hughe traffic on passive
Chris: progression of asset linked to security; CIS framework, proliferation of devices – remote work – what will happen? Work from anywhere, connect from anywhere, need to get better to solve this asset problem, contextual awareness, zero trust models
Arlen: security – asset, more information that needs to be correlated, value of AI/ML,