Retailers have long been hampered by their data infrastructures, first by structural limitations inherent in data warehouses and then the expense and lack of agility of newer big-data systems. The emerging need for data-centered decision making is an opportunity to accelerate modernization initiatives with current cloud technology.
In part one of this blog, I explained the cost of legacy systems. Now, let’s investigate the solution.
Our experience suggests that companies with outdated systems continue to incur high costs for maintenance without realizing any new business value. This means that accelerating a data-modernization journey will help retire legacy data platforms earlier and leverage more open-source software to cut expenses on licensing.
Companies need to look at ways to self-fund this modernization effort, while also continually delivering value through business-analytics efforts in parallel. The answer comes in developing a thoughtful and integrated AI and analytics data strategy and roadmap whereby high-value business use cases pay for themselves and otherwise self-fund every aspect of the roadmap. For example, if an enterprise can identify 50 to 70 business use cases that will bring value to the enterprise, it can then sequence these so that value comes early and often. We’ve even seen cases where the sequencing can create a self-funding mechanism whereby payback comes within two quarters and overall payback often exceeds five and even 10 times the cost of the program, inclusive of the entire data-modernization effort.
To win business buy-in and secure initial funding, companies should focus on identifying those luminary projects that are strategically important, offer significant rewards, and come with manageable risk. Sequencing these projects with a view for quick returns is key to building scale fast, as the more value the transformation brings, the more it becomes self-funding and the greater the business buy-in. At the same time, organizations need to thoughtfully pursue a manageable number of initiatives so they don’t attempt to boil the ocean.
Leveraging the partner eco-system
Retailers and consumer-product companies should scrutinize their IT spend and identify areas where there is a high CAPEX and OPEX incurred in maintaining and supporting the legacy hardware and software to kick-start the projects on the cost side of the equation, while also addressing the value side with additional business analytics which will increase revenue. For instance, the cost efficiency side of the equation may include accelerating the migration of data warehouse appliances, migration of commercial Hadoop distributions, and maximizing the usage of open-source software. In addition, modernization will potentially bring in savings from rationalization, consolidation, and optimization of elastic workloads.
Cloud providers and solution partners offer a wide array of contracting flexibilities and co-investment possibilities. For example, many of our clients have upcoming hardware and software upgrade, so moving to a PaaS or SaaS offerings will provide immediate CAPEX avoidance and the cloud provider may offer incentives to move your workloads to their cloud. Similarly, the revenue uplift side of the equation may include dynamic demand forecasting by mashing up with weather forecast, pandemic spread, local events, etc. Here again, cloud providers often offer upfront investment funding for co-creation in launching a pilot initiative.
Modernizing your data and analytics estate protects your current business and positions your organization to work more intuitively and intelligently, and provides the ability to leverage the abundance of talent and data and the external ecosystem that was previously inaccessible, so you can rapidly respond to business changes. New capabilities will open up revenue generating opportunities and directions to drive your business.
Retailer and consumer-product companies have several potential opportunities to drive their data and analytics transformation journey in a self-funded model. With extensive experience in guiding retailer and consumer product companies across the globe, we can set you on a path for a self-funded data and analytics modernization journey. A modern data and analytics estate will make your infrastructure invisible and deliver insights at the pace of innovation and yield superior business velocity for sustaining your business growth and competitive advantage.
Dinand Tinholt is Vice President with Capgemini’s Insights & Data Global Business Line responsible for the North American Consumer Products, Retail and Distribution Market. Dinand helps clients use data and analytics to improve their performance and innovate their products and services. Contact him to discuss your requirements at firstname.lastname@example.org.