1 Don t Be Overwhelmed by Big Data.
2 Focus Only on the Right Data Delivered to the Right People at the Right Time. Big. Data. The CPG industry is abuzz with those two words. And for good reason, as both brick-and-mortar retailers and online retailers each attempt to create the ideal omni-channel consumer experience that will drive increased sales, they look to Big Data for actionable insights that can be measured against key KPIs. And while it s understandable that the CPG industry is excited by the prospect of more data they can use to better understand the who, what, why and when of consumer purchasing behavior, it s critical CPG organizations pause and ask themselves, Are we providing retail team and executive team members with quality data? POS, Big Data, order data or shipment summary data. It doesn t matter. Is the right (i.e., quality ) data getting to the right people at the right time? In essence, it s the same question retail and executive teams face when considering how to best merchandise their SKUs. If CPG organizations understand the importance of getting the right product to the right people at the right time, then surely they understand the importance of applying the same forethought to their demand data? The point is this. Big Data can be a Big Deal if you are in fact acquiring relevant data and delivering it to specific CPG organizations need a team of IT Analytics Champions. A team who can efficiently control the data acquisition process and assume responsibility for secure, quality data acquisition and management. people within their specific timetables. But it would appear that many CPG organizations are putting the cart before the horse. They re looking to retail teams to funnel variable streams of data into a stream of actionable insights and yet a crucial step is often overlooked data acquisition. Just as CPG suppliers look to provide consumers with what they want when they want it (be it online or in-store), so too must the IT divisions of CPG organizations be empowered to provide the right data to the right people at the right time. Call it data merchandising the act of managing, cleansing and securing highly diverse data from a variety of sources; delivering specific data to specific users; and doing so 24/7 with available personnel and resources. In essence, CPG organizations need a team of IT Analytics Champions. A team that can efficiently control the data acquisition process and assume responsibility for quality data acquisition and management. The properly positioned IT Analytics Champions don t deliver a barrage of data to everyone at hand; they carefully screen and cleanse that data and then provide pinpoint delivery of that data to exactly the people who need to see it. Then, and only then, can retail and executive teams transform Big Data insights into Big Deal KPIs LumiData Don t Be Overwhelmed by Big Data. 2
3 Build a Data Acquisition Strategy that Provides a Foundation for Making the Right Decisions Big Data presents CPG retail teams and corporate-level decision makers with a major challenge. They must figure out what to do with the influx of new data POS, market, forecast, social media, mobile and dot.com as they migrate from an order-driven data model to a multichannel, demand-driven one. With such voluminous and diverse data on hand, CPG organizations must uncover the relationships within multi-channel data in order better understand customers, differentiate their products and drive sales for themselves as well as their retailers. Insular, siloed data won t cut it. Nor will individualized data downloads to Excel sheets. In order to ensure that everyone within the organization is comparing apples to apples and thus deriving quality insights from the data, everyone must draw from the same common demand data stream. Better yet, each individual should have a unique data slice delivered to them based upon the KPIs they are responsible for. And that has been a challenge. CPG organizations have relied on a variety of platforms to acquire data with either users pulling data or having IT pull it for them. This uncoordinated data acquisition strategy taxes an IT department already burdened with scrubbing data and maintaining current systems. As a result, the user often receives data that is wrong, incomplete, outdated or simply irrelevant to the person s needs. Because of this, Big Data has been undermined by infrastructure. Allowing all parties to acquire data by variable means and not assigning responsibility for quality data management is not a strategy for Big Data success. That s where IT comes in. IT must lead the effort to define and provide the best data acquisition process one that delivers clean, non-redundant, secure, timely data to specific users based on their business roles. IT must assume control of data acquisition and identify and implement a data acquisition platform that converges data and enables users to manage and control these variant data sources in order to be effective at driving enterprise-wide decisions tied to KPIs that impact and improve business performance. By assuming control, responsibility, governance and accountability of the data acquisition process, IT can free itself from the time-consuming burden of fixing and cleansing data. IT can also put power back into the hands of the users. Because the converged and cleansed data is delivered to their own digital doorstep, users have exactly what they need, exactly when they