Data Value in Decison Process: Survey on Decision Support System in Small and Medium Enterprises

Data Value in Decison Process:

Survey on Decision Support System

in Small and Medium Enterprises

Maurizio Pighin(*) and Anna Marzona (**)

(*) Department of Mathematics and Computer Science University of Udine (Italy)

(**) LiberaMente srl – Udine (Italy)

miproBIS - Business Intelligence Systems - 2012 Opatjia , Slovenia

Agenda

• The economical context on analysis

• Survey targets and methodology • Survey Results

Economical context

• The province of Udine with its 4,905 sq km is about

62% of the territory of Friuli Venezia Giulia • It is the largest province in the region also for:

 Concentration of population, with 529,000 inhabitants,

representing 44% of regional total

 Number of employees, with 228,000 employees,

representing 44% of regional total

 Number of businesses, with 49,500 businesses, 48% of

the regional total.

• High rate of entrepreneurship: one production company every 9.4 inhabitants.

• The companies are mainly small ones (such as considering up to 49 people).

Economical context

• Production specialization,



metal-mechanical

production with 1,600

units (26% of total manufacturing)



woodworking and furniture production

with 2,020 units (33% of total manufacturing).

• Strong propensity to

export

.



European Union with 60% of export value



America (especially Northern) (11% of

exports)

Agenda

• The economical context on analysis • Survey targets and methodology

• Survey Results • Conclusions

Survey targets

• Survey on mechanical companies



represent the trends of the entire territory



heterogeneous in size, incoming, type of

products and processes

• We inquiry



how many companies use data warehouse

systems



what is their profile

Survey targets

• In general we expect that

 greater use of data warehousing systems on medium-large size companies

 small businesses are less interested in these systems

• not so important amount of data • less computerized processes • low proneness to investment

• low attention to new technologies and innovative practices

 companies with data warehouses are those

• with higher technology

Agenda

• Introduction

• The economical context on analysis • Survey targets and methodology

• Survey Results

Profiling companies - Dimension

• Group A: more than 100 employees • Group B: 51 - 100 employees

• Group C: 21 - 50 employees • 38% of companies’ income is

between 5 and 15 million euros

C ompanie s In sample

Group A 16

Group B 14

Group C 15

Profiling companies - Age

• The average age of companies is about 36 years of activity

companies of group B and C, significantly more recent (29 and 31years)

companies of group A on the market for about 45 years.

Profiling compaines – Export-Quality

• High level of export and foreign relations

• High percentage (75.5%) with quality certification

94% of group A 53% of group B 75,5% of group C

C ompany

% avg.

Export

Group A

65%

Group B

41%

Group C

25%

Total

43%

Profiling IS – Specific function

C ompany % spe cific function for I.S. Avg. numbe r of I.S. staff Group A 100% 2,4 Group B 93% 1,4 Group C 26% 2 Total 73% 2

Profiling IS – Computerized areas

• The areas mainly computerized are Administration, Sales, Purchase, Logistics and Production

• The percentage drops down in the areas of Quality and Control, while still not widely used are the CRM

subsystems.

Are a Group A Group B Group C Ave rage

Accounting 100% 100% 100% 100% Logistics 94% 93% 67% 84% Sales 94% 100% 93% 96% Purchase 100% 100% 87% 96% Production 100% 86% 67% 84% Quality assur. 87% 57% 60% 69% CRM 44% 21% 13% 27%

Profiling DW – Data analysis areas

• The areas most involved in the data analysis are Administration, Sales and Purchase

• Logistics, despite having a high percentage of computerization, is less often the subject of data analysis.

Are a Group A Group B Group C Me dia

Accounting 100% 100% 87% 95% Logistics 69% 43% 33% 49% Sales 88% 93% 100% 93% Purchase 88% 86% 80% 84% Production 88% 71% 73% 78% Quality assur. 75% 36% 47% 53% CRM 31% 21% 6% 20% Control 88% 36% 60% 62%

Profiling DW - Knowledge

• group A: 94% know the existence of DW

• the percentage drops to 50% of companies of group B and 47% of group C C ompany % Knowle dge Group A 94% Group B 50% Group C 47% Total 64%

Profiling DW - Usage

• 24% use DW systems for data analysis

• among the companies that still do not have this tool, 26% will adopt one in the future, and 11% in the short term.

• 20% in group C

 orientation of small organizations into decision support systems.

