by Terence Leung

The Harvard Business Review article “Big Companies Are Embracing Analytics published in February, 2018, highlighted the results of an annual survey of Big Data and Artificial Intelligent (AI):

  • A majority (76%) of the respondents has already received measurable results from Big Data and Artificial Intelligence projects.
  • Almost all (97%) respondents are investing in such projects.

This is very consistent with the feedback we have gathered. Finance and risk executives across major industries, including financial services, discrete manufacturing, process manufacturing, media, and telecommunication, were highlighting the key challenges of using existing systems to analyze their business and their actions, at an event that I mentioned in a previous LinkedIn blog article.

These executives are having chronic challenges, even though their budgets and resources are not decreasing at all:

  1. Connecting disparate systems and making sense of the business changes from the resulting data are very difficult. The implication is that it may take months to merely set up a new benchmarking initiative and may take even longer to diagnosis the cause of sub-par performance.
  2. Different generations of reporting, business intelligence, and decision-support systems have overcome parts of the challenges. What these generations of systems still cannot do is to give executives enough timely insights to make prompt decisions, especially when new businesses and therefore new analysis are involved.

The executives from this event are taking on analytics initiatives to overcome these challenges. At the event, I presented such a system that is designed to put the analytical power back to Finance and the Business: Balance Sheet of the Future™. The premise is to combine relevant business and risk data from sales, manufacturing, supply chain, HR, quality, etc, and leverage the power of AI and big data to identify improvements with quantified impact. Several examples were mentioned:

  • Supplier optimization: what’s new to help this very established process is the ability to enable the cultivation of strategic suppliers locally and globally, while considering very granular performance and risk information from an extended set of aspects, in order to improve DPO, cost and other metrics.
  • Demand and supply balancing:
  1. the contribution here are the expanded scope and granularity of sales, manufacturing, customer service, and other data;
  2. (in order to supply) scenarios to achieve (and balance) the many goals of the organizations involved.
  • Cash-to-cash cycle: scenarios can be easily constructed to return cash to the balance sheet and to improve underlying processes in terms of cost/agility/satisfaction in sales, procurement, and supply chain.

The business benefits were immediately apparent to the audience and in many ways motivated subsequent discussions on what can be achieved. Some executives were also interested in follow-up discussions on how this can be applied to Sales and Operational planning process, borrowing actions, further procurement optimization, and possible investment decisions.

In this current era of Finance Transformation, Digital Business, and Industry 4.0, planning and re-planning at strategic and operational levels have to be faster and faster, yet more comprehensive and sophisticated. Please join in to this discussion with your comments on how best to leverage this wave of advanced and predictive analytics for business and finance.

And may I make an additional request on a very relevant topic: please participate in this online “2018: The Year of Working Capital” survey, organized by Finance Executives International. As mentioned in the survey introduction, “several senior financial leaders have already pledged that getting working capital to run as efficiently as possible is a top priority for 2018”. How is working capital factored into your decisions for growth, operational improvements, and change

 

A note about the author: At Greenlight Technologies, Terence Leung conceptualizes and manages analytical solutions for Finance, which serves the increasing needs of the Office of the CFO on strategic decision-making critical to processes, operations and transformations.  He was previously at Deloitte Consulting’s Finance, Operations and Strategy practice and at solution providers including i2 Technologies that optimize company performance and processes.  Terence really enjoys interacting with industry practitioners on topics such as business value, technology, business models, and especially analytics.