need it rather than relying on customized IT data downloads that often happen too late rather than just in time. In order to take advantage of Big Data, and any other relevant data sources, IT must provide the technology, tools and architecture that allows users to manage, IT must lead the effort to define and provide the best data acquisition process one that delivers clean, non-redundant, secure, timely data to specific users based on their business roles. analyze and link Big Data. It s important to create a context that helps them see the inter-relationships within the data, fosters enterprise-wide communication and leads to insights that drive growth across the enterprise. And IT must do so while ensuring data integrity, nonredundancy, accountability, security, auditability and user access privileges. It s a tall order to fill. But it all starts by understanding not only the user s need for context, but the changing nature of demand data acquisition LumiData Don t Be Overwhelmed by Big Data. 3
4 From Batch Processing to 24/7 Processing Data Acquisition is Always On Define Your Current Data Acquisition Strategy In the past, CPG demand data could be processed in batches, overnight. Waiting for data was the norm. Users only accessed the data at work. They received and analyzed it in silo fashion, and data analysis tended to be reactive, rather than proactive, because of the sales order-driven nature of the enterprise. Not so today. Now, data acquisition is 24/7. Users access data from anywhere and they demand near-instant access to seamless data derived from a wide variety of resources. No one ever sits idle, nor should the data. The problem is that this increasing demand for responsiveness is at odds with IT s responsibility for acquiring, cleansing and processing bigger and bigger stores of data with fewer and fewer resources. Ultimately, IT needs to connect all the data sources with all the variable means the enterprise has of accessing the data in order to meet the ever changing business challenges of the enterprise. To meet these challenges and make the necessary connections, you need to examine how your enterprise is currently collecting data and what data people need and when they need it. The process should be a collaborative approach between IT and the business enterprise. When IT has a better understanding of how business is done you can then start on a data acquisition strategy and subsequently locate a data acquisition and applications platform that best suits your enterprise. Only then can IT truly evaluate vendors to determine if they meet the business and technical criteria for implementing an enterprise-wide data acquisition and demand management solution. IT needs to connect all the data sources with all the variable means the enterprise has of accessing the data in order to meet the ever changing business challenges of the enterprise. In the recent past, CPG organizations have focused solely on analytics, and thus established insular and siloed approaches that curtail business performance. CPG organizations have also adopted non-scalable data acquisition solutions from multiple vendors that lead to inconsistent and redundant data at best, and prohibit the enterprise from integrating new data resources, at worst. Remember, CPG users need data that is cleansed and consolidated in order to provide context that drives insights. Currently, many CPG organizations follow a horizontal data delivery path, in which warehouse data is pushed out horizontally from business process systems using ETL capabilities. With ETL platforms, the emphasis is primarily on delivering raw data simply making data available to everyone in the enterprise no matter what their position is within the enterprise. Little or no regard is paid to either providing the right data to the right user, or providing them with ready analytics that will help them make more informed business decisions quickly LumiData Don t Be Overwhelmed by Big Data. 4
5 To avoid such siloed data acquisition strategies, start by determining how your CPG organization is currently collecting demand data. What characteristics define your current system? Data is being collected, used weekly and provided directly from downstream sales teams. Some data is being collected, but not from all the retailers and not in a unified manner on any basis. Complicated data formats and file conventions make it technically difficult to collect and translate to usable POS data. Data is not being provided by retailers on a weekly basis to the sales teams. Data is not being provided by retailers at all by some retailers. Some form of data collection is being done monthly by third party vendors. One of the greatest obstacles to syncing data acquisition effectively is coordinating the decisionmaking time frames of consumers, suppliers and retailers and the data generated by those independent groups. Consumers make decisions every single day and the changes and trends in their purchasing behaviors are reflected in web.com, social media and daily POS consumption data. Retailers, in cooperation with suppliers, adjust their decisions on a weekly basis in response to the previous week s consumption data. These weekly adjustments affect their overall tactical and operational merchandising plans and business activities. Suppliers also utilize historical data and current POS data to adjust their monthly production plans in order to come up with more accurate