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The role of data and analytics is rapidly changing from simply acting as a business-supporting function to being a catalyst for digital transformation.

Whether you like it or not, we are all generating and consuming data at an unprecedented pace. For example, Google now aggregates anonymized datasets from willing mobile users based on their device’s location history. It has built community mobility reports based on geolocation data and shared it for public use. In the current Covid-19 climate, this data has proved to be immensely useful for any organization that is looking to reopen and reimagine its operations.

As a leader of a corporation, government agency, university or nonprofit, it is likely that you use data every day to make choices that affect your business. If you were not already using data to drive decisions, the Covid-19 pandemic must have been a wake-up call for your organization. The ensuing economic disruption has forced businesses to adopt or accelerate their digital transformation journey as they adapt to changing market demands, reinventing offerings, optimizing resources and, in some cases, even fighting for survival. Data and analytics have become strategic and central to digital transformation, but Covid-19 has complicated this journey, making it more challenging to collaborate.

Based on our firm’s 16-year history of supporting customers across all industries and recent conversations with customers and our global centers of excellence, I’ve highlighted five success factors that CEOs should consider critical in their quest to derive maximum value from available data assets:

1. Put data and analytics at the heart of business strategy.

To create a sustainable competitive advantage for your business, you should invest in analytics as a core capability within your organization. This means a top-down commitment from executive leadership, investment in people, trustworthy data and insights made accessible to business users. This also means that you focus on ensuring that executives act on what the data tells them.

Do not assume that you must build analytics systems yourself to create a competitive advantage. If IT is not core to your business, find the right partner to help you build the analytics systems, and you focus on consumption and decision-making.

2. Plan for perpetual modernization.

Given the state of evolution of technology and data, IT leadership should reimagine how it designs data and analytics systems. The architecture itself should be evolutionary — including data systems, insight development and delivery systems. Without taking advantage of cloud, modern architectures and automation, you will not be able to fulfill the expectations of different users and their analytic intentions in the organization. Keep in mind that moving to the cloud should not take years of planning and execution. If needed, you can always keep your current systems working on-premise while you build the new systems in the cloud.

One of our customers moved a 2PB complex analytics system from an on-premise data center to the AWS cloud within nine months. You should adopt modular and technology-agnostic architectures with room to evolve and avoid lock-in to specific tools.

3. Revisit the business/IT engagement model.

To ensure that the value of analytics reaches the strategy and operational units, organizations should focus on how the business and IT work together. Various models are available — centralized, decentralized, supportive, consultative — so you can pick the one that works best for your organization. Not being consistent with how your business is organized is likely to create longer-term challenges. The good thing is, you can start with one model and evolve into the next based on your organizational maturity.

When one of our customers implemented self-service analytics capability across their business units, they established clear roles; IT was made responsible for the enterprise platform, and business units were made responsible for building and maintaining the applications.

4. Make insights accessible to users.

Data-informed decision-making is no longer an executive privilege. Data should be accessible to all staff so they can use or create their own insights for their jobs. IT teams do not need to create every single report and insight. They should also move away from trying to standardize the consumption tools. They should consider making insights available in the tools that the users are already comfortable with.

Insights should be understandable and actionable. Consider the use of techniques such as data storytelling to enable users to comprehend information easily and move toward actions. One of our customers uses automated commentary on top of visuals to convey specific actions to front-line staff.

5. Reimagine return on investment.

We all know that the Covid-19 pandemic has caused a significant shift in consumer demand and that most organizations have had to reevaluate what is important today and what will be relevant tomorrow. Traditional portfolio rationalization models use metrics that show a connection to the revenue or profit for justification and prioritization. However, return on investment encompasses more than just the financial impact; one must consider other factors, such as the potential of results from empowered employees, better customer experiences and newer capabilities.

Leaders must also find ways to explain the intangibles that come with informed decisions. Not everything can be black and white. For example, how do you quantify the impact of saving lives due to better insights? If Google’s community mobility report helps you keep your employees safe, get health care to those in need or bring a sense of normalcy into our lives, what is the investment that we are willing to make to use it?

