Managing Data Bubbles

Automating Core GRC & Operational Data Flows in Finance and HR for Value Creation

Bubbles can be seen as positive in that ongoing process changes within data silos can be tightly managed, or negative from the viewpoint that these primary data sources might contain core relevant information that is not easily accessible to others.

Functional, departmental, regional and global bubble variants exist, but each one can be expanded or reduced in size to drive broader deeper controlled change, or even removed altogether. As always, successful execution is in the detail.

Processes that are x-application or x-ecosystem, whether within or between entities, are easier to create and manage today. They can be set up with or without RPA (robotic process automation) ie hyperautomation, noting that any document onboarding may additionally leverage some document recognition features using AI (artificial intelligence), or alternatively may use simpler yet still effective automated document onboarding methodologies.

Historically, these end to end x-app and x-ecosystem transactional process activities have come together with extensive painful baggage, in the form of execution friction, which continually and disproportionately suck out time from your other core management tasks. This is because decision support, operational controls, and management interactions have all been hard to execute (due to speed and required transformations), let alone automate, on a repeatable and auditable basis. 

Finance including HR are therefore critical areas receiving attention for improved business continuity. Holistically, looking across all operational entities, these process inefficiencies and bubbles of data are replicated not once, but many times. This means that there is extensive value to be released in terms of resource hours, not to mention the prospect of having much more timely and broader information to drive new actionable contextual decisions across multiple stakeholders.

For example, consider that month end routines typically span 7 to 16 days (source https://www.cfo.com/management-accounting/2021/01/producing-management-reports-faster-metric-of-the-month/). This leads to a delay in getting insights into the business, and is certainly one area to explore to release resource hours for other areas.

Dig deeper and one survey revealed that some 84% of companies cannot knock out transactional flow barriers due to technical difficulties and know how. This issue typically gets expressed into terminology relating to talent or domain capability or lack thereof. (https://www.cfodive.com/news/real-time-data-decision-making-accenture/592402/ ).

Connected with this is that all financial software systems look and feel ostensibly the “same” on the surface, in that they enable similar financial processes including report and statement designs, so in reality it is all very much down to the how, and ease of use of the system by domain users ie UX, process functionality including segregation of duty, that become the main differentiators between them.

Not only that, but the demarcation lines associated with detailed transaction handling, in terms of the hardware required for execution has to all intents and purposes been nullified. This means that one should carefully scrutinise the cost of ownership per line item including annual increments ie software upgrades including extensibility options for new technologies, maintenance, and required consulting, to ensure that ongoing value is being received.

Note that this challenge is many times worse in older higher volume systems, where older technology simply does not support transactional throughput, and transformation in a timely manner, and where expertise for these older systems is harder to locate etc.

Business imperatives driven by today’s operational environments require that multiple operational bubbles be broken across multiple functional areas. An example of this would be the bringing together and ultra-granular transformations of relevant information from other domain areas for purposes of value creation.

This would include reporting processes x-application ie HR, financials and budgeting (FP&A) that can drive deeper meaningful insights, as well as allowing for deeper staff contributions from other functional areas ie broader participation.

Demands involving change are always constantly evolving, whether that be due to changing regulatory environments, data location management or the looming / often threatened e-based web transaction tax or other tax changes in various jurisdictions.

Each one might be disruptive to you in terms of setup time, and certainly be incremental to your current workloads, so more time has to be found from the streamlining of your existing daily activities.

For example, data location management classifications these days require considerations as well as execution re the physical, logical, legal and taxable location of data, including those inter regional dependencies that may be driven for example by GDPR, and also within the finer execution and operational details of new free trade agreements eg RCEP (Regional Comprehensive Economic Partnership) which covers c 30% of the global gross domestic product (link below), or the GBA (Greater Bay Area). Not only these of course, but there also other important critical drivers of change as well.

Updated March 2021: World’s first space hotel scheduled to open in 2027 https://edition.cnn.com/travel/article/voyager-station-space-hotel-scn/index.html

Cybersecurity, privacy, carbon neutrality, DEI (diversity, equity and inclusion), digital enablement, not to mention algorithmic bias within AI deployments are also areas that require deeper and more intensive consideration, as businesses evolve themselves to handle the future. Time for execution of these initiatives has to come from somewhere.

