Can we level the playing field and admit off the top that everybody, or more appropriately, every organization plans? This has been a mantra of my colleague A.G. Tan for as long as I’ve had the pleasure of working with her, and it’s no less true today than it was 4 1/2 years ago when I heard it for the first time, and no less true spanning the decades of collective experience at QueBIT Consulting. And while some planning is simple (e.g. single GL, single chart of accounts, single data source) and some complex (e.g. multiple companies, consolidations, multiple GLs/charts of accounts, multiple data sources, etc.) at the end of the day, much of the work is the same, it’s a matter of approach and scale and having the right tools to support the plan.
IBM Planning Analytics (TM1) gives us the ability to quickly and effectively prototype a potential business solution demonstrating to stakeholders and others proposed functionalities and capabilities of a design rather than relying on only discussions and theory.
If you are a long time IBM Planning Analytics (TM1) administrator, you may have developed a fondness through the years for a utility called TM1TOP. TM1TOP would tell you what your TM1 Server was up to, which was especially useful if users called to complain that it was “slow” or “hanging”.
We at QueBIT think of Cognos Analytics as more than just a BI tool, but rather as a platform that contains BI tools. Between the introduction of the Exploration tool and visualization insights in the past year, Cognos Analytics has enabled users to explore, understand, model, visualize, and most importantly - share these findings securely with others. This means that the platform socializes data engineers, data architects, analytics professional, process experts, and consumers by keeping each party involved in the process of making actionable decisions with data.
I’ve got a lot of stuff in my office. Your house is filled with a lot of things you might not need. And then there’s that lot# on your beverage can. But what is a lot and why does it matter? How can something as arbitrary as a “lot” have real importance in our everyday lives? In the English language the word “lot” is used for describing a large quantity of items or some grouping or set of items. In operations we define “lots” as groups of goods received or produced.
Even with the onset of Artificial Intelligence (AI)’s recent advancements and perhaps new or at least reiterations of all that it promises, some organizations continue to wait or “put off” any serious investigation of the technology.
In an earlier post (IBM Planning Analytics Data Modelling with Context) I stated that when modeling data as part of a planning analytics solution design, context clues should be developed, through a process referred to as profiling and then “built in” to the data.
In the past, data to be modeled came from a single source and was provided in the same format, typically transactions from a general ledger system. In today’s data driven world, project data can come from a variety of places which, potentially, can influence the data’s possible meaning or value, effect how you model and use it and ultimately, whether it will provide insights the business can in fact leverage.