In his latest post on the Actian corporation hosted Data Integration blog,data management industry analyst, Robin Bloor laid out his vision of data flow architecture. He wrote, “We organize software within networks of computers to run applications (i.e., provide capability) for the benefit of users and the organization as a whole. Exactly how we do this is determined by the workloads and the service levels we try to meet. Different applications have different workloads. This whole activity is complicated by the fact that, nowadays, most of these applications pass information or even commands to each other. For that reason, even though the computer hardware needed for most applications is not particularly expensive, we cannot build applications within silos in the way that we once did. It’s now about networks and grids of computers.”
Bloor said, “The natural outcome of successfully analyzing a collection of event data is the discovery of actionable knowledge.” He went on to say, “Data analysis is thus a two-step activity. The first step is knowledge discovery, which involves iterative analysis on mountains of data to discover useful knowledge. The second step is knowledge implementation, which may also involve on-going analytical activity on critical data but also involves the implementation of the knowledge.” Read more->
Are you the type of person who easily assesses all angles of a decision and calmly arrives at the point of clarity? Or are you the type of person who is overwhelmed by all of the information you need to consider, becoming frozen by indecision, as if you are a deer in the headlights? Does how well you navigate decision-making depend on the type of decision you need to make? Maybe you find making big decisions easy, but smaller ones, like what to order for dinner, leave you stymied.
Effective decision-making requires much more than just the ability to gather and process information. It requires focusing on the very core of the decision, rather than getting mired in the details that can so often derail good decision-making.
What impact does clear decision-making have on companies in the collections business? Let’s start with the decision of which collection software to use. Artiva, DAKCS, CollectOne, Windebt, Titanium ORE (DM9) and FACS are some of the most frequently used credit and collections software used in the industry. Which one is best for your company? Let’s answer that with a question. What is the single most important thing your business needs this software to do? Is it:
2. Process automation
3. Vendor integrations
4. User friendly
What’s key to making the right technology decision, is to focus on the mission critical business outcome.
Once you’ve identified the primary business goal for purchasing collections software, you evaluate each product’s ability to achieve that goal. Software bells and whistles that don’t help your company achieve the primary outcome are extraneous details that should be tossed out. Next, look at other key factors that will affect your company’s ability to execute on your core business. What resources does your company have available to integrate, implement and maintain and the software? Which software syncs most closely with your team’s capabilities?
Your company may have a few other key factors to include in the software selection process. Prioritize them and then score each software solution for effectiveness with those factors.
Finally, there’s budget. It’s last because addressing the primary goal and key factors are mission critical to a clear decision-making process. Without the information about implementation and resources required to maintain the new software, total cost of ownership (TCO) cannot be determined. Quantifying the TCO of software is far more accurate than the purchase price. Focusing on gathering the best information about the primary goals and key factors will provide the path to crystal clear decision-making.