What You Need for Planning: Software Package or Platform?

As I build planning tools and deliver consulting projects I have started thinking about an interesting question.

Is it really planning software that companies need? A software package with well-defined workflow, logic and user interface that handles data, presents historical performance and future projections to users, lets them decide a course of action for their business…  Being ‘well-defined’ is the key here, and in a changing business environment very few planning processes are so:

• They could be well-defined today but will they be tomorrow? They may not be even relevant in the future.

• If a re-organization effort artificially removes/introduces product categories?

• When a company decides to expand into new geographies & channels?

• Or when a supply chain is redesigned by adding a new distribution center?

In addition to these there is also a new challenge/opportunity redefining many industries as more data are available to companies. Here is another plausible scenario: while in pursuit of predictiveness what if the talented data scientist in your team correlates a new data set (let’s say mall traffic projections) with your forecast and shows that you can explain your demand reasonably well with this new relationship. In many companies it would be years before this information is leveraged as a planning capability (if at all). Unless… 

Unless they have invested into building a ‘planning platform’. The definition is probably subjective (and quite possibly ever-evolving), but here is my version of it:

• The most critical component is the scalability & availability of all data sources to any application. In other words, you should be able to add new tables / fields / rows into your platform while letting all applications access source & staging tables (with certain limitations not to keep admins on their toes all the time). By the nature of planning (i.e., decisions & physical flow of goods can be modeled as time series) I think relational databases would be sufficient for most cases; however, a NoSQL database could be needed (and increasingly more) as companies explore social networks and other unstructured data sources.

• Similarly, a scalable analytics engine is needed (on the server side) in which all algorithms reside & crunch through data sources.

• A sandbox environment where your data scientists can experiment with next generation algorithms.

• Because adapting to changing conditions is a fundamental component, the business intelligence (BI) & decision making (DM) capabilities somehow need to merge in the planning platform. Traditionally BI (one-way information flow) and DM (two-way information flow) tools are separated from each other, essentially due to the complexity of the latter (i.e., data architecture and workflow).  Nevertheless, I believe it is possible to build a flexible architecture if you are OK with some coding effort associated with each change.

• A cloud-based architecture might be the ideal platform for the above definition. Alternatively, if it is a reasonably sized company you could achieve the same with an onsite server.  And I could even argue that the combination of SQL, R, and Excel is the ultimate planning platform for many small companies.

Because change is the only constant in business, the emphasis is really on the accessibility of data sources & flexibility of overall architecture (databases as well as user-interface). A planning platform will require a more hands-on approach than some companies may prefer in terms of coding & maintenance efforts, but I believe this would be the most effective approach to planning in the near future.

Özgür

Originally posted: April, 2014