Who Uses This Software?

Our targets are medium to large manufacturing firms in the APAC region, preferably in the verticals of Pharma/Healthcare, Footwear, Automotive Components and Consumer Durables.


Average Ratings

1 Review

  • 5 / 5
    Overall

  • 4 / 5
    Ease of Use

  • 5 / 5
    Customer Service

Product Details

  • Starting Price
    $6,000.00/year/user
  • Pricing Details
    Our prices vary in range depending on number of SKUs and users
  • Deployment
    Cloud, SaaS, Web
  • Training
    Webinars
    Live Online
    In Person
  • Support
    Online
    Business Hours
    24/7 (Live Rep)

Vendor Details

  • Anamind
  • anamind.com/
  • Founded 2015
  • India

About PLANAMIND

An online demand planning system with unique collaborative planning and BI reporting features.


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PLANAMIND Features

  • Ad hoc Analysis
  • Ad hoc Query
  • Ad Hoc Reports
  • Benchmarking
  • Budgeting & Forecasting
  • Dashboard
  • Data Analysis
  • Data Visualization
  • Key Performance Indicators
  • OLAP
  • Performance Metrics
  • Predictive Analytics
  • Profitability Analysis
  • Strategic Planning
  • Trend / Problem Indicators

PLANAMIND Reviews


Planamind is a business intelligence reporting tool, which helps with statistical forecasting.

Sep 19, 2017
5/5
Overall

4 / 5
Ease of Use

4 / 5
Features & Functionality

5 / 5
Customer Support

4 / 5
Value for Money
Likelihood to Recommend: 9.0/10 Not
Likely
Extremely
Likely

Pros: The best feature of this tool is its flexibility and adaptability to usage as per the user requirement. This is a very user friendly and robust software. This has got many statistical models, mix and match of which can be used to simulate a live environment. This tool has a very strong data analytics capability, which helps in better forecasting accuracy.

Cons: The format in which data is to be fed in this tool is bit cumbersome. We should have blank templates in downloadable formats available on the user interface to help in ease of usability.

Overall: 1) Forecasting Accuracy

2) Ease of usage with mix and match of multiple statistical models.

3) Identification of outlier data and its correction to get better forecasting

4) BI Reporting