Winning Through Business Intelligence

Many organisations struggle to understand the contribution of their business intelligence service. Yes, reports are produced, analyses conducted, decisions are taken – but how can this be reduced to a straightforward statement of value that senior management can appreciate?

A standard measure of volume, such as the number of reports or publications produced is too simplistic and disconnected from the service’s value-add. A senior manager might be astonished to find that several thousand reports were produced but would have trouble assessing if the service added value or not.

There is a way of thinking about this.

If you consider the purpose of business intelligence is to  the business: value is delivered when the business acts on that information and secures a positive result.

If a business intelligence insight points the business the wrong way and decisions are taken that destroy value, then counting the production of that item of insight as a positive output measure is wrong.

Goddard and Eccles, in their excellent book, talk about competition through learning. Their discussion should resonate with those senior managers who seek to understand how insights add value. I’ve adapted their logic slightly to give this explanation:

• Each competitor in a given market has its own understanding of that market, it has perspectives that it uses to inform the decisions it makes about how to operate and compete

• There are many, many perspectives – related to perceived customer needs, how to deliver services, where to be located, employee pay levels, normal profit margins, etc. etc….

• The bulk of perspectives are shared in common across all competitors – businesses in many markets operate and compete in roughly the same way because they all think the same way about how their market operates

• However, each competitor will have some differences, they have a few perspectives or insights unique to them

• As perspectives drive decisions and implementation, these differences explain differences in performance (to some degree)

• Winners are those that are better aligned with the market – their products and services resonate with customer needs (in many subtle ways) and their delivery models are lean and profitable: winners have perspectives that are closer to the ‘market truths’ than losers’ perspectives

• No business is perfect – some of its perspectives will be true and some will be false – things a business believes about the market might be right or wrong and its actions may be constructive or destructive of value as a result

• The market’s shared perspectives will also contain a mix of truth and falsehoods, every competitor adding value and making mistakes in the same way, it is only those perspectives that are different that matter

• Strategy is about learning – developing unique truthful perspectives about the market and learning which previously believed perspectives are false

• Winners learn faster than their competition – they acquire sense (true perspectives) and discard nonsense (false perspectives) faster than their rivals

• Winners use their advantage to make better decisions and to implement changes in their business that better align them to the market’s true needs

This logic is illustrated below:

Clearly, business intelligence underpins this argument. It is a key tool for learning.

This logic has consequences. Think of your business intelligence service as a process – a factory, churning out perspectives for management. Think about running this as a lean process – with the true end-to-end process starting from raising an initial idea, through analysis, developing a theory, developing actionable insights, proposing and then ending at delivering a change within the business (through a business change project).

A good process will generate and deliver actioned insights fast. An improving process will accelerate delivery of increasingly higher-impact insights.

If this is the case, it should be possible to produce a business intelligence service scorecard that contains a selection of pipeline process measures such as:

• Throughput – the rate at which insights are produced and actioned by the business (the end-to-end process), the rate at which the business acquires new perspectives or disproves existing perspectives and capitalises upon them, this could be measured as insights per month, or in terms of benefits delivered (£££) per month

• Cycle time – how long does it take to complete the process (idea to implementation)

• Work in progress – how much value is locked up in the process at any one time (number of parallel initiatives, size of initiatives, benefits yet to be delivered)

• Planned capacity – how much work the process can deliver, the designed throughput measure

• Responsiveness – how quickly the business can respond to situations where learning is needed, how long does the business have to wait for new ideas or theories to be investigated

• Planned benefits – identified in business cases put forward to implement business changes that were identified by an insight

• Realised benefits – delivered by business change projects that were triggered by insights

• Yield measures – planned and realised benefits on average per idea, or return on investment given the total cost of the business intelligence service and actions taken (project delivery), or the number of ideas raised versus the number that are pruned versus the number that make it through to implementation

• Distribution – the distribution of size of items going through the process, are they uniform, are there lots of small insight projects or a few large ones?

Business intelligence is knowledge work. You can’t expect every idea to work out, or for insights to be generated to a timetable. However, averaging out over time, the work produced by a business intelligence service is close enough to a production process to make these measures useful.

In summary, what does this mean?

• The logic that the business benefits from a ‘rate of learning’ underpinned by business intelligence must be understood and agreed between senior management and the business intelligence service manager

• Business intelligence should be thought of as a process

• And the process includes delivery of business change, just generating an insight does not add value

• So project delivery of insights must be managed as part of the business intelligence process, this might be a challenge in some organisations

• Looking at the process in lean terms makes it easier to explain the value added in terms that senior management understand

• It also throws up opportunities to make business intelligence process improvements and makes it easier to make the case to invest in these improvements

Up to this point the only measure most senior managers have about the business intelligence service is its cost. With just a single measure, managing the service is about reducing this cost. Now, with process measures explaining the value added the discussion can take on another, more productive meaning.

And just a thought. If your business intelligence service primarily produces variance reports (plan versus actual) what does this mean in terms of value delivered to the business?