Operational Analytics in a Recessionary Environment

Lately I have faced an interesting issue with large companies seeking business analytics assistance: how to provide operational predictive analytics to companies that need results in no more than 5-30 days when their budget is extremely limited and access to their data is narrow. The pressures that companies are facing in these recessionary times are:

1. Time-to-Market – companies must turn around in a quarter to show improvement to their investors;
2. Cost-Containment – predictive analytics solutions must be inexpensive to implement; and
3. Data Limitations – companies can only spend a minimum amount of time in assisting vendors with data issues.

I have found that these issues represent an opportunity for predictive analytics vendors (services, hardware, and software) that have a flexible business model. The answer to this issue involves two old sayings: No man is an island, and You eat an elephant one bite at a time.

Alliances with established companies, as well as new vendors, become essential, since collaboration is a tenet of surviving in difficult times. The ability to bring together different skills and experiences, as well as to have a flexible position to solve problems, is a …

Lately I have faced an interesting issue with large companies seeking business analytics assistance: how to provide operational predictive analytics to companies that need results in no more than 5-30 days when their budget is extremely limited and access to their data is narrow. The pressures that companies are facing in these recessionary times are:

1. Time-to-Market – companies must turn around in a quarter to show improvement to their investors;
2. Cost-Containment – predictive analytics solutions must be inexpensive to implement; and
3. Data Limitations – companies can only spend a minimum amount of time in assisting vendors with data issues.

I have found that these issues represent an opportunity for predictive analytics vendors (services, hardware, and software) that have a flexible business model. The answer to this issue involves two old sayings: No man is an island, and You eat an elephant one bite at a time.

Alliances with established companies, as well as new vendors, become essential, since collaboration is a tenet of surviving in difficult times. The ability to bring together different skills and experiences, as well as to have a flexible position to solve problems, is a keystone in measuring success in these times. Another keystone is to divide predictive analytics issues into small and measurable parts. Vendors that have the ability to prioritize client’s issues have an opportunity to be successful. Prioritization includes the possibility that initial revenues for an analytical project may be limited, but the payoff is an immediate lift to the client.

The time where companies could afford even a free six-month proof of concept in analytics is becoming a thing of the past. Companies do not have the time nor the inclination to hear, “It cannot be done.” Companies literally want and need predictive analytics today so they can face the challenges of tomorrow.

Have you found similar issues? If so, how did you deal with them?