As companies achieve parity with their competitors on products, technologies and services, analytics is emerging as the new arena of the war to gain competitive advantage.
Using analytics, companies now know what products their customers want, what prices they will pay, what will motivate them to buy more, how much each employee contributes to the bottom line and how salary levels relate to an individual’s performance. Analytics permitted Amazon to be instrumental in turning in a profit inspite of making huge investments in infrastructure and customer acquisition.
Marriott International has perfected the art of tariff determination for its rooms. It has created an analytical model which shows potential revenue opportunity based on optimal tariffs and realistic occupancy levels possible and maps actual revenues against this figure. Actual revenue figures have grown from 83% of optimum revenue figures when the program began to over 90% today. Marriot’s Revenue Management System adjusts prices in real time to improve prospects of a room being sold at the optimum room tariff. Marriott’s analytics program is now an enterprise wide revenue management system called One Yield. It covers 1700 of its 2600 properties. Marriott’s web analytics group is constantly studying the revenue impact of changes in its web site through which it does business of $4 Billion annually.
Capital One, a banking and financial services company conducts 30,000 experiments a year with different interest rates, rollover incentives, minimum balance and other variables. Through these experiments it understands which customers are likely to sign up for credit cards and how likely they are to pay up against expenses incurred and over what period, a factor critical to profitability. Its savings business improved retention rates by 87 percent and reduced new customer acquisition costs by 83 percent. Capital One started off as a credit card division of Signet Bank and its experiments with credit card customers led to a better targeting and retention of its most valuable customers. It was eventually spun off as an independent company. Capital One’s analytical prowess made it a Fortune 200 company. Its stock price grew 1000 percent over a ten year period, outpacing the S&P index by a factor of 10 and its nearest rivals by a factor of 2 to 4.
Insurance company Progressive, the first insurance company to offer insurance online analyses data on a narrow group of customers-say motorcycle riders aged 30-40. It correlates the incidence of accidents and claims with a number of factors such as age, education, income, credit scores, occupation etc. It establishes likelihood of claims being made based on each of these factors. It then sets prices based on the presence of such predictor variables. With this approach, Progressive can profitably serve both low and high risk groups.
UPS has emerged as a major analytics based competitor. UPS is able to predict customer defections by examining usage patterns and complaints. It can anticipate and influence the actions of customers. UPS tracks the movement of packages and anticipates bottlenecks, and is able to proactively intervene to prevent failures in delivery.
Procter and Gamble has created an enterprise wide analytics group of 100 data analysts from various functions who operate within each function but are centrally managed. P&G helps suppliers improve responsiveness and reduce costs using the Joint Value Creation program.
Wal-Mart has developed a system named Retail Link which can be used by suppliers to monitor movements by store so that stock outs are minimised. Consumer product companies are helping retailers optimise their mixes and in the process offer more shelf space to their own products.
Dell employed DDB Matrix, a unit of its worldwide advertising agency DDB Worldwide to create a database of the company’s print, radio and TV advertising campaigns and the sale in different territories before and after the advertisement campaigns.
Research firm International Data Corporation estimates that analytical projects aimed at improving production have a median ROI of 277%, those involving financial management have a ROI of 139 percent, and those involving CRM have a ROI of 55 percent.
What are the key attributes among analytics companies?
Most companies are able to generate descriptive statistics about their operations. Data on sales, profits, costs, productivity, ROI are known in great detail. Much of it is after the occurrence data.
Analytics companies use predictive modelling to find the most profitable customers. The customers who are likely to defect and those who have the most profit potential. They pool data extensively- data captured internally and data from secondary sources. This data is analysed deeply for an in depth understanding of their customers. They optimise their supply chain and establish prices dynamically to achieve optimal sales. They measure the impact of their various intervention strategies and apply the results to improve upon these interventions.
Analytics competitors understand where their data crunching efforts must be directed for maximum effect.
Analytics competitors do not perform these activities in discrete pockets. The initiative is likely to be under a single unit which delivers a comprehensive information based strategy. Since data does not originate from different departments, relying on an organisation wide approach to capturing data at transaction points, duplication and data errors are minimised.
Analytics driven companies are also getting their partners to use analytics tools so that their operations may be improved.
Competing on analytics entails acquiring the latest technologies. Companies invest in systems which capture data from every transaction point. IT applications ensure that no transaction occurs without leaving its mark.
Analytics warriors invest in the requisite hardware, software and people to keep improving their understanding of their supply chain, customer selection, customer loyalty and service, pricing, human capital, product and service quality, financial performance and R & D.
Rules for competing in analytics
- Create sophisticated systems to capture critical business operations data across all
- Ensure that your senior executives understand the importance of analytics and constantly refine their analytical skills
- Instil a culture of making data based decisions, discourage seat of pants and intuitive decision making.
- Hire the very best analytics skilled people you can get.
- Give Analytics the status of a strategically important initiative at the enterprise level.
- Develop proprietary metrics for use in each key business process. Create performance benchmarks and meet those using predictive and diagnostic features of your analytics program.
- Share data with suppliers and customers. Help them optimise their operations using this proprietary data.
- Run experiments profusely to understand cause effect relationships. Based on such experiments carry out activities which are likely to improve results.
- Make quantitative capabilities a part of your company’s DNA.
- Constantly measure improvements, keep what works and weed out whatever does not.
Analytics is emerging as the next battleground for gaining competitive advantage. Analytics warriors are able to predict business results across functions based on predictor variables and are consequently able to fine tune inputs for optimal results. The article cites experiences of leading analytics driven companies and suggests a roadmap for companies seeking to adopt analytics as a strategic business initiative.