Understanding your problem/ Identifying your problem (and finding a solution that works)
Finding the right tech option for your organization can be challenging. There are a variety of boxed products on the market designed to offer solutions for common data-related business problems. The question is how do you know these products are what you need if you don’t really understand what your problem is?
Problem vs symptoms
Often times leaders will attempt to remedy the symptoms of a problem in the workplace but not really address the underlying issue causing it. To diagnose what is going on, you need to get under the surface and look beyond the symptoms. Yet, this can be a gradual process and most companies want a quick solution.
To best understand the problem, it is important to understand the individuals involved. What are your employees doing and being asked to do? Often times taking data in and reporting on it are two separate issues that have unique challenges.
To get to the root of the problem, ask yourself several why questions. This will help you discern between the symptom, which is the sign of a problem, and the problem itself.
For example, if a puddle of water is found on a warehouse floor mopping it up is certainly one way to tackle the issue. However, asking why the water is there can help locate a broken pipe. Furthermore, asking why the pipe broke can uncover an issue with the water temperature or pipe components. Ultimately, discovering the why can help organizations sort out the fundamental problem. From there, you can eliminate it and prevent any further symptoms from appearing.
Unfortunately, according to the Harvard Business Review (HBR), many businesses are failing when it comes to using data effectively. This is despite the fact many are investing over $50 million in big data and artificial intelligence technologies. One of the major factors for this is that they are likely trying to treat the symptoms of the problem rather than get to the root of it.
It is a challenge to find a single product that solves all your problems. The solution depends on how big the problem is and how much data is involved. Yet, by coming to understand what the underlying problem is, it is possible to find a solution that fixes it and makes the symptoms disappear as well.
Solving the problem
After you have been able to identify what the problem really is by examining the symptoms and digging deeper, it is time to find a solution.
Starting by defining what people in the organization are doing with data. What they need from it can help clarify what software might be beneficial. Due to the variety of software products on the market, it is crucial that you fully understand what you need to solve your data problem. This will help you invest wisely in data solutions.
One of the best ways to integrate tech solutions effectively is to make data democratized, which means it is available for everyone to use. This may require customization for specific groups within the organization so that they receive the data in a way that is most useful for them. For example, the data that is most relevant to your sales team is not the same information that your marketing team will need.
Be prepared that data transformation for your organization can fundamentally change your business. Rather than becoming an additional feature of your company, data becomes central to everything you do. Moreover, Gartner has predicted that by next year, 80% of organizations will realize their need to become more data-driven.
Although needs can change in any business, the need to be data-driven will continue to grow. This means that additional or new demands will be ongoing for whatever tech solution you choose. In fact, they may come to the surface because of the tech you have opted to employ.
NBS Consulting has deep familiarity with the challenges that arise when identifying what problem to solve. We assist companies to identify, develop and execute projects around the problem you are choosing to solve. Reach out to us today at email@example.com for a free consultation on how to use data more effectively.