How is your company upskilling or adding Data Science talent? Are you centralizing these skills or building throughout the functions and business units?
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Director of Finance in Consumer Goods8 months ago
We have a COE department which specializes in RPA and Data science. Its a centralized department and provide seamless support on automation and data analytics through visualization tools across functions and business units.CFO in Finance (non-banking)8 months ago
In my experience at Apple and Uber, it was always fastest to bring on skilled Data Science and Analytics talent (i.e., hire net new). Training your existing team will not be as quick as you would like. It's also worth differentiating Data Science and Analytics because most companies actually need Analytics rather than true Data Science, but that can be a separate post entirely.That being said, it's also important to have a good data infrastructure and data engineering so that the data is there for these people to use. Sometimes IT teams can help with this, but if you don't have in house data engineering expertise, I would advise going with a data consulting firm that can help you stand up a data warehouse to help answer the finance and business questions you want answered. This can be very costly (time and money) if done incorrectly.
Finally, it's important to continue to up-level your existing team and get them more exposure to query languages, data models and data structure. Your existing team is going to know the business the best, and working together with data scientists and analytics experts is going to yield the best result. Good luck!
CFO8 months ago
In making a call on that, I believe a key criterion for you is to asses your organisational level of maturity in terms analytics (from descriptive to prescriptive analytics) as well as data literacy.We have chosen a centralized approach when creating our D&A organisation (hub and spoke), which includes a unit (D&A Lab) that purely focuses on advanced analytics. The latter, we will grow organically but we expect also to add more Data Science talent over time as we successfully deliver tangible benefits to the business. The central approach is in response to having assessed our level of maturity, which needs to grow further before we're able to decentralize. Our objective remains to decentralize, as we acknowledge that a business driven approach and close proximity to the business is crucial to successfully delivering on our D&A strategy. Only by having a profound understanding of the business you're able to achieve your D&A objectives. We realize that it probably will take a couple years before we're able to decentralize.
Addressing your current data pain points and ensuring a cloud native infrastructure is needless to say another area of focus.
Director of Finance8 months ago
Our company has a program in Finance called the leadership development program (FLDP) for finance professionals. The new hires from colleges / MBA programs over the last three years added through this program have typically had digital / data analytics skills. Through the screening / hiring process we have focused on their studies and intern work where RPA, automation, and data analytics are prominent. The institutional knowledge we have in our existing finance team in the Financial Shared Services organization has been easily upscaled into the RPA effort. Their comfort with enabling technology, and propensity to execute business process reengineering have augmented the services provided. This has been extremely beneficial in that endeavor to add digital services to the SLAs provided to all of finance with our existing (upskilled) Financial Shared Services team.
Our Financial Shared Services team has transition into the automation / RPA service provider that is leading the finance function’s digital objectives; allowing the client finance teams to be focused on achieving business outcomes and refocusing on value added effort. The additional of digital finance skills for RPA development, data analytics and automated finance business processes are three years is and extremely successful with over 500 automated processes in place, 250 of which came in the last twelve months.
By upskilling the Financial Shared Services team, we have identified the opportunity to assign broader transformation responsibilities to the delivery model, seizing an opportunity to accelerate digitization efforts across all of Finance. By dedicating more time to finance wide digital transformation efforts, we seek to build a shared services digital transformation roadmap that links with broader finance function efforts. Two FLDP candidates have successfully rotated through the RPA & Enabling Technology team in Financial Shared Services.
An extremely high level of adoption of RPA in the Financial Shared Services operation has created the bandwidth necessary for the team to spearhead the digital roll out in Finance to be so successful. An unexpected result is, we have moved this team from a net exporter of talent into an area that young professionals seek to align with the implementation project teams responsible for digital finance transformation.