|Buy vs. Build (technology platforms)|
- Quick start
- Ensure vendor’s skin in the game
- Readymade infrastructure (training to troubleshooting) to aid scale up
- Reduced dependency on internal development teams
- The market for off the shelf solutions with ‘low code’ or ‘no code’ options has increased over the last 3 years.
- Subject to organizational on-boarding requirements, it will be easier to implement an off the shelf tool with support / training from the vendor in year 1 and subsequent support froman internal center of excellence
|RoI vs. Learning|
- Current way of working – EUC driven / manual
- Evolution stage of organization in the pursuit of process excellence
- Applicable scope to implement
- Future vision for the function (TAT, Data capability for Business Partnering & support, Agility to changing regulations)
- Not Investing in Innovation will eventually result in its own ‘downside’.
- Extension of process transformation along with technology provides higher synergy and better results
- Impetus to re-visit current ways of working and acquire new skills at the same time – eventually impacting the culture of change within the function.
|Drip feed vs. Big bang|
- Current Experience & Learning from implementation
- Existing success cases (Pilots, Proof of concepts)
- Implementation experience and size / type of support model in place
- For new tools, focused Pilots (typically in 100 days) are recommended to provide the required learning to adjust the implementation operating model (Skill set to develop, IT support, vendor support, tool limitations).
- Important to for the new technology to be seen as useful (demonstrated thru Pilots) to impact wider adoption in the function
|Train SME’s vs. hire future skills|
- Type of technology / Innovation being implemented (E.g. Data Science vs Simple Automation)
- Current skillset of staff in technology
- Current Culture
- A combination of training SMEs and hiring new skills will provide the right knowledge required to undergo Digital transformation
- The introduction of ‘low/no code’ tools (e.g. Xceptor, Qlik, Ateryx) has made it possible for Finance staff (using excel) to learn new technologies in weeks.
- Investing in some new skills which are not a part of the traditional Finance skillset(e.g. Data Science specialists) especially inconcepts like Machine Learning which can aid better Forecasting & Insights and provide a better level
of automation for complex manual processes
- Change / Innovation job families required for Finance to understand and define the strategy for the function over the next 5 years based on current state and pain areas / business needs.
|Long term strategy vs. Bridge strategy |
- Where do we want to be in 5 years (Single data set for all Finance needs?)
- Speed of implementation
- Markets operated
|Short term innovation solutions can rely on internally hosted solutions, and provide quicker results. However a cloud strategy and plan to transition to it will become necessary in the medium term. Such plans need to run concurrently, and|
is bound to go through a phase that is likely to feel chaotic.
- Provides the required processing power to create a single data repository for all Finance needs at a lower cost/span>
- Cloud based services can be added on top to provide additional automation / visualization
- Higher time to satisfy regulators of appropriate security measures (e.g. encryption / data masking) and seeking Data transfer approvals
- Most innovation tools (off the shelf) are compatible with cloud hosting