AI Series – Part 2: Data Analysis

2) Data Analysis

I previously discussed “Data as an Asset”. Data analysis and preparation are best approached with this as a company and individual mindset. What this means is that the company teams set up a standardized system and processes and a CoE to manage the data with the same focus and fervor that you do for the services and products you sell. An example of an action (which can become a rule) would be to apply the concepts of proper ‘metadata’ management, naming conventions and auto labeling (Jeff Jonas) to better aggregate your data sets.

Another example is to assess your current data models and put the data in the Right Object! I have seen some companies putting data, triggers, etc into a supportive object like the Account object that should be in a more actionable object (ie. Opportunity or custom object). There are general “supportive” objects and there are “actionable” objects that push a process forward. Know the difference and even change your model (painful I know) if you need to for greater flexibility and to build a more antifragile system. Now is the time to do it before your data really starts to grow.

Once you begin the process of analyzing your data (per industry standards, division, location, etc) your CoE team will need to find a measure in points (per value). This can be accomplished via numerous tools (ie. Appexchange) so you don’t have to go to the trouble of inventing the wheel. For example, ‘Data Quality Analysis Dashboards’ can provide visually driven dashboards to identify deficiencies in your record data from key standard fields.

Just a quick note on system design. You may have to add additional levels of data in your Field Service UI for input as some assets are not equipped to provide the right kind of data needed to make actionable decisions. Third party (ie. Youreka) or custom Dynamic Checklists can work with the asset to provide a balance of value, effort and automation bringing in some deeper data sets to apply to your models. More on this later.

Now to take action…

The next article will cover…

3) Data Collection and Preparation