In part I of this series, we talked about the importance of productivity and speed. 

That puts a lot of pressure on the inspector to be quick — there’s no faster way to have people resent the time you spend “checking boxes” than to take a long time doing it.

Yuck. There are few things more annoying — and detrimental to your organization — than being looked upon as box-checkers. 

But, as important as speed is, there’s more to fixing that problem than doing your inspections faster. If you want to prove that you’re about more than box-checking, drive more processes and results with the inspection data you collect. 

So let's focus on the importance of workflows that generate insights and feed decision-making processes. 

Data maximizes the impact of your processes

A data-driven organization needs to establish workflows that take inspection information and share it with people, organizations, and systems that need it to make better decisions.

Suppose your company provides outsourced sanitization services. Your business workflow might start with a team sanitizing a building. Once they’ve done the work, they check the right boxes or collect other relevant data to prove that they’ve done a high-quality job. 

I’m going to set aside the processes you have for your own scope of work. Let’s focus instead on the fact that, within a data-driven organization, the data you’ve collected needs to drive more action with broader scopes.

• The data you collected might be typed into the billing system to bill a client. 
• A compliance officer might need to review the job information and then keep a permanent copy of it. 
• If you’re lucky, your data will go into a customer relationship management system and a data warehouse. 

Let’s drill into that last bullet. I say “If you’re lucky” because the more your data gets used, the more value people get from it.

So, for instance, it’s good for a sales account manager to know that someone has sanitized her client’s building. That fact can drive her next actions. Since she uses the CRM application, that’s where the data needs to be for her to be well informed.

Similarly, It’s good for analysts to have your information available when they do customer analytics. They can use it to drive decisions about pricing, staffing, equipment, remediation, and other issues. Since they load up their tools with datasets taken from a data warehouse or data marts, they need your data to appear there. If it doesn’t, it has a lot less likelihood of showing up in their analysis. And if it doesn’t show up in their analysis, your business workflows hardly seem to exist.

The power of a workflow is ensuring that your actions — more precisely, the data you collect about the work you do — has an effect on other people’s understanding of the business. If, as the saying goes, 80% of success is showing up, then workflows are important because they make your data “show up.” 

Aside: quality is critical

Having said that, I need to call out the fact that the data needs to be right. 

I personally know account executives who would rather have no data about installations than to have unreliable data, because not knowing something is a lot less embarrassing than “knowing something that ain’t so,” as the saying goes. 

That’s why high-quality data — which you’re going to get from digital collection in ways that you won’t get from paper-based processes — is so important.

Automating impact

Consider five things when trying to become more data-driven. 

1. Capturing better data at the beginning of a workflow. The data capture process is as important as everything that follows, because it’s the way you get high-quality, high-value data to begin with. 
2. Capturing location information every step along the way. If there’s one thing we’ve found over the years, it’s that location data can greatly enrich analysis and decision making — but if you don’t automatically capture it, it’s unlikely to be there when you need it. Adding it in after the fact makes for a lot of lost time.
3. Sharing information with people. People need information in a variety of forms. Some of the best are PDF reports, dynamic maps, and spreadsheets.
4. Sharing information with tools. When people need to do more complex analysis, they use tools like Tableau or Microsoft PowerBI. You’ll want to provide extracts to those tools or, even better, enable the tools to get a shared view of the data whenever they want it. These tools will typically use comma-separated values (CSV), JSON, and the like, although geographic tools will use a variety of “geospatial” formats. 
5. Sharing information with systems. When information needs to be integrated with other processes or to be used for deeper analysis, it needs to be pushed into other systems. This might be a data warehouse, a CRM application, or a business process management platform. These systems will use web service-based APIs, webhooks, and data feeds to integrate your data with their processes. 

By putting your data into a wider context, you’ll be able to understand what’s happening throughout all of your business processes — which will lead to better decision making and a more data-driven organization.