Accomplishing any task involves knocking off a series of intermediate activities in a predefined sequence. We can simply term this as workflow – the flow of events to get work done. This is applicable to any context that involves accomplishing a task. A manufacturing company procures raw material, subjects this material to various change and ultimately produces a marketable product. A software firm accepts requirements, analyses and builds necessary code, deploys it on the customer’s servers and runs it successfully. In essence, we can characterize almost every work using workflow data structure and diagrammatically represent it.
Do workflows have any relevance when it comes to spreadsheets? Can we begin to see our day-to-day spreadsheet tasks in terms of workflows? As it turns out, we can. And it makes perfect business sense to do so. Because we can attribute all our spreadsheet task to an intended outcome that we need to accomplish.
Realizing a workflow data structure
Here are a few general pointers that will help us build workflows into spreadsheets:
1. Start with the business problem
To begin building the workflow, we need to understand the problem that we are trying to solve. Let us discuss this with the help of a small example. Consider a sales team manager. His team members work on sales leads and generate individual datasets. But there isn’t a current system in place that will help the team manager with performance metrics such as lead conversion ratio. So the problem for him to solve here is that he needs to come up with a setup that will consolidate all the leads in one place, and then build reports from this data.
2. Identify the individual steps that need to be accomplished
In order to get to the final result, we need to successfully finish the intermediate steps. So, to do that, we need to establish these steps first. Continuing with the example, let us assume there are four members within the sales team, one for each region. In order for the data to flow from individual leads spreadsheets to a consolidated spreadsheet, we need to create four connections. Setting up each of these connections is an individual step operating in parallel. The next subsequent step is to generate performance indexes from this consolidated data set. It helps us achieve more clarity if we can depict these steps on a piece of paper before we proceed further.
3. Create the workflow
Now that we identified all the possible steps, we can go ahead and create them. We start with the very first step in the flow, then move on to the subsequent steps. To create connections in Google Sheets, we may use built-in features such as the IMPORTRANGE function. Or, automatically connect our spreadsheets with Sheetgo. Once the data is consolidated, the team manager may use mathematical or statistical functions to arrive at the performance metrics as part of the final step.
Example: Workflow Structure
4. Test the workflow
Things can go wrong, especially if we don’t pay attention to how the individual step is working. For instance, as part of the second step, the data isn’t flowing into the destination file as desired. In that case, the final result isn’t the exact picture of the actual data. So it is very essential that we validate each step of the workflow.
5. Refine the workflow
The process is now set and working well. But there will be times when we need to refine it, although not necessarily from scratch. For example, let’s say a new member joined the sales team. In that case, the manager has to create an additional step to connect the new member’s data to the consolidated file. Or, maybe, the higher management wants to see a very specific set of performance metrics. In that case, the team manager will have to create a new step after the previous final step, just to narrow down the results.