Navigating organizations safely and effectively in the coming months will be a big challenge for all leaders. However, in times of uncertainty, making informed actions based on data is better than making decisions simply based on instincts. You do not have to drive into an unknown city without maps; you can invest in a navigation aid that you can afford and that makes sense for your business — it could be a paper-based map, a GPS or maybe even a Tesla. You have to make a choice.

Data collection for retail shops has grown from the manual inventory of receipts to sophisticated POS systems nowadays. However, retailers everywhere are facing new business disruptions on the account of the global COVID-19 pandemic. They are racing to adopt new strategies to be successful moving forward. What store locations should open first? What are the shopping patterns and can we improve them for social distancing? Where is my supply coming from and what should be restocked? As such, real-time data and analytics will have a key role to play when operations resume.

Decisions made in a silo will unintentionally affect other aspects of the business. Making sure you not only have the data and insights but really understanding what is happening during the full lifecycle of your business is imperative. Knowing your customers so you can provide recommendations, partnering with suppliers to improve product availability, assisting ground staff to optimize store utilization and services, benchmarking competition, and pricing to stay ahead will all need timely data and powerful insights delivered in near-real-time.

Making Data-driven Recommendations

  1. First, establish robust ground communicationCommunication will be vital, with both your ground staff and customers. Create a centralized ‘response team’ to maintain real-time contact with stores to understand and solve challenges being faced on the ground. Extend relevant information to customers, to help them make more informed choices. In addition, share updates on specific efforts taken to keep customers and workers safe, for example, special store hours for seniors, items tried or returned to be held for 24 hours and more.
  2. Leverage digital transformation in retail – Focus on technologies that can help in these times, such as:
    • Store navigation, live digital interactions, geo-fencing, and wayfinding solutions – ensure customers can find the products they want as quickly as possible.
    • Scan & Go using a mobile app – allows customers to reduce human contact and avoid standing in line.
    • Click and collect – order products online (mostly via a mobile app), and collect them by the entrance of the stores, from special “parcel locker” nearby, or other supporting locations.

    A good example here is from one of our key customers. they recently released a series of live stream sessions and short videos to introduce its new range of customizable handbags. These broadcasts were bolstered by other digital experiences, including a mobile lifestyle quiz leading to personalized handbag recommendations from the brand’s namesake designer.

  3. Push the pedal on omni-channel strategyAn omni-channel strategy is a must to ensure movement in the stock levels. Managing inventory centrally and servicing ecommerce orders through in-store inventory will be essential. Incentivize in-store customers to adopt technology to experience and buy products online or remote shop at the store. Shift workforce to support order picking for ship from store, click & collect, home, and curbside deliveries.For example, one of our customers, PetSmart’s launched a hugely successful curbside pick-up program where customers can order online, drive-up, check-in with mobile, and pick up the merchandise safely. PetSmart revamped its mobile platform and re-assigned its store associates to support curbside deliveries and was able to deliver essential products and services, even in high-risk areas.
  4. Enable access to analytics that helpsDeploy artificial intelligence (AI) or machine learning (ML) based analytics using hot data sets to aggregate and provide real-time intelligence on changing consumer behavior and happenings in the stores around social distancing, traffic management, and occupancy rules. Provide real-time intelligence on product demand, product availability, competitor, and price benchmarking quickly to make swift decisions. Implement ‘triggered alerts’ as a way to notify customers in real-time about the products they most care about. Automate price drop, low inventory, and back in stock messages to those who interacted with specific items. This can become a major differentiator and greatly enhance customer experience.

Recognize Their Opportunity to Make Data-Driven Decisions

This time can be intimidating, but using data brings clarity and instills confidence to make appropriate decisions. This is the perfect time for retail companies to use data to do what is best for the business and workforce. The role of data and analytics is rapidly changing from simply acting as a business-supporting function to a catalyst for digital transformation.

Hear Infocepts CEO Shashank Garg’s point of view as he engages in a dialogue with Evan Levy, a recognized thought leader in data and analytics. They discuss how businesses should invest in their D&A programs today to achieve a sustainable advantage for their business and mission. Watch now.

