Welcome to Monday! This was one of those weekends you want to tell people about—good times with those who are important to you. Rest … no, I mean real rest … and a chance to recharge just a bit. Then first thing this morning, you received a phone call that turns your day from “ease into Monday” to “hair completely and utterly on fire!” 

Your team did not come through on the commitment you made last week, and this morning the customer is letting you hear about it. You scramble through the file, trying your best to put the pieces together, and begin to realize that not only did the team not follow through as promised, but there also seems to be little to no record in the system of the last week. No dates, no notes, no costs, no plans, no nothing! Dang it, even the work to be completed over the weekend was just communicated verbally and not entered into the system (but you can only look in the mirror for that one). 

Deep breath, my friend. Fix the problem; you know what to do. After that’s done, let’s talk about the real problem—you have bad data. The story is incomplete and full of holes. Filling in the gaps to piece together the narrative may cost more time than it’s worth but without some change, the cycle will begin again. 

You can have a new start, tell a better story. Sure it takes hard work, but that’s what got you here anyway. Let’s talk through the risks of bad data and look at some solutions to get things back on track.

What is the cost of bad data?

Increased financial expenses 

Poor data can cost your company both directly and indirectly. In the absence of the right information, you can find yourself spending extra money to dig yourself out of a poorly performing project, whether it be ordering materials a second time or assigning more labor than expected to drag the project across the finish line. The indirect and sometimes hidden costs begin to pile up as well. As the old saying goes, time is money. What else could you or your staff be doing with the time you are using to piece together disparate data in an attempt to make a reasonable story? Playing detective on a broken file can be a labor intensive and frustrating undertaking.

Flawed insights 

Bad data will lead to poor decision making. Your project manager may believe they have more money left in the budget, because expenses being entered into the system are lagging. The shower surround will be ready for the shower door install on Friday, but the materials have been backordered and the tile setter hasn’t even started yet. Even more worrisome is when an employee or process looks successful and profitable on the surface but is proven to be just the opposite with more complete data. Further investment in people or procedures can occur without justification for the expense.  

Lack of efficiency 

Most companies don’t find themselves listed in the Fortune 500 and are always trying to do more with less. The resources and expertise available in your company to fuel profit and potential growth are among your most valuable assets, but they are limited. Instead of looking forward and pushing toward being better, many companies find themselves looking backward as bad data pushes the team to constantly sift through the pieces in attempts to make a reasonable whole.

Organizational bottlenecks 

Bad data and poor systems create clogs in the process. I can think back to times in my career where I identified a problem and assigned a specific resource to fix that singular issue. In the short term, I fixed the issue but inadvertently created a bottleneck where that one person had to touch every file, and if they were backed up, the whole process slowed to a crawl. Instead, what I should have done was identify the root of the problem and fix the system.

How to fix bad data?

Accept the reality 

Like it or not, you have bad data. It happens to the best of us! From experience, I have found that rather than trying to convince ourselves that we don’t have a problem, understand that we do and create a plan to fix it—for today and tomorrow. If you haven’t realized it yet, let me be the first to break it to you: good data practices take ongoing efforts and regular rhythm. You will need to be ever diligent to ensure that the data works for you in the long term.

Take the time 

This will take longer than you expect but take the time that is required to get it right. A champion in the organization should be assigned to drive the process. It cannot always be you, but you have to cheerlead the process, as painful as it may seem at the onset. The investment you make now will pay its dividends downline when you have the right answers to the right questions available at your fingertips.

Improve data collection and implement data quality checks  

Create a checklist; draft SOPs around call intakes; dictate how often employees should update a file as it works its way through the project lifecycle. Create a system of audits that will help you identify and correct gaps in real time. Reconciliation is significantly easier on a daily or weekly basis rather than waiting until the end of month, which may end up being too late anyhow. Business moves fast, and if we wait to make corrections or fill in the gaps, bad data can build into more bad data.

Educate everyone 

People work better when they understand the why. Think about this scenario: you tell your intake personnel that they need to capture the referral source on every project, every time. Yet, it still is missed on occasion, which is frustrating, I know! What if, instead, you explained how the information can allow you to better focus your marketing efforts and ensure that the dollars spent to spread the company message is in front of the right people at the right time? What if you took it to the next level and showed your intake person how the agent you have taken to golf four times this year has given you two leads, neither of which converted into a job? Or how the team sponsorship has led to eight new leads within the past quarter? By connecting a few dots, you will raise the value of entering a key piece of data into the system and drive better results.

Bad data happens. Even the best systems will fail over time if they are poorly maintained. Don’t let it throw you off your game, but don’t settle for it either. Whether it’s human error or a simple lack of training, use the resources you have available to make it one step better today. A little time spent with your data now can pay massive dividends downline. Good decisions that drive great results are counting on it.