While a number of cloud platforms for data and analytics have been launched since 2013 and well accepted by the market, big data is still a difficult technology from which to derive value.
There certainly are many consumer-focused companies that have adopted big data technology, but realizing positive business impact is limited since many IT organizations and data analysts are still in the experimental stage. At the same time, the litany of data sources across the retail supply chain now includes web statistics, social media, multiple Internet of Things (IoT) devices, mobile, machines and others. Companies from their board of directors to their operations teams are facing increased pressure to responsibly use this data to their advantage and increase value to stakeholders.
However, it is a formidable effort for companies to ingest, relate, analyze and then develop some meaningful insight from big data. Across consumer industries as well as manufacturing and pharmaceuticals we see very similar challenges within the multi-channel retail ecosystem:
· Improving supply chain agility with advanced analytics.
· Operationalizing a data-driven culture.
· Monetizing the opportunities found.
· Rapid delivery of new analytics to improve business.
· Future-proof technology.
These deliver now vs. perfect requirements challenge often bog down IT teams, who dig in their heels, with the infamous, ”please provide justification/good requirements and we will deliver!” All of this takes too much time and the business opportunity is lost while the original issue being investigated and solved has changed.
Can an organization continue to build it themselves or is it time to leverage something pre-built such as a focused big-data analytics solution?
We see many companies and executive teams opting to focus on the analytics and business value versus the infrastructure and platform that lies beneath it, now that they have seen value with cloud and SaaS solutions in other parts of their business operations. Also, with the availability of industry-focused cloud offerings that bring a level of computational power and machine learning that was not possible before, it is becoming simpler to zero in on the relevant data points in a short span of time. For companies faced with the “I want it now” consumer, shorter time to insight is imperative.
Platforms such as FusionOps include pre-built models and intelligence that has been gathered from thousands of data sources for business users to leverage. If built in-house it would take months, in most cases years, for a team to aggregate, assess, and build.
The approach of leveraging a pre-built solution allows an organization to stay focused on its core business competency and can lead to better strategic business decisions from product design, direct-to-consumer strategies, brand awareness, marketplace delivery, reducing margin erosion, optimizing working capital, and improving operating margins.
Intelligent, functionally focused, cloud platforms minimize the excessive time spent on activities that don’t align with a business’ core competency such as:
· Running and managing the computer hardware infrastructure and platform required to produce predictive and prescriptive outcomes.
· Managing support packs, system performance, and tuning of IT applications.
· Having to integrate and manage the data lifecycle.
With a solution that can take much of the administration and maintenance work out of the equation and serve up the relevant and actionable knowledge, IT teams, business analysts and product teams can spend less time wrangling data and put the intelligence to action for the business operations.
Data analytics is no longer a “nice-to-have” for competitive advantage but a basic requirement in order to do business in today’s fast paced and ever-evolving landscape. If companies are to accelerate and realize rapid business value, it is time to consider solutions designed to expose insights with smart data, instead of just provisioning more data.
Jason Ruhmann is the product director for Supply Chain, Consumer, & Sales Analytics at FusionOps. He has 18 years of applicable information delivery and analytics experience. He has held various leadership, business consulting and executive roles helping to monetize the value of analytics for organizations and achieve proper return on investment. When he isn’t working with customers to tap into analytics and achieve business success, he can be found doing any sort of outdoor activity including the ocean, fly fishing and mountain sports.