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Infocepts is a Data & Analytics Services firm – recognized by Gartner amongst the Top 50 in the world – who enables its customers to optimize & accelerate the value of all its data assets. Unique amongst its peers, Infocepts operates with the scale as a global consulting firm, yet the expertise of a niche partner.

Founded in 2004, Infocepts is headquartered in Tysons Corner, VA, with offices throughout North America, Europe, and Asia. Every day more than 150,000 people use solutions powered by Infocepts to make better decisions.

It is a well-known fact, thanks to the widely popular Latency Curve by Dr. Hackathorn, that the longer the time-difference between a business event and action (preventive or corrective), the lesser chance of potential impact of the action. To put it simply, data latency destroys the value of business insights. As a result, new architecture paradigms, technologies and tools promising to reduce data latency keep arising.

Lately, data streaming has emerged as a preferred choice to address latency challenges. Numerous tools, both open source and commercial, are available and accomplish the same. However they suffer from following shortcomings:

  • Restrictive end-points and data volume-based pricing models – Separate databases and schemas qualify as end-points rapidly adding to investments even for modest setups.
  • Additional workload on source systems – Running queries (at short time intervals) that poll source systems for changes is common practice.
  • Generic JDBC based target systems integration – Optimized tools for loading target systems such as Snowpipe for Snowflake are not leveraged.
  • Rigid design limiting out-of-the-box suitability – Specifics such as PII protection and in-flight analytics are excluded for user implementation. This requires custom user implementation leading to longer turnaround times.
  • High total cost of ownership (TCO) – End-point based licensing coupled with restrictions on data volumes leads to significant upfront capital expense. In addition, ongoing enterprise support by end-points contributes to high operational expenses. For example, a medium scale set-up with 10 endpoints could cost up to $1.6M USD in CAPEX and about $450K USD in OPEX.

The above challenges can prohibit most businesses from adopting commercial data streaming solutions. To address these concerns, Infocepts created its own proprietary data streaming solution – Infocepts Real Time Data Streamer (RTDS).

What is Real Time Data Streamer?

RTDS helps enterprise set-up high-performance real-time data pipeline with ease. It provides flexibility of a custom solution and the stability of a packaged solution at the same time. In addition, RTDS provides cost savings up to 4X compared to similar commercial tools, making it an affordable option for every size organization.

Case Study: US Fashion Retailer

A leading fashion retailer focused on selling clothes, shoes, watches, handbags, and other accessories leveraged Infocepts’ RTDS to set-up high-performance real-time data pipeline with ease. They were challenged with integrating all of their distribution center (DC) systems data, like their Warehouse Management (WMI) and Labor Management (LM) into a data warehouse for a high priority transformation project. Through this project the customer aimed to:

  • Optimize omni-channel operations by seamlessly integrating their website, POS and warehouse data
  • Implement digital walls enabling real-time insights into distribution center operations, promoting transparency and efficiency
  • Optimize Free Trade Zone (FTZ) reporting to prevent non-compliance costs
  • Integrate data from additional systems such as Labor Management (LM) to optimize distribution center operational planning

However, due to challenges like capacity restrictions plaguing source systems (IBM DB2 iSeries and DB2 LUW), data sensitivity (PII data) and velocity (sub-second latency) open source solutions could not help and leading packaged solutions proved to be very expensive thus not fitting the bill (literally).

At this point they turned to Infocepts. We helped develop and implement RTDS as a solution to help the customer see:

  • Estimated efficiency gains in distribution center operations of over 1.2 M USD over the course of 3 years
  • Significant savings in taxes and duties due to timely Free Trade Zone (FTZ) reporting
  • Intangible benefits such as improved transparency of digital walls and better productivity through self-service analytics
  • To top it all, lower TCO of RTDS lead to jaw-dropping cost savings of 1.4 M USD over 3 years

Summed up, Real Time Data Streamer did not just enable real-time it enabled real-value!

If you have identified data latency as issue to be fixed, trust Infocepts RTDS to take care of the rest. Schedule your demo with an Infocepts expert today and start saving money tomorrow!

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