Incorta, the platform for real-time operational analytics on raw business data, recently launched its Analytics Data Hub for Finance. To find out more, VMblog spoke with Ardeshir Ghanbarzadeh, Director of Product Marketing at Incorta.
VMblog: Incorta’s Analytics Data Hub for Finance was just announced. What capabilities are IT organizations most excited about?
Ardeshir Ghanbarzadeh: The Analytics Data Hub for Finance enables IT professionals to quickly deploy a centralized hub for financial analytics and empower finance decision-makers with timely, accurate insights. IT organizations can leverage Incorta’s fast and flexible data pipeline to bring subledger and operational data into a unified environment without the need for traditional transformation or ETL. They can also use pre-built business schemas and dashboards of Incorta’s finance data apps to quickly deploy customized financial analytics on their ERP data.
That’s a big deal for IT professionals supporting the office of finance because it offers an end-to-end view of financial and operational data to quickly adjust forecasts, perform timely analysis, and even run predictive models for forward-looking insights.
VMblog: Who and what does this new solution enable?
Ghanbarzadeh: The solution ultimately enables CFOs and finance teams to make faster, better and more informed decisions.
When you have an end-to-end view of the latest business data in real time, it materially impacts the efficiency and accuracy of Finance teams doing planning, forecasting, analysis, close and reconciliation processes. More broadly speaking, the focus in financial and operational analytics goes from backwards-looking reports and dashboards to real-time analysis and insight discovery. That’s game changing.
VMblog: What challenges are customers able to solve with the Analytics Data Hub for Finance?
Ghanbarzadeh: With the Analytics Data Hub for Finance, IT professionals can enable finance teams to collaborate and share critical business data in a unified environment that:
- Provides consistency for data models and governance across the enterprise by connecting data from multiple ERP solutions, business applications and financial and operational systems in a unified environment.
- Accelerates data feeds to, and analysis for, planning, forecasting, reconciliation and close cycles with visibility and analytics directly on subledger details and external operational data.
- Delivers built-in finance data apps to quickly and easily deploy new financial and operational analytics in days.
- Extracts more value while simultaneously future-proofing your financial technology investments by easily integrating with popular finance tools and reducing long-term operating costs.
VMblog: What prompted Incorta to create a solution specifically designed for the office of finance?
Ghanbarzadeh: Today’s business environment is growing increasingly volatile, unpredictable and challenging to navigate. Against this backdrop, we are seeing more and more CFOs and offices of finance called upon as key strategic partners to the business. This not only raises the stakes for strategic financial decision making but also accelerates reporting demands and timelines.
To succeed, Finance teams need real time data for analysis, as well as visibility into all financial and operational data for a complete view of not only key metrics and business drivers but also transaction-level details. Additionally, they need the ability to quickly answer new questions that were never asked before in order to support the immediate decisions that face the business. This means the need for flexible self-service capabilities to run ad hoc queries and build new reports on their own with limited reliance on IT teams.
But that’s easier said than done… Today’s finance teams routinely struggle to access, analyze and generate meaningful insights from financial and operational data – i.e. the data that is most critical for driving timely strategic business decisions. That’s because the data is siloed in ERP systems, business apps and finance tools. As a result, instead of being strategic partners, most finance teams are stuck spending a majority of their valuable time collecting data from disparate systems, reconciling conflicting reports and stitching together data sets to gain a complete view of the data just so they can start to analyze it.
We created the Analytics Data Hub for Finance to address these challenges and help finance teams and the IT professionals supporting them to spend less time preparing data and more time making strategic business decisions with it.
VMblog: What makes Incorta’s approach to tackling “timely and accurate financial decision making” different?
Ghanbarzadeh: Unlike other solutions, which are built within traditional data warehousing paradigms, Incorta introduces an entirely new approach.
Incorta’s proprietary Direct Data MappingTM engine is a core differentiator – a revolutionary approach that eliminates the need for time-consuming data engineering, including ETL/ELT and data warehousing. More specifically, Incorta can preprocess raw data to determine all potential query paths, enabling fast queries on normalized (application) data models without data reshaping or transformations.
With Incorta, IT professionals can skip costly and time-consuming data warehouse projects and focus on delivering data, insights, and real business results. End users in the office of finance, meanwhile, can analyze all of their usable data down to transaction-level detail, with unmatched performance, even when analyzing billions of rows of data and hundreds of table joins.
VMblog: How will CFOs and finance teams benefit from this?
Ghanbarzadeh: The newly launched Analytics Data Hub for Finance brings unprecedented speed and flexibility to financial and operational analytics. It provides an end-to-end self-service platform for analysis of accounts payable, receivable, fixed assets and general ledger data, and provides visibility down to transaction-level details while applying common models and governance controls to data from different sources and destinations. New financial data apps accelerate operational analytics for Oracle ERP Cloud, SAP, Oracle EBS, and NetSuite. New integrations enable data delivery to core forecast, plan and consolidation process finance systems, starting with direct API feeds to BlackLine with planned solution expansion across a breadth of technologies in the space.
This translates to faster decisions driven by the most recent and accurate data. This has a transformational impact on business outcomes, while delivering efficiency and productivity to give organizations a competitive advantage.
VMblog: Can you share additional details on the overarching challenges finance teams face when it comes to working with financial and operational data?
Ghanbarzadeh: Today’s finance teams face a series of data and analytics challenges that limit their ability to efficiently deliver meaningful analysis and insights from business data:
First, the operational and financial data that’s critical for making timely business decisions is stuck inside a constellation of siloed ERP systems, business apps and finance tools. As a result, finance teams lack an end-to-end view of financial and operational data.
In an attempt to solve this, many finance teams take matters into their own hands and do their best to manually reconcile data sets. But bringing together data sets from different source systems is notoriously painstaking, time-consuming and error-prone work. The time spent collecting, cleaning and reconciling conflicting data models and reports can severely reduce a team’s resources and capacity to perform analysis and craft commentary to the business, which delays critical business decisions.
Another issue that crops up is finance teams lacking the ability to run ad-hoc queries and ask new questions. The only answers that arrive on time are the ones that were predefined in a report or dashboard. Worse yet, they lack the ability to perform self-service analysis or drill into transaction-level details for root cause analysis because they are limited to topline KPIs and highly aggregated data.
Finally, Finance teams often find themselves waiting for data. Once a request for new data or reports is put into the IT or BI team’s queue, it could take days or weeks for delivery. This is an unacceptable tradeoff, and inconsistent with the required pace of business and decision making today.
VMblog: What emerging technologies and trends make financial and operational analytics modernization a priority?
Ghanbarzadeh: The challenges around financial and operational analytics are longstanding issues that were never solved by technology. Data warehousing offers a solution, but it’s a solution that creates as many problems as it solves – including loss of data through transformation, data delivery delays, or rigid data models that can only answer questions of the past.
The biggest driver of demand for better, faster and more flexible financial and operational analytics is the growing need for speed and agility in strategic business decision making against a backdrop of extreme and persistent uncertainty and change – and a stark realization that the systems these teams have relied upon for decades can no longer keep up with the pace of modern business.
##
