Amid continuous market changes and disruptive new business scenarios spearheaded by digital technologies, advances in artificial intelligence and robotics, companies must be prepared for surprises and be ready to move in directions that are often difficult to predict. We will try to answer these questions in the following paper, although we warn it is easier said than done.
With the advent of the Fourth Industrial Revolution nipping at their heels, companies are under pressure to effectively align investment in new technologies with the business strategy and core finance function. The ability to extract valuable insights from datasets combined with data-driven business models will help them determine how these changes are likely to affect their internal structure and capacity to continue to meet customer expectations.
To this end, companies need efficient solutions that will input essential data into their strategic business planning process. At everis we think analytics helps companies sharpen their competitive edge by allowing them to leverage business-critical information from connected datasets to drive operational efficiency, boost performance and generate revenue on the back of insight-driven business decisions.
INNOVATING in ANALYTICS means shifting FROM preparing and analyzing information TO generating knowledge, anticipating results, prioritizing actions and leading change.
In today’s fast-moving business environment, financial executives need to close faster, report earlier and produce insightful business reports for investors, shareholders and boards in order to make better decisions aimed at gaining market share and creating added value. Amid fierce competition, the quality of financial reporting cannot be compromised by disconnected data and unforeseen events.
At everis, our experience working with market leaders allows us to affirm that traditional reporting techniques and spreadsheets must give way to new financial analysis tools and accurate predictive models in order to make insight-driven decisions and spot trends that would otherwise go unnoticed by:
- Anticipating and carrying out better analyses to obtain more reliable, accurate and actionable results.
- Unifying data into one environment and working with different data sources to obtain a single version of the truth.
- Streamlining and automating reporting, data analysis and forecasting processes.
- Addressing culture change and evolving towards new digital relationships and work models.
DATA should TELL STORIES and PROVIDE INSIGHTS to make decisions about how to grow business and market share, develop and discontinue services, optimize product portfolios and sales channels, balance make vs. buy activities and maximize ROI on investments.
Analytics capabilities should not be limited to systematically preparing automated financial and regulatory reports with the same format and based on the same criteria. Based on our experience, applying analytics to new business challenges can help companies and executives obtain relevant actionable insights, identify opportunities for innovation and ultimately improve the bottom line by looking beyond cost efficiency and tracking performance indicators.
Crunching and displaying data is no longer enough.
In today’s fast-paced digital world, companies need to present their data in a way that is compelling to stakeholders and customers and targeted to business needs. It requires preparing the data and defining the questions that analytics reports must answer in relation to business and market analysis, business modeling, operating variables and financial statements. Some 65% of CFOs say that they’ve never breached a deadline.
Based on our experience, these are the Ten Key Success Factors to address the financial reporting and analytics transformation within companies:
1. Designing a strategy and building step by step…
…experimenting and creating POCs to discover what works and what doesn’t in the company.
- Having a clear strategy of what the company expects from its reporting process, core business drivers, type of decisions being made and strategic measures.
- Designing a roadmap for the analytics model and deployment in the coming years through pilot projects that showcase the company and the type of potential capabilities arising from the deployment of this type of models and tools.
- Changing mindset and adoption of agile analytics, assuming risks in order to learn by trial and error.
2. Establishing a governance model…
- Establishing data ownership.
- Ensuring a single, consistent, common data model to guarantee data relatability, quality and standardization, security and access, cost vs. effectiveness and scalability of the model.
3. Investing even when ROI cannot be quantifiably justified…
…and accurately measuring internal and external capabilities.
- Investing in the resources that will allow the company to achieve its business goals and strategy.
- Being realistic and identifying the internal and external capabilities the company needs to acquire.
4. Attracting and retaining talent with technological savviness skills…
…and integrating them in multi-disciplinary teams to develop the model and foster an analytics culture within the company.
Investing in equipping employees with analytics skills and training at all levels: senior management, finance, functional leads and Business Unit teams.
5. Being interconnected…
…breaking silos and implementing cross-company, integrated, collaborative models and procedures. A hybrid organizational model combines:
- A Center of Excellence (CoE) as a key strategy with a global location portfolio, sharing expertise and efficiently managing valuable talent.
- Business Partners in the different business units.
- Key people in functional areas who are evangelists, proposing new work methods and ways of exploiting data.
6. Integrated driver-based models…
… with the objective of linking the operational models of each area through key business indicators and establishing the relationship between them.
- In this way, the needs of all business areas are integrated, giving a holistic and interconnected vision of the business while providing greater depth and reliability both in performance analysis and forecasting, in an interconnected manner and responding to the hypotheses, needs and resources of all the areas, and in data analysis. Most CFOs consider reasonable a forecast accuracy of less than 5% and 2% as best-in-class.
- Working with “white box” modeling order to understand the impacts of the different variables on the company's financial statements.
7. Lead by finance…
… relying on the recognized analytical & methodological skills and business acumen of Finance professionals. Some 70% of CFOs believe that Finance is in a position to lead the digital transformation of their company.
- Leveraging the unparalleled reach of the finance function across all functions, Business Units and geographies within the company.
- Sponsored by the Steering Committee, guaranteeing the vision and understanding of business needs. It is essential for analytics teams to include people who, while lacking in analytics skills, have extensive experience and knowledge of the business and work side by side with data engineers and scientists.
8. Use and application of fit-for-purpose technologies…
…increasing data volumes require the use of new technologies that will allow companies to create complex business models, shorten time-to-market and implement self-service, dynamic and real-time reporting.
- Properly defining the areas in which the company needs to evolve and the purpose of this evolution, i.e. characteristics of visualization, real time, flexibility, time-to-market, granularity and others.
- Analyzing the type of reports and analytical capabilities that the company wants to cover: dashboards, statistical reporting, past & present analysis, predictive analysis, data discovery, dynamic or self-service reporting.
9. Measuring change…
…monitoring metrics such us reporting period and forecasting times, forecast accuracy, dedicated FTEs, other quantitative and qualitative benefits in the decision-making process, progress and adoption of analytics techniques and models in the organization.
10. Keeping the mantra in mind: Innovation is the future…
…adventuring to test new ways of working such as Agile Finance for Transformation and Kanban Finance for Business As Usual, as applied in everis proprietary methodology. Some 80% of CFOs think that more focus should be placed on innovation, or at least on automating and speeding up time-to-market of the information provided.
DATA-DRIVEN COMPANIES know that and know how to harness the POWER OF DATA AND ANALYTICS in every stage of the innovation process to outdo their competitors.
This necessarily begins with a shift in mindset, one that advocates organizational change to support analytics initiatives and fully capitalize on their potential. To this end, the necessary talent must be attracted and retained, and resources deployed to structure and implement transformation plans across the board.
