The Desilofication of the Enterprise

May 12, 2021 | 4 minute read
Stefan Schmitz
GVP, Product Management, Analytics Applications
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How Fusion Analytics Warehouse and Oracle’s unique strength in cloud apps enable cross-domain insights and drive collaboration, alignment across business functions

Silos. We still see so many business functions operating in them when it comes to data, data insights and reporting. This leaves them with far less clarity into how their specific function drives and impacts the organization's overall performance and goals. While they may track any number of different metrics that are important for their specific operations, they end up less aligned with the company's overall strategy and business objectives.

The thing is, the pandemic has intensified competition, and markets are changing fast and drastically. Businesses across different industries need to be increasingly agile to ensure they keep up with the pace of change. In this climate, there’s really no room for different business functions to work in silos as they have in the past.

Basically, it's time for a massive enterprise desilofication (some call it “un-siloing”) effort. And analytics is the key.


The Goal: Cross-Organizational KPIs

An analytics system that provides total KPI and metric alignment across the organization enables everyone - from the executive suite downstream - to work in closer unison and tighter collaboration with other business functions. 

This is what we’re doing with Fusion Analytics Warehouse (FAW). FAW provides a single layer on top of all operational data across various different business functions – meaning our customers can track and measure their performance based on a single set of cross-organizational KPIs that are shared by different business functions. 


For example? HR and finance. Historically, these two functions aren’t that well aligned. HR frequently tracks their own business performance by measuring the number of people in the hiring pipeline, time needed to turn candidates into new hires, etc. But the real value, from an organizational perspective, are metrics that express how well these employees perform and drive the company's bottom line. This means looking at new hire performance in the context of financial results. 

This is where silos are the enemy and FAW is the good guy. Because to do this, you need to pull and correlate data from both finance and HR. It’s the only way to create KPIs that can track how employee quality impacts revenues and profitability – which reflect the ultimate goals of both HR and finance. And these employee productivity metrics are exactly the type of new KPIs that FAW can serve up.

Another great example of cross-organizational KPIs is the lead-to-revenue pipeline - which straddles the boundaries between marketing, sales and finance. How can we optimize the process from marketing lead, to qualified opportunity, to sales order, to closing a deal, to booking revenue and cash? How can we drive that entire cycle? Clearly, in a siloed enterprise, it’s tough, because measuring the throughput through that cycle requires inputs and data from marketing, sales and finance. 

Here again, Oracle is uniquely positioned as the only enterprise software provider that has cloud apps to cover all of these business functions - from the front office, to the back office, from marketing, sales, through HR, finance, and supply chain. They’re all tightly integrated, they all sit on a common data model, and this enables FAW’s cross-organizational reach. It’s how we create the KPIs and metrics that drive and measure truly enterprise-wide processes. 


How Does FAW Do It?

FAW is essentially the analytics layer that sits on top of multiple cloud applications and can pull in the data into a common instance of the Autonomous Data Warehouse. FAW provides, out of the box, a data/semantic model with conformed dimensions like time, business unit, product geography – all common and all shared by all the different business functions in the organization. This allows our customers to define cross-functional and shared KPIs and metrics. What’s more, we also deliver a library of best practice KPIs in use today.

And even if our clients aren’t 100% Oracle shops, FAW still delivers this value. Because we understand that with the proliferation of cloud applications from different vendors - each potentially with its own unique data model and highly-optimized business function – we still need to access and use data from these source applications. That’s the reason we put such an emphasis on FAW’s extensibility - we also allow customers to bring in data from other applications, we don’t just limit them to Oracle cloud apps.

That said, we do bring unique value to the table for Oracle Cloud Application customers, since FAW is completely Oracle-managed. That means that our customers don’t need to have a dedicated and skilled set of IT resources to manage and set up data extraction and manage the data pipeline. Rather, they just define the parameters that control which specific data and data slices to pull in, and everything else is fully managed by Oracle and automated. This also means that when Oracle Cloud Applications come out with a new version or patch (which happens frequently), FAW ensures that there is no impact. We manage the changes behind the scenes, completely transparent to the customer - they can rest assured that it keeps working from release to release. 

Driving Collaboration 

Overall, the desilofication of the enterprise is about alignment and collaboration. FAW and Oracle’s unique strength in cloud apps enables the cross-domain insights that drive collaboration and alignment across business functions. In the end, the pandemic – for all its tragedy - has created an opportunity for businesses to enhance agility and gain better clarity into how each specific business function drives and impacts the organization's overall performance and goals.


Learn how you can move beyond silos using Fusion Analytics Warehouse KPIs, cards, and decks.


Stefan Schmitz

GVP, Product Management, Analytics Applications

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