Article 'stand-up' Each student will be assigned an article as additional reading. Sometime during the respective class period, an assigned student will be randomly selected to present a short 3- 5 min summary of the article incl. source, date, author(s), the main points in the article, how the articles content relates to that in the respective Strategic challenges chapter, and what about the article the student enjoyed or appreciated the most, and why. Do not read the article to the class during the 'standup' selected quotes are fine. As the name implies, students will stand during their presentation. The students ability to present the required information will be assessed as part of the participation grade A.

Finance teams will need efficient ways to generate and disseminate real-time forecasts that reflect rapidly changing circumstances. models. A company can use data from these indexes must also collaborate to ensure that employees at all and machine learning to detect patterns, trends. levels are trained to understand the systems and seasonality in users web-search behavior. Then required to collect access, and maintain the data it can feed these data back into its forecasting models to help establish targets. The total number Operations and organization. It won't matter how of variables in such forecasting efforts can clean the data are or how easy they are to access exceed 1.000. If the finance function doesn't have the right opera- tional and organizational structure to implement advanced analytics programs. It needs supporting Implementation: Scaling up processes and protocols to gather insights from Once opportunities to create value have been ide the data, share those insights, and develop action tified and benefits targeted organizations plans in concert with business-unit leaders Implementing advanced analytics and machine These structures might include strategic data envie learning at scale must emphasize three ronments, such as data lakes.enterprise layers, basic requirements: cloud platforms, visualization tools, and development sandboxes Clean, accessible data. Perhaps more than other functional groups, a finance organization The finance team will also need to focus on cultural Implementing or scaling up an advanced-analytics issues--for instance, by highlighting lighthouse program must ensure the fidelity and accuracy cases that might inspire other parts of the business of data. When business information isn't adequately to use advanced analytics. Leaders in one sourced, copregated, reconciled, or cleaned pharmaceutical company started with one smal staffers spend more time on tasks that don't add group charged with monitoring data on clinical value and less on important strategy-oriented trials. The company then gave a slightly larger group discussions. As one data analyst told us, availability of users access to these data so it could determine is not an issue in most companies accessibility how efficient and effective its clinical trial process is the bigger concern. At one chemical company, was. Eventually it built out modules that thousands for instance, the machine-learning models of users could access could not read unorganized data sets, so certain key performance factors were excluded from Talent. The company and the finance team will likely the results. The data in question had to be cleaned need to hire data scientists, data engineers up and reingested, which added time to the and data-visualization specialists. They will probably modeling process need to retrain internal staffers to work with data specialists, as well. Otherwise, execution will stall. Finance leaders must work with IT and the business to set the ground rules for data usage-what good In most cases, this will be difficult. Traditional data look like, who owns them, who can access them, organizations may not be able to lure top digital and and so forth. Finance, IT, and business leaders finance talent. Smaller companies that do not have the payrolls to bring on data scientists and financial analytics programs. Project teams and senior analysts full time will have to determine how much leaders may suspect that their companies could analytics work to outsource and how much to keep streamline processes or export products more in-house. One consideration is sustainability: efficiently, for example, but the CFO can put these models and regressions are never 100 percent stable ideas in the proper context. At investor days or in over time, so they will need to be adjusted quarterly earnings reports, C-suite leaders tend to continually, which strengthens the case for in-house talk about analytics programs in broad terms-for capabilities. It may be worth convening a small instance, how they will change the industry, how the hybrid group of finance and digital professionals to company will work with customers differently. work on no-regrets projects that make the case or how digitization will affect the financials. What's for deeper investments in digital talent. missing is the impact for investors, and CFOs can supply that. In doing so, they can help fulfill the oft- In many companies, data governance can involve repeated request, from both senior management significant effort, which may be better managed and the board, that they serve not only as traditional in-house. A global manufacturing company, for transaction managers but also as key strategy example, developed its own in-house programs and partners and as value managers. certifications for training digital translators and data scientists. The company offers multiple modules Of course. CFOs cannot lead digital transformations and curriculums at all levels of the organization, all alone; they should serve as global conveners and more than 300 managers and employees have and collaborators, encouraging everyone, including gone through the program, which mitigated the leaders in IT, sales and marketing, to own need for an extended recruiting effort. the process. Vision: The CFO in the lead Leaders of companies must have a clear vision of CFOs on the cutting edge of advanced analytics how they will use new technologies. In our experience, are positioning themselves not just as forward- CFOs are well positioned to provide that vision thinking finance leaders but also as valued business and to lead the widespread adoption of advanced partners to other leaders in their companies. analytics. They have most of the necessary data Those who aren't will need to think about how ana- in hand, as well as the traditional quantitative lytics programs could change the way they work- expertise to assess the real value to be gained from and then lead by example. Holger Hrtgen (Holger_Huertgen@McKinsey.com) is a partner in McKinsey's Dusseldorf office, Frank Plaschke (Frank_Plaschke@McKinsey.com) is a partner in the Munich office, Karolina Sauer-Sidor (Karolina_Saver-Sidor@McKinsey.com) is a partner in the Vienna office, and Nils Wittmann (Nils_Wittmann@McKinsey.com is an expert in the Hamburg office. The authors wish to thank Davide Grande and Sebastian Kerkhoff for their contributions to this article