Digital Transformation: Rapidly Leveraging Digitalization Value

by Kevin White on 8th June 2021

Proof of value is critical for digital “trust” within an organization, and quick wins are a must.

Digital transformation can be seen as a two-step process:

1) Digitize
2) Transform

While simplistic, it allows for parallel activities to occur, taking advantage of available digital data for quick, quantifiable wins.

So, what does “digital” data encompass? Well, for starters, we can define data which is clearly not digital: paper operator logs, stand-alone asset gauges, conversion thumbrules utilized, preventative maintenance sheets, valves without output signals. Digital would include any data which can be tracked digitally, whether manually entered in a spreadsheet, clicked on a web interface, or updated in real time from the process. Reviewing the value of the data, including real time data analysis benefits, cost of manual entry errors, and time lag cost between collection and use, will focus the user on data point selection. This limited list of KEY parameters and their required variables could then be evaluated to determine the gap between current digital state and, ideally, data automation.

OK, so now your key data is digital and you are wondering how it is going to be transformational. Proof of value is critical for digital “trust” within an organization, and quick wins are a must. Immediately upon digitization, the following benefits naturally occur:

1. Timestamp: Data can now be seen in a time relational manner. That simple fact allows various events, parameters, evaluations, and predictions to be aligned along a time scale.

2. Historization: Timestamping allows immediate historization, providing continuously updated averages of real time data points with no human interaction. It provides the ability, as well, to perform agile post mortem discrepancy analysis, focusing on specific data within time ranges.

3. Baseline: Initiating digital data flow also immediately creates a baseline for data. Improvements made by utilizing this data can now be compared to the baseline to show value add. Also, provides feedback when ineffective actions taken, as their will not be an improvement in the parameter.

4. Visibility: Digital data is visible data, eliminating status questions. Whether it is a missing data point, a sensor showing a valve is open, or a temperature continually running high, digitization provides process visibility through various digital signals.

5. Comparisons: Once a digital data point is created, it can immediately be compared to a standard, whether that be an average, control limit, or median. The digital data point instantaneously gains an additional feature, being “good” or “bad”, as far as comparisons go.

Great, digital data provides these 5 instantaneous benefits.  Still sounds like quite a leap to transformational, doesn’t it?  Well, let’s assume something about your process, and then these digitization financial benefits may become more apparent.  Let’s make the assumption that you can put a dollar amount on an hour of time for your process based on scope.  It can include labor hours, machine time, rework delays, downstream logistical impacts, upstream raw material ordering, anything that an hour of deviation could impact financially.  Using that hour valuation rate in $/hr, time now becomes the key parameter for measurements.

Given the following industry agnostic process, we’ll assume an early digital maturity, meaning the process has some digitial data available, some collection occurring, but little automation or cross system communication of data. Simply digitizing indications of start and end of a step provides the initial “standard” which can then be used for deviation comparison. It will also allow visibility of the time between the end of one step and the beginning of another (the “available, but not in use” scenario). Using the valuation rate calculated previously, time deviation can immediately be converted into cost impact (ex. 4 hrs behind standard at a rate of $2500/hr equates to $10k cost for that deviation). This scenario is an example where a simple binary signal (On/Off, Start/ End, Running/ Stopped) can provide the digital information necessary to track and quantify cost impacts in real time.

The best way to determine which data should be digitized is relatively simple: What costs you? and How do you measure that? Showing the visualization of that data and its financial impact will provide true digital transformation.

If you have questions regarding this topic or would like to learn how the EIS Operational Intelligence (OI) team can help operationalize this,
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