How much time can be saved? At the moment most corporations are working from a clean slate in that they do not know how long processes actually take them to execute. Often the level of  real FTE (full time equivalent) resources required for execution are not really understood or known, nor is the actual timeliness for certain supporting processes that contribute to the rushed through headline numbers that ultimately drive or undermine confidence in submissions.

For example reconciliations, data transformations etc as historically, systems have not supported deeper transformational process flows that might include the time saving flexibility to toggle data by segment, currency, headcount etc or solving those seemingly innocuous one line communications from HQ of the same type that take hours to resolve.

Instead, most organisations have a macro view on the end result like # of days to complete a task or a final version of the reporting pack. Two examples of weakness to expand on timeliness: detailed aspects of project management incl payment triggers, revenue recognition factors etc; state of staff attrition in key functional areas plus dependencies etc.

Simplicity in process execution and complexity in process design (transformations & segregations of duty), can be diametrically opposed goals and both have to co-exist and be supported by the system. Therefore, fully evaluate your ability to define ultra-granular processes to achieve these goals, including any required systems integration skills associated with the bringing together of data sets, both initially as well as iteratively ie version control, data trace back etc.

Crisis drives change, but technologies are now available for you to deploy compliant business process optimisations on an iterative basis to save you valuable time for those other critical areas of activity, whether that be driven within or across finance, HR, or operations.

FlexSystem is a financial and operations business software vendor to 1 in 10 Forbes Global 2000 (May 2020), and 1 in 5 Global Fortune 500 (August 2020), operating at the intersection of new process and payment technologies, whether on-premise or cloud, to provide you with iterative opportunities for value creation with or without AI at both gross and net margin levels.

Other Information:-

  • Process framework. End to end process definition, from data collection thru all required x-application / x-ecosystem transformational dependencies (including use of API’s), with actionable contextual reporting @anytime and @anywhere in the process + simulations. Consideration for various data type handling.
  • Connectivity will be at the centre of driving efficiency, innovation and deep value creation x-application, x-ecosystem and x-geography. This is not going to be a one off, as there is going to be continual opportunity to drive multiplying value and convenience at both macro + micro levels, and increasingly both; eg top down or bottom up AI or leveraging AI in other applications https://www.uber.com/hk/en/business/
  • Quantifying the Value of Data. https://hai.stanford.edu/news/quantifying-value-data
  • Timely transformations. Leveraging processes across applications with the end result of having resultant processes that are therefore fully defined for the task in hand, are specific in design scope, meaning that coding is less complex, more robust and easier to maintain. Combined with other technologies, like compression gives the already smaller code base additional practical execution advantages.
  • Cloud is one deployment option alongside hybrid / on premise. Our customers are choosing Alibaba Cloud, Amazon Web Services (AWS), Citic Telecom CPC Cloud, Google Cloud Platform, Huawei Cloud, IBM Cloud, Microsoft Azure, Tencent Cloud as well as other service providers or solutions (eg Nutanix) based on their specific needs to create a single or multi cloud collaborative software deployment platform for overall business agility, governance, risk management and compliance purposes.
  • Cloud PAAS Vendors. Note that not all cloud services nor vendors are consistently available across geographies ie need to assess cloud service within cloud vendor by geography.
  • Artificial intelligence. Laser focused by definition, but always positioned holistically in general industry marketing. Once processes are defined, and fully understood end to end, then AI may be a viable “within process extension” to consider further for purposes of deeper value creation. Ie only started once one can define the exact output required. https://flexsystemhk.wordpress.com/2020/09/02/artificial-intelligence/
  • HR Structures for Digital. https://flexsystemhk.wordpress.com/2018/10/09/digital-in-2019-is-still-about-technology-but-more-about-organisational-structure/
  • Greater Bay Area. https://en.wikipedia.org/wiki/Guangdong-Hong_Kong-Macau_Greater_Bay_Area
  • RCEP, Regional Comprehensive Economic Partnership. https://en.wikipedia.org/wiki/Regional_Comprehensive_Economic_Partnership
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