by Data Driven Decisions Circle

Your Sentient Enterprise Plan Needs God


Context is everything. Context is the reason serious investors require a business plan. Context is the reason the book tells a richer and more rewarding story than the TV movie. We do not often think about context as it relates to data but context is actually the most important data set, helping dramatically improve the usability of the other data sets. Gary Vaynerchuk sums it up nicely: “Content is king, but context is God.” (https://www.garyvaynerchuk.com/content-is-king-but-context-is-god/).  

There is often much ado about the TECHNOLOGY powering a Sentient Enterprise. In the excitement to harness the data and push it through, rarely does an organization consider how to capture, measure and synthesize the context in which the data is born or used. We capture context through process mapping. The term context is attributed to late Middle English from Latin contextus, from con- ‘together’ + texere ‘to weave’. Mapping is a method by which we capture pieces of organizational activity in nodes and weave them together with links. Once captured, we can then apply the other organizational data sets to hyper-specific points of work, down to the piece of paper an employee uses to perform a task. It also allows us to effectively manage unintended outcomes resulting from the changes driven by the fantastic new insights provided by artificial intelligence and machine learning. 

Mapping does not occupy a venerated place in most data science projects, however the product of mapping, a context data set, has been recognized as a determinant factor in implementation frameworks. Per Nilsen and Susanne Bernhardsson (https://bmchealthservres.biomedcentral.com/articles/10.1186/s12913-019-4015-3) identified 12 dimensions of context that influence healthcare implementations. Four dimensions are organizational level determinants (organizational culture and climate; organizational readiness to change; organizational structures; organizational support). One dimension is a personal level determinant, the patient (or in a generalized case, the user). One dimension is the world, or the environment in which we exist (i.e. implementing a healthcare platform in a COVID-19 environment looks very different than the same implementation in early 2019). The remaining six dimensions are general, can apply to the world, the organization or the individual: social relations and support, financial resources, leadership, time availability, feedback and physical environment. 

 

Permit me an example. What might it look like if we used mapping to apply sentient enterprise theory to the process for starting the day?

We could start by brainstorming. Maybe we use a GPS to optimize the routing for weather and traffic or a programmable coffee maker to make coffee at the moment the alarm rings. This sentient stuff is AMAZING. We all pat ourselves on the back and move to the next project....

But wait. Lest we forget that context itself is a data set, and all data must be validated. If we perform a process audit on this workflow, we may find the version depicted in Figure 2 to be more accurate. 
 



Same as before, maybe we use a GPS to optimize the routing for weather and traffic or a programmable coffee maker to make coffee at the moment the alarm rings. 
But wait. 

If we don’t have groceries, our optimized routing may not take us by the café we need to stop at today to get coffee and/or lunch. If the creation of coffee in node C is only triggered by the alarm and does not factor in if we have groceries, we will waste water, coffee and electric making a pot we won’t want to drink without creamer from the grocery store. 

In this simple example, it’s easy to see the root cause of why we are late to work or the electric bill is higher but in a very large data set with a multi-level machine learning model, the errors created by the lack of context may never be discovered. Additionally, the hyper-charged advantage of cloud, machine learning and artificial intelligence would then intensify the inefficiencies and costs we were looking to eradicate in the first place.

When we have mapped the process as it actually happens, the one that includes all the branches of how it may go, we create context and find richer, more complex and more inter-connected ideas. We can then see solutions like using a sleep cycle app aggregating data from our fitness trackers and our sleep sounds to learn the optimum moment to awaken us. When it goes off, it then sends a message to the coffee maker app to tell it to brew coffee. It then checks the digital grocery list and if it’s longer than a certain threshold, it sends our breakfast and lunch order to our favorite café for pickup and adds this as a stop on our route. The more often we do it, the more accurate the predictions become. This the precipice where this sentient stuff really can produce amazing and exponential results. 

This is why we map. Context is the god that makes it amazing.

VSE Inc. invests heavily in process mapping, technology mapping and data mapping as a fundamental and foundational component in the implementation of sentience. Mapping allows us to better understand the business activities and data flow for the terabytes of data generated on a regular basis. Mapping provides context to our content. 

It is only with the vetted, supervised contextualized dataset we transcend having –just- a cool piece of technology to embracing data complexity as an opportunity to serve customers at the next level. That doesn’t mean we don’t have cool technology too. VSE Inc. has layered machine learning and artificial intelligence technologies onto advanced data warehousing capabilities. This enables the enterprise to provide an environment of autonomous decisioning, which, in turn, optimizes human intelligence.

How is this possible? A robust in-house team of business intelligence architects, data engineers, data analysts, and data scientists working in tandem with our full stack developers and system engineers, many of whom have been working together at VSE Inc. for decades. Yep, decades. So day by day, our data gets bigger and we continuously advance our sentient journey, so we also continue to invest in and expand our data driven decisions team. To join us in our ongoing quest for sentience, apply today.