If you’re looking for a new data analysis solution, you probably have prestigious names on your list, and maybe a few smaller, boutique firms. It’s not easy to compare apples-to-apples, because there’s so much technical jargon to wade through – not to mention lofty promises.
So what’s the best way to assess different companies and decide what size firm you want to work with? Here are some factors to consider:
- Level of task complexity – Do you need something totally custom, or could an out-of-the-box solution meet your needs? Carefully evaluate what you are hoping this new system will do, and any particular requirements that are specific to your company or your industry. For example, all employers have to track employee time in some way, but off-the-shelf software is probably not adequate for companies that operate in multiple countries with different languages, currencies, and regulatory requirements. Some big data firms excel at complexity and have seen it all before. However, smaller firms can often be more flexible, and can tailor their solutions to your needs.
- In-house expertise – Do you have people already on your team who know how to modify or fix the software you are considering? If you don’t, you might be drawn to a larger company that offers a formal support structure for its products. I’ve seen too many companies stay within their comfort zone when it comes to technology because they were burned in the past. A prior implementation didn’t work out well, and the support they were promised turned out to be slow and impersonal. Understandably, these companies are reluctant to try something totally new.When the solution is intuitive and properly customized by a knowledgeable software consultant, your team will be able to make a smooth transition – even if they had no prior experience with it. So don’t let a lack of familiarity with a new system be a deal-breaker. Just make sure that the software company or consultant you choose can provide the fast, personalized support you need to make the implementation successful. When you call, you should get a dedicated person who knows your business and solves your problems — not somebody in a call center providing generic answers.
- Legacy system integration – Software systems are not effective when used in isolation, especially when large organizations are involved. Your company may already have a complex web of applications that this new system would need to “talk” to. For example, would this system need to pull data from multiple sources, such as your accounting system, your payroll/ HR systems, and key databases? What will it do with all this data that will improve efficiency and the bottom line? Understandably, many companies prefer to work with the same firm who built their other systems to ensure maximum compatibility. However, it is important to evaluate those legacy systems and confirm that they are still up to the job. You may find that technology has evolved considerably since those other solutions were put in place, and better options may be available.
- Robust discovery process – Does your company have a lengthy procurement process that involves a lot of research and evaluation before a decision is made? If so, you may find it easier to work with a larger company that has the staffing to provide the documentation needed. In addition, large firms can study user patterns in a deeper way, because they have a much broader client base. But, some smaller firms can surprise you in this area. So ask how they handle the discovery process and if they have partners that can handle in-depth research.
- Budget – Big corporations prepared to make substantial investments in their technology may prefer larger firms that are used to operating at a similar scale. At the same time, these large firms have a tendency to treat businesses with smaller budgets like afterthoughts. If you run a small business and you’d rather not feel like a tiny fish in a vast corporate pond, you may be happier going with a boutique firm for consulting and data analytics.
Hopefully, we’ve given you some things to consider when choosing your next data systems partner.
