We all want to be in a work environment where our talents and expertise can be exercised efficiently and not feel bogged down by maintaining the tools for the job. We feel best when the routine steps necessary to produce results — our workflow — proceeds without a hitch. The steps that make up a workflow can be our actions, can involve others in our organization, and may include transactions with external actors. They can be equally digital or physical.
While the workflow concept has existed for centuries, our present understanding started when automobile inventor Henry Ford created the assembly line in 1913. Previously, automobiles were assembled unit-by-unit instead of part-by-part. This was important because by coming up with the idea of a linear assembly, Ford sped up the process of mass production. In turn, that reduced costs, improved productivity, and revolutionized how manual labour was performed.
Then, during World War II, complex government and military projects coupled with a shrinking war-time labour supply forced the industry into finding new ways of organizing work. Managers began to introduce draft registration cards, decimal file systems and complex network diagrams called PERT charts. These resulted in greater control over incredibly complex projects. After the war, these innovations spread to all kinds of different industries. Business leaders continued searching for management strategies to optimize their company’s productivity and give them an edge in a competitive world.
The second breakthrough in workflow development occurred in the 1980s, spurred on by thought leaders who addressed two major criticisms of workflows at the time. The first was that all this efficiency had dehumanized jobs in factories and offices. People were unhappy. And second, that these complex systems were inflexible and unresponsive to the changing demands of the industry. Workflows that were initially designed for factories to produce more cars were inefficient in the office or the home, where the personal computing revolution was causing lightning-fast changes to output and communication.
Emerging theories such as Total Quality Management and Six Sigma addressed these problems of workflow fit and user happiness. As a result, work became more human-centred, allowed individual customization, and linked planning more directly with execution.
This dramatic evolution has changed workflows from factory tool to the familiar and ubiquitous digital and human systems we use today.
Now, workflows are transforming once more. The advent of real-time data, cloud-based reporting, and online collaboration have caused an upheaval greater even than the personal computing revolution of the ’80s and ’90s. As a result, data has become an enormous part of our work, and developing an efficient workflow is now the critical driver of success.
But several factors work against efficient, effective data management. For one, location: we’re now able to work outside the office more frequently — at home, on the subway, even while travelling abroad. Consequently, we need access to our data at any time, from any place. Social media engagements, payments, production monitoring, consumer behaviour, GIS mapping, project milestones. We gather data for quality control, analysis, market research, and more, accessed by more people from more places.
Then you have a multitude of different formats. Technical information such as geospatial maps or engineering drawings require specialized software systems, and as more technical siloes are created, gathering and storing data becomes much more complex. Many formats are incompatible with each other, and workers can’t use a single, ordinary piece of software to read them.
In this article, we’ll share some strategies for optimizing workflows that must face the challenges posed by complex data. We’re going to focus specifically on internal informational systems. These are best typified by emails, reports, workflow management software (WMS), Enterprise Resource Management and Planning systems (ERMs and ERPs), data collection forms, presentations and everything involved in the collection of and distribution of tasks, information, work, and results.
Research in data management is ongoing, but the rapid evolution of technology has kept companies on the back foot, playing catch-up and often losing. You know the symptoms: getting bogged down by too many apps, not accessing your files, or drowning in versions and collaboration tools.
As data workflow specialists, we’re here to help you see a better way. Before hiring consultants or buying more software, there is a lot you can do to get a handle on your workflow yourself. Let’s dive in.
The desire to evaluate the data workflow within a company doesn’t come out of anywhere. More often than not, troubling issues or perhaps even a crisis bump such an examination to the top of the priority list. In this case, it’s essential to block off sufficient time for a thorough analysis. Perhaps an initial evaluation can take place after a project has been completed, where it can be part of an extended project post-mortem meeting.
How much time? Consider location, people, and touchpoints. The more of each you have, the greater the task of organizing them. Do these people work together or separately? How many people are involved in the workflow? How often do they have to send or receive information (touchpoints)? You will need to involve each stakeholder separately and engage them as a group. Make sure you include peripheral parties in your understanding of the scope. For example, a project management workflow involves not only the project manager but also the contractors they manage and the executives they report to.
You’ll need to create an environment where your team can openly discuss issues without assigning blame. Depending on the personalities that make your staff, you may also need to lead them in acknowledging that problems even exist. This is a crucial step because unless your team accept the reality of these problems, their commitment to resolving them together will remain low. When everyone can see that the source of friction is a workflow wrinkle (and not each other), they can start to imagine a better way forward.
