Six Must-Have Elements of Full-Scale Digital Product Lifecycle Management

It’s increasingly challenging for R&D departments to operate a cost-effective product lifecycle when product data is manually gathered, stored and analysed across working groups and formats, and rarely consolidated into one place. To complete product research and cost-effectively test new and updated products, R&D scientists often are stuck 'data wrangling' product attributes throughout the organisation and manually completing formula calculations in Excel lookup tables, modelling different product scenarios with multiple variables which are incredibly time-consuming. Companies are on the hunt for ways to completely digitalise every stage of product development and put predictive models in place that can automatically determine the best chance of a product’s success.