How much do you know about your buying process?
One-third of technology and service provider organizations with artificial intelligence (AI) technology plans said they would invest $1 million or more into these technologies in the next two years, as revealed in a new Gartner survey. Sep 2021
If you are running an enterprise business then it’s not about whether you need AI software, it’s all about “which” one you need. But on the surface, most AI software buyers are not fully aware of their own AI Software qualification, and decision-making processes, so answering the “which” part is a million-dollar question.
A practice of keeping more decision-makers close to the software vendor for selections seems like the silver bullet, but when a lot of stakeholders are involved in buying decisions that they don’t make regularly leads to unintended uncertainty.
On the other side, often software vendors assume buyers know how to buy their AI software, but in most cases that is not true. To accelerate a great sales cycle, AI software vendors need to help their buyers make the purchase and reduce delays. It is important to build confidence and drive through “customer success”.
“What is the next step?” is the most famous question in sales cycles, but that must be eradicated; rather, vendors should honestly talk about their success stories, data points, and propose appropriate actionable steps for buyers to evaluate and make the decision.
Why, What & How:
AI software sales is not a one-man show; buyers need to have a detailed evaluation strategy with “Why”, “What” and “How” questions.
“Why” should come before “how” and “what” even before inviting vendors into the game. Buyers can’t evaluate AI software if they don’t identify the tangible outcome, most of the why part deals with key pain points that are to be resolved.
Working more on the “why” will make it easier to handle the “how” and “what” and eliminate irrelevant situations and surprises. For instance, if buyers like to have more control over their AI software, they can look for a solution that offers supervised learning, self-service, etc, without compromising user experience.
Next is “What”, crafting a custom evaluation strategy will help buyers to do detailed AI software evaluation that includes various aspects such as capabilities, performance, cost, etc, by factoring in their unique business model and requirements. There are few things to be considered even before starting the evaluation process, such as, who owns the evaluation, budget, security, and other enterprise approvals and timeline; this will help buyers to execute the strategy successfully.
Now the “How” part, it’s all about understanding how AI Software works, with a clear understanding of the pain points; the goal is to keep the expected feature list handy with the classification of “must-have” features and “nice-to-have” features. This can be evaluated by doing overview sessions, technical deep-dive demonstrations, workshops, etc with vendors.
Pick out:
When, why, how, & what is done, it’s time to start shortlisting the AI Software that meets the derived feature requirements. In general shortlisting is a daunting process, but that can be simplified with a clear evaluation strategy as mentioned above, buyers can also refer to market research, third-party websites, with user ratings, especially for advanced AI Software for critical automation, it’s okay to spend a fair amount of time with vendors to do workshops to lay the foundation for the next steps such as asking detailed answers for business and technical questions.
Buyers making a lasting partnership with the vendor is critical for success; selecting the right vendor is as important as selecting the right AI software. It is a proven story that buyers selecting a poor vendor with great AI software will not lead them to reach their peak. Since AI software purchases are usually a long-term commitment, it is worth taking some time to study the vendor about their business model, investment strategy, R&D, recommendation, and commitment in doing business.
There are few other items to be factored in before deciding the vendor.
§ Deployment options
§ Deployment timeline
§ Demanded support
§ Data storage
§ Maintenance support
§ Software updates
§ Software training,
§ User materials, etc.
The total cost of ownership:
Gartner says TCO for IT is the cost of “hardware and software acquisition, management and support, communications, end-user expenses, and the opportunity cost of downtime, training, and other productivity losses.”
Beyond direct cost, there could be several hidden costs, detailed pricing review is a must to avoid inconvenience. Few items are license cost, deployment cost, usage cost, ongoing cost, maintenance, and support cost. The goal is to generate the estimation with projection for the next 5 year’s total cost.
Post Deployment:
The game is not yet over, after every new AI software rollout, stakeholders should do surveys, email campaigns, brainstorming, behavior change process even one-on-one feedback to track their employee acceptance and take necessary measures to achieve quick ROI. Keep in touch with the vendor and encourage all kinds of customer support initiatives to enhance the investment value.
