Driving Supply Chain through Analytics
Success in supply chain project IT projects has the probability of the toss of the coin. Today, only one-in-two projects are rated successful by line-of-business users. Despite hard work and many project plans, the success rate is a low. This is a dilemma for most organizations. While projects are carefully selected and analyzed for a Return on Investment (ROI), the rate of success is not as high as companies’ desire.
So, in the design of project portfolios be careful where you tread. When it comes to project success, not all projects have an equal probability. As shown in figure 1, it varies by type of project. Based on a survey of over one hundred respondents, we can see that transactional systems have the greatest probability of meeting business requirements. Why? It is easier. Enterprise Resource Planning (ERP) systems for order management and the supplier management solutions are easier to conceptualize and have a higher probability of success. Supply chain planning systems are the second most likely project type to be successful, but many organizations struggle with how to implement planning systems. The missing gap is usually the understanding of how to use planning in the organization. However, the toughest and most unpredictable—in terms of outcome—are projects focused on analytics.
It is ironic. Companies are crying for analytics. Most data has been stuffed and catalogued into systems, but it is hard to get access to it to use the data. In the words of one of our clients, “It is like Hotel California. The data checks in, but the data does not check out.” In today’s enterprise, people cannot get to data. They are drowning in data and starving for insights. As a result, many revert to spreadsheets and the building of spreadsheet ghettos. It is a work around, but it is not the answer.
Business leaders want analytics projects, and they are critically important, but they have the lowest probability of success. Analytics are one of the hottest investment areas that we are seeing for 2015. Yet, the probability for a successful project is low. How do companies improve the odds? How can line of business leaders drive more success in analytics projects? The research shows that five steps help:
1) Start with education. Analytics means different things to different people. It is about much more than reporting. In the design of systems, try to use in-memory analytics systems with a focus on reporting for selfservice. Try to put the user in the driver’s seat. Reporting systems run by IT are doomed for failure.
2) Importance of visualization. Analytics is an area where the mapping of “to be” and “as is” states is difficult. Most teams do not know what they do not know. As a result, the probability of success in designing fixed format reporting is low. Business users want more flexibility and they want to see and manipulate data. As a result, invest in new forms of visualization. The research shows that projects have a higher success rate if the project has visualization tools.
3) Change the mentality. Invest in small iterative projects. Forget big bang approaches. Build teams to test and learn for the organization within the business. This can be a BI or a functional center of excellence, but invest in building the organizational muscle.
4) Enable portability. Use cloud-based analytics to enable greater portability of data across devices and functions. Avoid analytics that are application-centric. One mistake that companies make is limiting their analytics thinking to ERP-centric analytics approaches. This is problematic because the supply chain is about much, much more than the data in ERP.
5) Provide innovation funding. Fund a center of excellence with some investment funds to experiment with new forms of analytics. When it comes to new forms of analytics, most users do not know what they do not know. Build a case for experimentation in the centers of excellence.
So, the next time that someone asks for you to do work on an analytics project, stop and think. Are you aligned for success? Where are you on these five factors. For most there is an opportunity. Analytics built by IT and used by IT does not define successful outcomes. Instead, engage the business to be true partners and invest resources in defining new outcomes through new forms of analytics with the business. When handed an analytics project, start by driving this understanding. The research shows that it is this type of organizational muscle that drives success in analytics projects.