current and new product assortments. Define Your Ideal Data Acquisition Strategy Based on Who Needs What Data When Now create a rules-driven business case for what demand data should ideally be collected, integrated and used to make informed and timely decisions that improve KPI-defined business performance. The challenge here is to understand that people throughout the CPG enterprise have varied responsibilities and they need data that is in sync with those responsibilities and their unique time frame. Within the CPG enterprise, everyone has very specific responsibilities. How they view retail data, and what specific data they need to look at, is highly dependent on where they are and what they are charged to do. The ideal data acquisition strategy must pay attention to the specific needs of each team member, and ensure the data is in sync with their decision cycle. The best means of ensuring these needs are met is to ask the retail team and c-level team members what data is needed, in what format and in what time frame. Below is a sample table of data table needs. Data Definition Source Data Owner Major Frequency of Use Time of Data Availability POS Retailer systems Fiels sales teams Daily and weekly Weekly in some cases Forecast Sales teams S&OP executives Monthly Varies with management process Corporate teams Orders Retailer systems Sales executives Monthly Daily and weekly Corporate order entry providers Market Syndicated provicers Field category Monthly Varies with providers Corporate marketers 2015 LumiData Don t Be Overwhelmed by Big Data. 5
6 Create a Checklist of Data Acquisition Requirements Once IT has assessed the current data acquisition practices and has created a business rules-driven data acquisition strategy, a checklist of requirements can be created for a Big Data acquisition RFQ. Following is a sample data acquisition platform checklist. Meets business and technical needs of business users, upstream and downstream Provides all users with context a variety of multi-channel, integrated and inter-related data that helps them better understand the customer/demand; helps users see the relationships across data sets Doesn t silo data and limit usage among team members Uses past data to improve the present and plan for the future Is agile and incremental providing solutions that scale across, up and down the organization Meets data acquisition demands now, but helps the organization prepare for future data demands Efficient solution that evolves to analyze/cleanse new data types Better control and efficiency broad-based solution for managing demand via IT s governance Demand intelligence solution does it all: cleanses data, analyzes, creates reports, maintains security Allows variable access IT can choose who has access to what data One convergent stream of data that provides faster service and ability to adapt to change Automation and one source of data brings all clean data together and minimizes data errors and redundancies All consolidated demand data is contained in one data center that provides efficient, responsive and valued insights and integrates pre-existing demand intelligence platform components Is easy to use, providing basic reporting, tracking and summary analysis via a wide variety of multi-level reporting formats Cost effective solution that alleviates financial risk due to implementing expensive, disparate and incompatible technology platforms Big Data, Big Opportunity Data delivery networks designed to deliver the right information to the right people at the right time will become the critical funnel through which both suppliers and retailers differentiate their goods, better understand their customers and ultimately drive business performance. The greatest opportunities await when IT assumes the lead role in developing this data acquisition strategy. For a more in-depth look at the varied roles within the CPG organization who needs what data and when, download our white paper, In the Demand Intelligence Universe, Perspective Matters LumiData Don t Be Overwhelmed by Big Data. 6
7 CMYK: CMYK: About LumiData LumiData is a demand intelligence specialist providing retail demand information that assists Fortune 1000 consumer goods companies to evolve their business strategies. LumiData s combination of software dashboard applications and client services creates easy-to-visualize demand planning solutions utilized to drive sales and marketing strategies that increase revenue, improve margins, enhance retailer partnerships and strengthen market positions. About THE AUTHOR Ransom Stafford, MBA Ransom Stafford has served as the president and CEO of LumiData for five years. He has more than 25 years of corporate experience in information technology, business consulting and infrastructure change management, and has held a variety of managerial positions with IBM, Control Data and The St. Paul Companies. He is an expert at business architecture re-engineering aligning strategic intent, technology, business processes and people to achieve maximum organizational productivity. During his career, he has been instrumental in helping organizations optimize their success by providing employees with the right resources they need to maximize their contribution. Minneapolis 333 S 7th Street, Suite 1100 Minneapolis, MN Bentonville 1001 SE 28th St., Suite 13 Bentonville, AR toll free LumiData.com Right data. Right people. Right time 2015 LumiData Don t Be Overwhelmed by Big Data.