9 Data and Analytics Trends That Will Dominate Finance in 2017 *Bridging the talent gap...
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9 Data and Analytics Trends That Will Dominate Finance in 2017
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What decisions will dominate your finance operations in 2017? Finance leaders are fast re-evaluating their teams’ analytics skills and learning how to leverage these for the new era of data-driven decision-making.
The competitive advantage of data analytics is well understood in an age where enterprise insights and agility allow organisations to leapfrog their competition. Analysing data is crucial for improved decision- making, to provide answers to management’s questions, and to support the business in gaining an edge over its competitors.
As a result, proactive finance strategies are being built around greater systems integration, improved access/transparency, and intelligent evaluation. These kinds of analytics can be broadly applied across an organisation but run into competing investment priorities that distract management’s attention. Nevertheless, there are several key trends that cannot be ignored, and that will be pushing Data Analytics to the top of management agendas next year.
Learn the benefits of 9 data and analytics trends that will dominate finance operations in 2017:
Continued growth in analytics jobs SSON’s 2016 survey report highlighted data analytics as one of the key skills that shared services leaders are focusing on at present, and we see plenty of proof that analytics skills are being stoked up through targeted recruiting as well as training. If you are going to invest dollars in skills, this should be top of your list. At the same time, a recent Everest Group report* warns of a sizable gap between demand and supply of talent for analytics services. Smart organisations are optimising their global location portfolio to leverage the best proposition across all geographies, and focusing on retention strategies.
Setting up data analytics Centres of Expertise Centres of Expertise or Excellence (COEs) are fast emerging as key strategies to drive performance across a wide range of tools or solutions. The ability to deploy data analytics experts to a given project or problem on an “as needed” basis, and to leverage this acquired expertise across other teams or groups, is the most effective way of benefiting from this skill. It is also an efficient way to tap into this valuable and relatively expensive talent.
Investing in technology solutions that support real-time reporting and transparency
Pushing back on multiple sources of information and, instead, focusing on a single point of access and channel
Promoting analytics skills across the employee base so that it becomes part of everyone’s job to recognise opportunities
Solution providers are shifting their products forwards by reacting to customers’ demand for immediate, transparent, and actionable data. For leading solution providers, this translates into real- time data, easy identification of patterns, and improved flexibility around reporting for different stakeholder groups. For those who are not yet there, the writing is on the wall: evolve, or become irrelevant as competitors grasp this edge.
One of the biggest hurdles to accessing and understanding enterprise data is the “multiple versions of the truth” that are commonplace when various ERP or other legacy systems are entrenched. One of the reasons we are seeing so many finance transformation initiatives is that enterprise leaders recognise the cost of fragmentation, and are pushing for single channels. This involves significant change management and effort, much of it difficult, but builds a strong foundation for real-time analytics in the future.
As well as centralising expertise within COEs, data analytics has a democratizing effect in that the basic skills can easily be pushed out across the employee base, as a basis for encouraging all staff to look out for, recognise, and drive initiatives around relevant opportunities. Much like the Japanese philosophy of Kaizen, based on personal efficiency, every employee of the future will be responsible for searching out and recognising analytics prospects within his or her own workspace.
Advanced analytics are able to predict future scenarios and suggest strategies to optimise resources accordingly The ability of analytics to cross-reference and integrate data, both internal and external, structured and unstructured, produces powerful results. These extend from devising optimal purchasing or sales strategies based on expected currency fluctuations, to ramping up talent where it is plentiful, to identifying the least cost- effective suppliers. As such, data analytics is a powerful tool in management’s arsenal, and one that provides a clear and credible competitive edge.
Analysing HR-specific data for patterns and trends to identify core talent, particularly in aiding with recruitment and retention of millennials One of the most valuable outputs of data analytics is the ability to segment the existing workforce according to skill and ability, as well as cross-referencing with external market data, including social media, to devise successful policies for attracting the millennial talent that constitutes the workforce of the future. Millennials are famously reactive and tech-savvy, and therefore data analytics presents the perfect opportunity to identify what attracts them to an employer, and what will retain them.
Improved understanding of artificial intelligence may lead to more intelligent automation Much of what is currently being lauded as “cognitive” is in reality far less. Artificial intelligence makes a great headline, but the actual connection to cognitive processing and subsequent big wins are still more talk than tangible implementation. While it’s important to be aware of the potential of analytics’ evolution, don’t waste time chasing every red herring. Beware of hyped up claims for AI that in reality are based on “OCR” style technology claiming to be cognitive. Select your partners carefully, and pick their business case apart.
Use prescriptive analytics where it pays off most: in customer retention and in maximising a customer’s lifetime value, real-time reporting and transparency Every enterprise knows that it is easier to keep a customer than to gain a new one. So, leverage new tools on the basis of their ability to maximise customer acquisition and retention. Analytics is a powerful partner in identifying successful retention opportunities and their effectiveness. If you can demonstrate wins in this area, business leaders will also be willing to consider alternative projects that might otherwise be overlooked. Choose your projects strategically. *Bridging the talent gap – global talent hotspots for analytics (Everest Group, 2016)
What next? How you can get started with Data Analytics: • Identify the analytics effort that needs to be
driven in a coordinated fashion across the company to enable better leverage
• Develop a common set of analytics capability in a central group for faster capability ramp-up
• Establish reusable tools/approach/methodology for deploying analytics solutions for better efficiencies and consistency
• Develop a central talent pool of highly skilled analytics professionals
• Establish standard processes for best practice sharing and effective knowledge dissemination to enable a learning organisation culture .
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This trend insight was created ahead of the Future of Finance Summit 2017.
A review of Data & Analytic trends are heavy featured in the Summit agenda. You will learn effective insights that will impact your strategy through real-time analytics and business intelligence. Speakers specifically focusing on Data & Analytics include: Schlumberger, Quad Graphics, Ikea and more….
Future of Finance 2017 is taking place on 14-16 February 2017 in London, and is the most exciting, forward-looking Finance Summit with a truly progressive approach to help you drive your finance function into the next-generation. With over 50 speakers, 3 streams and 180 attendees, this is your chance to learn, network and benchmark with your European Finance counterparts.
This content was created by Barbara Hodge, Editor - SSON
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