Question

What are the long-term implications for business when too much intelligence is included in a DSS? Provide examples to support your arguments.

Answer 1

Hi,

Below is the explanation of the above question.

At first I have thrown some light on what DSS is ,then what is the framework of DSS and where does the intelligence is placed.

Later the implications of intelligence is explained with example:-

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DSS:-

It is a computer based information system that supports any organization’s decision making activities.

The results of decision making activities are:-

Ranks.

Sorted items.

Choosing the other options.

The Framework of Decision support system is:-

1.                                             INTELLIGENCE PHASE
2. DESIGN PHASE
3. SELECT PHASE
4. IMPLEMENTATION PHASE

                           

The intelligence is the phase where a condition for which decision making has to be done is searched.

In designing phase all possible available solutions are listed.

SELECT phase includes selecting a solution from designing phase

Finally implementation phase which implements the solution for the condition.

So by looking at the INTELIGENCE PHASE it is clear that this phase is responsible for all the next work to be done.

INTELLIGENCE PHASE:-

The goal of business intelligence systems is to reduce the gap between the amount and quality of data that organizations collect and the amount and quality of information available to users on strategic level of business decisions.

The information gap comes are available in different forms:-

Data sources are inconsistent

Organizations’ ignorance of the data they have

Data within operational databases is not properly arranged to support management decisions,

Analysts take too much time to gather the required information instead of analysing it.

Now the intelligence is applied to fill this gap with the help of provided tools.

But if this intelligence phase is applied to levels which are irrelevant, then following are implications to the business:-

• Wastage of tools and resources on analysing the unnecessary data
• Wastage of man power on analysing the levels.
• The unnecessary implementation of solutions which provides no benefits to the user.
• The implications affect the costing and reputation of the organization as well.

EXAMPLE:-

Lets say a ABC organization was given data of customers of ABC supermarket.

The data was a whole dump.

It was now ABC’s job to find out the relevant data from it.

In the intelligence phase ,the analysis was carried out with a team of 4 members for 7 days with tool XYZ,MNO .

The team applied intelligence and find out below information:-

• Sorting shopping gender wise.
• Sorting shopping category wise
• Sorting shopping discount wise
• Sorting the birthdates of the customer
• Sorting names of the customer
• Sorting address of the customer

……………………………………………………………….

Now for a supermarket to come out with new schemes it is not necessary to have names sorted and address sorted and they cannot apply any scheme with the help of the intelligence applied for the last two conditions. They can find this information provided to them irrelevant and can reject few solutions.

But the organization has invested time and money in it. Thus the organization has to bear loss which is a implication .

Conclusion

Intelligence needs to be applied in business .But if there is no limit put to its application then it can cause unnecessary implication to costing and reputation of organization.

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