From my perspective, supply chain management (SCM) and sales and operations planning (S&OP) are two of the most underappreciated disciplines of modern corporate management. Properly applied, they can improve performance and competitiveness by increasing customer satisfaction and reducing costs. A combination of more capable information technology with advances in operations research and analytics has made managing supply and demand chains potentially more impactful by making them more flexible and adaptable to market conditions. Consequently, companies can enhance profitability, reduce working capital and improve customer satisfaction by providing more reliable service.
The Strata Data Conference is changing and it’s changing in a good way. At the recent Strata Data Conference in New York, Mike Olson, chief strategy officer at Cloudera, which co-sponsored the event, commented that at prior events we used to talk about the “Hadoop zoo animals,” meaning the various components of the Hadoop ecosystem of which I have written previously. Following last fall’s Strata event, I observed that the conference was evolving to focus on the use of data. Advancing that evolution, this year’s event focused on a particular type of usage: artificial intelligence (AI) and machine learning. The evolution from a focus on zoo animals to a focus on business value using advanced analytics shows further maturation of the big data market.
There’s been some speculation in the market that Hadoop may be disappearing. Some of this speculation has been driven by vendors that have recently downplayed Hadoop in their marketing efforts. For example, the Strata+Hadoop World conference is now known as the Strata Data Conference. The Hadoop Summit is now known as the Dataworks Summit. In Cloudera’s S-1 filing with the SEC for its initial public offering, the term “Hadoop” appears only 14 times, while the term “machine learning” appears 83 times. So, if some of the vendors that created the market appear to be pivoting away from Hadoop, does your organization need to do something similar, or is there a role for Hadoop in your IT architecture?
The application of artificial intelligence (AI) and machine learning (ML) to business computing will have a profound impact on white collar professions. This is especially true in heavily rules-based functions such as accounting. Companies recognize the transformational potential of AI and ML, but the progression and pace of the adoption of these technologies is unclear. Some applications of AI and ML are already in use but others are a decade or more away from replacing human tasks.
In 2016 Unit4 acquired Prevero, a financial performance management software company. The acquisition reflects a trend toward the convergence of transactional and analytical business applications. ERP and financial management software vendors increasingly are adding analytic capabilities – especially in financial performance management (FPM) – to the core functions of transaction processing and accounting in order to broaden the scope of their offerings. The integration of transaction processing and analytical software is especially valuable to Unit4’s core customer base of midsize organizations, which we define as those with 100 to 1,000 employees. Midsize entities have almost the same systems requirements as larger ones but lack the resources the latter enjoy.
Topics: Marketing, Office of Finance, Continuous Planning, Analytics, Business Intelligence, Cloud Computing, Collaboration, Workforce Management, Financial Performance Management, FPM, Work and Resource Management, Operations & Supply Chain, Sales Planning and Analytics