Most RPA projects don't fail at the coding stage. They fail the moment someone picks the wrong process to automate. It usually sounds reasonable at the time. "This task takes the team 30 hours a week, so let's automate it." But hours spent is only one piece of the picture. A process can eat up a lot of time and still be a poor candidate for a bot, because it's full of judgment calls, messy inputs, or systems that change every month. The cost of getting this wrong is real. EY's Get Ready for Robots report found that as many as 30 to 50% of initial RPA projects fail, even though the technology itself works. Deloitte's 2020 intelligent automation survey named process fragmentation as the top barrier to scaling automation, with only 38% of organizations reporting mature process definitions. IN THIS GUIDE The five questions that predict whether a process is ready for RPA A scorecard you can copy into any spreadsheet How to read the total, plu...
Founders and product leads tend to describe what they want in terms of a technology category. "We need full-stack development." "We're looking for an AI development shop." "We just need someone to handle mobile." Those are reasonable starting points for a search, but they're not actually the useful question. The useful question is what stage the project is actually at, because the right service to hire depends entirely on that, not on which buzzword sounds most impressive in a pitch deck. A quick scan through Bitcot's services overview makes this pretty visible. The categories aren't organized by technology alone, web, mobile, AI, enterprise, they map fairly cleanly onto different points in a company's life: validating an idea, scaling something that's working, or modernizing something old that's holding the business back. Picking the wrong category for your actual stage is one of the more common and expensive mistakes compan...