- Data-as-a-Service: Data Provisioning, Management, Lineage, Quality
- Reporting-as-a-Service: Dashboards, KPIs, Drilldowns/Aggregates…. Descriptive
- Analytics-as-a-Service: Predictive Modeling and BI… Prescriptive analytics
- Information-as-a-Service: Threshold based Alerts, Exceptions, Mobile Prompts
- Insights-as-a-Service: ML/AI based…automated learning – ambient intelligence, Next best Offer/Action
Which strategy are you implementing?
Data is valuable. Data is plentiful. Data is complex. Data is in flux. Data is fast moving. Capturing and managing data is challenging.
So, if you are a senior leader in a Fortune 2000 company. How do you structure your group to deliver effective BI, Analytics or Big Data projects? Do you have the right structure, toolset, dataset, skillset and mindset for analytics and Big Data?
Organizing for effective BI, Analytics and Big Data is becoming a hot topic in corporations. In 2012, business users are exerting significant influence over BI, Analytics and Big Data decisions, often choosing analytics and visualization platforms and products in addition to/as alternatives to traditional BI platform (reporting and visualization tools).
Data-driven DNA is about having the right toolset, mindset, skillset and dataset to evolve a major brand and seize today’s omni-channel opportunities. Whether it’s retooling and retraining for the multiscreen attention economy, or introducing digital innovations that transform both retail and healthcare, P&G is bringing data into every part of its core strategies to fight for the customer.
Striving for market leadership in consumer products is a non-stop managerial quest. In the struggle for survival, the fittest win out at the expense of their rivals because they succeed in adapting themselves best to their environment.
CMOs and CIOs everywhere agree that analytics is essential to sales & marketing and that its primary purpose is to gain access to customer insight and intelligence along the market funnel – awareness, consideration, preference, purchase and loyalty.
In this posting we illustrate a best-in-class “run-the-business” with Data/Analytics Case Study at P&G. The case study demonstrates four key characteristics of data market leaders:
- A shared belief that data is a core asset that can be used to enhance operations, customer service, marketing and strategy
- More effective leverage of more data – corporate, product, channel, and customer – for faster results
Technology is only a tool, it is not the answer..!
- Support for analytics by senior managers who embrace new ideas and are willing to shift power and resources to those who make data-driven decisions
This case study of a novel construct called Business Cockpit (also called LaunchTower in the Biotech and Pharmaceutical Industry) illustrates the way Business Analytics is becoming more central in retail and CPG decision making.
Here is a quick summary of P&G Analytics program:
- Primary focus on improving management decisions at scale – did the analysis to identify time gap between information and application to decision making
- “Information and Decision Solutions” (IT) embeds over 300 analysts in leadership teams
- Over 50 “Business Suites” for executive information viewing and decision-making
- “Decision cockpits” on 50,000 desktops
- 35% of marketing budget on digital
- Real-time social media sentiment analysis for “Consumer Pulse”
- Focused on how to best apply and visualize information instead of discussion/debate about validity of data
“Running a company is an endless quest to find out things you don’t know“
– Jeff Immelt, CEO GE
What will 2012 bring? Recently, I attended the CIO Executive Leadership Summit in Greenwich, Connecticut. I was particularly intrigued by the presentation by the new CIO of IBM, Jeanette Horan where she presented the projects she was tackling and how IBM is thinking about business analytics.
IBM is making a bet that “true leaders” will develop the capabilities required for making good and timely decisions in unpredictable and stressful environments.
IBM is adapting to this new data analytics reality by a rapid-fire acquisition strategy: Cognos, Netezza, SPSS, ILog, CoreMetrics, Algorithmics, OpenPages, Clarity Systems, Emptoris, DemandTec (for retail). IBM also has other information management assets like Watson, DB2 etc. They are building a formidable capability around the value chain: “Raw Data -> Aggregate Data -> Intelligence ->Insight -> Decisions” . They see this as a $20Bln opportunity. Read more
The “Raw Data -> Aggregated Data -> Intelligence -> Insights -> Decisions” is a differentiating causal chain in business today. To service this “data->decision” chain a very large industry is emerging.
The Business Intelligence, Performance Management and Data Analytics is a large confusing software category with multiple sub-categories — mega-vendors (full stack, niche vendors, data discovery, visualization, data appliances, Open Source, Cloud – SaaS, Data Integration, Data Quality, Mobile BI, Services and Custom Analytics).
But the interest in BI and analytics is surging. Arnab Gupta, CEO of Opera states why analytics are taking center stage, “We live in a world where computers, not people, are in the driver’s seat. In banking, virtually 100% of the credit decisions are made by machines. In marketing, advanced algorithms determine messages, sales channels, and products for each consumer. Online, more and more volume is spurred by sophisticated recommender engines. At Amazon.com, 40% of business comes from its “other people like you bought…” program.” (Businessweek, September 29, 2009).
Here is a list of vendors who participate in this marketspace:
However, it took until 1980s when decision support systems (DSS) became popular and mid 1990s for BI started to emerge as an umbrella term to cover software-enabled innovations in performance management, planning, reporting, querying, analytics, online analytical processing, integration with operational systems, predictive analytics and related areas.
Gartner 2014 magic quadrant shows the key players in the BI market. The different players are differentiated based on five abilities— ability to handle large volumes of data, ability to deal with data velocity, variety (structured and unstructured), visualization capabilities and domain/vertical specific accelerators.
Analytics is becoming three different markets. First of all, there is the BI market which is actually going through quite a bit of change itself. This is a more consolidated market than we have seen in the past and there is a tremendous amount of work being done by Oracle, SAP, IBM and others to kind of retool it for the next generation of BI. So it is a growing market, lots of upgrade, replatform, modernization demand, lots of clients who are finally realizing that the tools (visualization etc.) are ready to give them some of the capability that they have historically cared about.
The second part of the market is what is called Advanced Analytics. Here you need PhD level data scientists who have backgrounds in machine learning, industry specific domain modeling, and different types of data science who can apply that in a very specific way to specific industry problems. This is a rapidly growing part of IT Services. Also, there are just not enough data scientists to go around.
The third part of the market is Analytics as a Service. This is about leveraging software-as-a-service platforms as opposed to on-premise. This is about a business model that is more like Business Process Outsourcing (BPO). Clients buy business outcomes; they don’t buy transactions and FTEs.
The analytics market has thousands of boutique consultants who are specialists in particular industries or specific technologies. It includes all the major technology providers, who are all trying to advance their business and capabilities that they are bringing to the market. And then there are vendors who are just bringing sheer capacity of data science skills to the market and they are coming in from a completely different angle of basically just renting the expertise of their data scientists into the market.
The market is incredibly fragmented. We are in the early stages of growth in the market. Every single one of our clients is building this capability internally and they are looking for more services from vendors, because the opportunity to apply analytics is in every single one function whether it is a customer analytics, industrial Internet, e-commerce platform, is growing. Analytics is embedded into literally every single business interaction.
BI, Analytics [and Big Data] Market Sizing
More recently to support a new generation of cost cutting and growth initiatives, corporations are investing heavily to gain near real-time actionable insights (historical and predictive), and from a mix of disparate spreadsheets and myriad of systems (legacy, internal silos, customer facing, suppliers, partners, etc.).