To better identify and resolve pain points in your workflow, you’ll need to visualize your data funnel as a part of your workflow. Tools such as Miro, Sketchboard, or SimpleDiagrams are perfect for this.
Start by figuring out all your data gathering points — where, when, and how data is collected, as well as by whom. Next, trace how that data is being transferred to the next step. Where does it go after collection? Who touches it? This transfer could be in the form of an email, an app, or a phone call. It could cover initial collection, storage, collation, analysis, or reporting.
Continue tracking all subsequent steps until the data is retired. When you reach this stage, go through the process again from the perspective of records management. Once you have all the parts of your data funnel visualized, you can retroactively trace the exact moments it gets corrupted, delayed, or missing. Locating pain points in your data workflow by mapping your data funnel makes them easier to resolve and gives you a better idea of how your company operates.
Now that you have a map of your pain points, you can find similar issues and group them. This final step of understanding will give a clear picture of what you can change. It’s essential to get as high-up a view of the problem as possible, rather than trying to solve each detail separately, or you may wind up introducing too many new systems and have a worse mess than when you started.
If your stakeholders are struggling with too much manual entry, copying and pasting information from one place to another, look for opportunities to automate and integrate. Create connections between software platforms to cut down on work.
Access issues, such as not finding a document or response, are usually a result of poor storage practices. Is it one particular type of data or communication that is being lost, or all of them? You may need to upgrade or modify your database to accommodate the users’ needs better.
A lack of transparency — unable to trace where the information came from or whether it is valid — is a more challenging issue that often needs expert input. But good records management and minimizing manual entry goes a long way toward providing a “paper trail” to follow in an emergency.
Gatekeeping issues, where staff have to manually distribute information from a technical silo or private data cache, are also tricky and may require an aggregation solution or integration.
Once you’ve located the pain points and developed solutions to resolve them with your team, it’s vital to create a set of standard operating procedures, or SOPs, to ensure improvements to the workflow are implemented and maintained. SOPs are step-by-step documentation of work-related tasks and how to do them correctly. Adopting a specific file-naming system or a series of weekly security checks are some examples. Well-conceived SOPs that clearly explain what and why things are to be done in a certain way remove any guesswork necessary to complete assignments. SOPs give managers the ability to maintain a high level of quality work with little supervision. Businesses from every industry and of every size can benefit from implementing SOPs to ensure consistent quality control, worker safety, and operational efficiency. In addition, it provides organizations with the chance to locate and resolve future issues more quickly.
One option for implementing SOP’s is to use dedicated SOP software, and there are plenty of these on the market. They vary in pricing, learnability, ease of use, and upgradeability. What should one be looking for in SOP software? It should be versatile and uncomplicated. Something that gives you a standard approach to every step of the documentation process, including creation, editing, approval, adjustment, and rewriting. Lastly, depending on the type of work and the workflow involved, further on-site training may be needed to reinforce the SOPs put in place.
Another option, and often a more effective one, is to integrate your SOP’s into the software tools your team is already using. This usually requires some custom work on your software provider but will allow you to enforce SOP’s as staff and contractors go through the workflow. Some examples of how software can help to enforce SOP’s is the use of mandatory fields, automatic changelogs, dropdown options instead of text fields, guided step-by-step forms, single sign-on (SSO) protocols, storage systems that facilitate filtering, and user permissions that block problematic access conflicts.
Have a plan to gather feedback from your team after the solutions created have been implemented. This will allow you to see whether issues in the data workflow have been resolved to your satisfaction. Feedback can be categorized into two types: formal and informal. Examples of formal feedback include surveys, structured team meetings, and regular one-on-one conversations with managers and employees. Informal forms of feedback take place in the form of casual interactions, e.g., water cooler chats, in-the-moment conversations and recaps, and group-based settings such as Lunch & Learn events.
How will you be able to recognize high-quality feedback that helps you further improve on the changes you made? Here are some elements to guide you:
Clear: the parameters of any issue are easily understandable
Important: explains why the problem should be prioritized
Timely: the information given is relevant and fresh
Safe: written with a professional tone and avoids blaming others
Open: all parties have a voice in the discussion and outcomes
Solution-focused: identifies attainable goals
Actionable: decision-makers can formulate steps to achieve these goals
Hopefully, this article has given you helpful strategies for improving your data workflow. Optimizing this part of your business is essential if you want to maintain an edge over your competitors now and in the future. However, not all companies are the same. If you feel that your data workflow has reached a degree of complexity beyond what you can manage, consider exploring more advanced data management and collaboration software. You can follow this same process we presented here to find the right fit.