Making data and analysis a priority
Gaining enterprise insights through an analytics-first approach
Two Deloitte specialists offer insights to help leaders understand to accelerate the value of an enterprise analytics platform and enable transformation with an analytics-first approach.
Today’s wealth of data brings limitless possibilities for generating insights that can drive new results. With the real-time data and analytics capabilities, the Kinetic Enterprise™ can achieve value from information faster than ever before. But much is at risk of being left on the table when analytics is too far down the list of priorities in a digital transformation.
Analytics and trend spotting
Advances in technology has made it cheaper and easier for companies to gather data. However, the challenge for many companies is pulling insights from the data and turning it into actions that can solve a business or industry problems, particularly when it comes to identifying trends.
Arman Haroutunian, senior manager, Deloitte Consulting LLP, offers grocery shopping as a prime example. Retailers gather customers’ personal data and can gain insights into transaction frequency, location and so forth. And while the daily transaction insights are important, they miss a huge opportunity: “They're not looking at the advantages of being able to analyze this data and look at some of the trends that are taking place.” He recommends that companies undergoing a transformation should make that kind of analytical insight a priority and not an afterthought and allow those insights to drive operational efficiency.
Gil Gomez, managing director at Deloitte Consulting LLP and an Analytics Practice Lead, seconds the recommendation and offers this approach must start with business leaders who drive collaboration, who think about analytics as a process and see insights as a requirement for the transformation. “Analysts already want to provide that [insight],” he says, “it’s business leaders who need to be providing the direction – I need to understand this – and drive the need for insight across the board, efficiently and reliably.” To Gomez, this is about a change in mentality and philosophy of how companies view analytics.
A holistic view from design stage
Real-time access to data coupled with advanced embedded analytics and reporting capabilities provides unique opportunities for organizations to realize the value of their information faster. Unfortunately, many organizations still fail to effectively combine operational management and advanced analytics. The solution, Gomez suggests, is to begin at the design stage and see analytics holistically, resisting the urge to dive into granularity. Consider a finance process transformation: Rather than thinking about what kind and the number of reports needed for payables and receivables for the accounting team and building the system to deliver that, consider what information the entire finance team needs – the structure – to perform and design a common information model. “That's really how we want to address it from the beginning design it in a different way and combining it not just from pure analytics,” says Gomez.
Insights before the go-live
An analytics-first approach has a role in helping go-lives become more robust, timely, and on target. Haroutunian points out that companies typically focus on standing up traditional, process-driven transaction systems so they can continue to gathering more data without much thought for analytics.
But with the real-time data and an analytics-first approach, common information models are built with existing systems and data so companies can see the advantages of bringing more insight into the organization, and then apply that during an implementation. “It might actually change some of the processes they have,” Haroutunian says, “or some of the mindsets that say they have to look at things differently.”
Given that the ERP has evolved, so should the analytics approach thanks to real-time capabilities. It’s that kind of shift in mindset, Gomez says, Deloitte has been helping companies embrace for some time. Transformation leaders are seeing they can mature the project much faster than before, are unconstrained by long load times and persisting data, have more access to virtualization – all of it another tool in their operational toolkit.
Combine a common information model with real-time data and analytics, and companies can quickly validate if they have what they need to measure and track their business. “And if they don’t have what they need, they can make adjustments in their transactional systems, and not only transact data and collect it, but change how they consume it.”
Everything relies on information
The hand-in-glove connection between data and the Kinetic Enterprise can’t be understated. “Our concept of the Kinetic Enterprise is ever-evolving, dynamic, moving forward … leveraging technology, improving business processes, automation,” says Gomez, and much of that relies heavily on information. He builds a case for analytics as equally integral to a kinetic enterprise since it allows companies to consistently and constantly measure internal processes with fast, dynamic access to information and, most importantly, “flexibility to quickly pivot to transform the business.”
Haroutunian advises that companies considering an ERP should resist the tendency to create only a slightly better version of their current system, and think differently, make analytics a priority. “It’s thinking outside the box … looking at the cohesiveness, at the flow of how the company operates, what are the advantages they're trying to gain for a new ERP implementation. Look at things holistically so they can see the value and the advantage of a new technology program.”
Want more transformation insights from enterprise leaders? Visit deloitte.com/SAP to download future podcast episodes or listen to previous ones.
A podcast series
Put the kinetic enterprise in motion. Is your organization built to last … or built to evolve?