Business intelligence technology is currently notorious for not living up to expectations. This is generally not the IT department’s fault as problems are less about implementation and more about usage by the business.
However, business managers will often ask IT to justify its choice of a complex system and throw a barrage of user complaints at the IT director about this system being difficult to use.
Users will retreat to the safety of Excel spreadsheets to store their customer data and IT will find that a substantial amount of its budget is being spent on collecting and storing data that is gathering dust.
With the economic downturn taking hold and renewed pressure on IT to support the business in its drive to understand its customers, outsourcing to experts is seriously worth considering; when profit margins are squeezed, business intelligence solutions have to deliver or the business will be on the wrong track and headed for the scrap heap.
There is always a need for data analytics, whether times are good or bad, but during the good times companies can get away with a cursory look at customer profiles, and even if understanding is based on sample data or older data, the business will still survive.
During the economic boom, consumers didn’t analyse whether they were buying the cheapest or the best, they just wanted convenience.
A scattergun approach of blanket email marketing to prospective customers ensured that companies made enough sales, for if they sent out enough emails, at least some of them would arrive in the right place at the right time.
The companies that did best were those that worked out what their customers needed, when they needed it and how to convince them to buy immediately. Yet while there was more than enough money to go around, even those with the poorest customer service could keep making a profit.
Sadly for these businesses, in tougher times companies need to know who their best customers are, as well as how to persuade them to buy and stop them defecting to a competitor’s product or service. Suddenly there is a renewed interest in using data the company has collected to its full potential.
However, with smaller budgets and CRM project failures still a fresh memory, IT departments can’t risk spending any more on data warehousing and analytics - which is when the dreaded ‘O’ word starts being used.
With many IT projects outsourcing means losing control and having to manage the performance of a third party which, despite SLAs, is often more of a headache than ensuring an internal team delivers results to the business. SLAs often mean that while the outsourced service is delivering within the terms of the contract, it is still not necessarily meeting users’ needs.
With analytics the proof of the pudding is in the eating. Does your business want to know who your biggest spenders are and what time of day they are most likely to buy or use your service?
Outsourced analytics can provide the answer in seconds, the user doesn’t have to learn how to use complex technology and the IT department doesn’t need to spend months building a data warehouse, maintaining it on a continual basis and supporting the users. Companies can pay for whatever information they use, whether it is to help marketing be more effective or to manage risk.
Increasingly, analytics is being used to manage risk, especially in the financial services sector. The subprime mortgage crisis that has been blamed for the worldwide recession illustrated that banks did not know who they were lending to and those customers’ ability to pay, particularly if they were distanced from the problem.
Many banks were shoring up other banks’ debts and didn’t ask enough questions. Those banks that have survived will now be demanding to know every little detail about their customers. Can they afford that coffee that they bought in the expensive high street chain or will it mean that they will be defaulting on their loan as they are spending £2.80 a day more than they earn?
This sudden change in direction causes a problem for IT departments that are managing analytics in-house. Suddenly the business wants to know all the negatives about its customers, a completely different data requirement when previously they were only interested in the high spenders and finding out how they could persuade them to part with more money.
By using data analytics as a service IT can easily recharge each department for its usage thereby recouping the cost.
The ROI benefits of analysing data whether for a business report, a marketing campaign or for chasing payments are obvious. Analytics are therefore ideally suited to an outsourced model where users pay for the reports they need.
Outsourcing also allows data to be controlled by a team that understands the needs of marketing. Currently this is not the case as according to one study, in more than 75% of organisations IT makes the decisions about business intelligence and data warehousing tools and solutions.
Without in-depth knowledge of the marketing department and its needs, how is IT meant to predict what marketing managers want to know about their customers?
And no sooner is the CIO able to get a clear understanding of what reports marketing wants to generate than suddenly the finance department starts demanding completely different customer profiling information, and so on for all departments that use this data.
Outsourcing affords the IT department the ability to pass on responsibility for responding to the constantly changing business intelligence needs of the company. In addition, users will get answers based on data that is current and is complete, rather than a sample from months ago.
The marketing department is used to paying for campaign development, management and analysis, so spending money on ensuring that it reaches the right customers at the optimum time is surely a logical step.
Business managers will definitely pay to find out about threats to the business’s stability and risks to its profitability. If the business is satisfied that it has the answers it needs immediately in order to make decisions, it won’t object to paying for this information. What end users do object to is paying for a business intelligence solution that they can’t, don’t or won’t use.
Indeed, why would an already overstretched IT department want to build and maintain this only to receive all the flak for its failure to meet users’ needs? By agreeing to outsource the analytical part of the business, the IT department itself can stand to gain by concentrating on more pressing matters instead of running the data warehouse.
This is why many companies are moving to an outsourced model; no capital expenditure, pay for what you use and business reports available in seconds rather than days.
Roger Llewellyn is CEO and president of data migration and business intelligence systems providerKognitio