• introduction of DW was fairly new

 except some rare cases, DW systems were introduced in the last 3-5 years.

C ompany % Usage % Future usage % Future usage in short te rm Group A 50% 31% 6% Group B 21% 14% 7% Group C 0% 33% 20% Total 24% 26% 11%

Profiling DW – Correlation with export

• The companies that

use DW systems

have the

high

percentage of

export



need to keep under

control the remote

activities

• The initial assumption

is reflected by the

C ompany % Export

Using DW 66%

Profiling DW – Correlation with market

•

High-tech

companies

tend to

adopt innovative tools

• The initial assumption

is reflected by the

survey

Product marke t

% DW usage Ele ctronic and automation 66%

Tools 66%

C ompone nts and subsupply 25%

Mechanic workshop 20% Machinary production 20% Carpentry and assembly 16% Installations -T hird party work -Metal furniture

-Profiling DW – Architecture - source

• The data that flow into the data warehouse comes from

ERP sources (in 100% of cases)

other external sources (73%)

 other internal sources (63%) • DW as instrument of data reconciliation Archite cture % C ompany 1 level 80% 2 levels 10% 3 levels 10%

Profiling DW - Supplier

• 80% - DW built by the supplier of the ERP system

• 20% - DW designed by other suppliers or consultants

A single known partner who already knows the company’s information system (better

comprehension of its dynamics and needs) • 88% - one-level architecture in DW built by ERP

supplier

• 50% - two-levels architecture in DW built by specific

consultants

ERP vendors offer solutions for Business

Intelligence, but usually of a lower profile compared

Profiling DW – Kind of tools

• OLAP tools

↔

“drill-down” or “roll-up” features

• Data Mining

↔

simple data analysis package,

like “classification and prediction” or

“association” analysis.

Tool Group A Group B Group C Ave rage

Reporting 100% 100% - 100% OLAP 75% 67% - 73% Data Mining 13% 33% - 18%

Profiling DW – Internal use and investment

• The general trend

 global monthly analysis

 investigate some small data on a daily basis

• In 90% of cases data is updated daily and automatically

• Budget spent by companies to acquire data warehousing systems is on average between 10,000 € and 20,000 €

• Annual budget for planned maintenance or for any developments of the system is less than 10,000 €

Role of use rs

Group A Group B Group C

Ave rage

Area managers 88% 67% - 82%

Staff 63% 67% - 64%

Profiling DW – Simplicity and Usefulness

• The

simplicity of the analysis

tools used, in a

scale of 0 to 10, has an average answer value

of about

6.5

with a variance quite low (1.25).

This shows a certain uniformity of opinion,

considering fairly simple the analysis tools

available.

• The

usefulness

of these tools found positive

answer with an average value of about

8

on a

Profiling DW - Activation

• The

activation process

of a data warehousing

system

The process is not very simple: the mean value is 5

on a scale of 0 to 10

• Exploring the reasons for this difficulty through

the use of open questions, we found

Determining what information to require

The lack of internal knowledge

• the design is almost exclusively dependent on external consultants or on the same suppliers of ERP

Profiling DW - Motivation

• Almost 60% of companies say they have

been pushed to invest in this direction



to be

more competitive

on the market



the need to have a

single tool

to conduct

analysis and obtaining clear and usable

information.

• Barriers to investment



lack of knowledge

Survey results

Agenda

• The economical context on analysis • Survey targets and methodology

• Survey Results • Conclusions

Conclusions

• Desire to use methods and tools of business intelligence:

amount of data that modern transaction systems

generate

more competitive on the market, taking quick and

appropriate strategic decisions based on fast and complete information

synthetic indicators that allow to monitor corporate

performance and to have crossed and parametric analysis on raw data provided by operational

Conclusions

• Knowledge



the

theoretical foundations

that underlie the

formation of these indicators are fairly

consolidated,



much less are foundational aspects and

engineering skills with which

to build

business intelligence systems



the instruments used are

not always

Conclusions

• In most cases data warehousing systems are made by the ERP vendors,

relationship of trust

• Software companies often push to solve the informational question through their ERP

develop reporting or interactive investigations as

customized ERP functions

use of simple OLAP navigation instruments that read directly the operational database

(one-level-architecture)

• poor knowledge of tools and methodologies of business

intelligence

• attention to operational core business, the ERP system

Conclusions

• Producers of business intelligence tools are

very

oriented to architectural and

technological aspects

, much less to

application and organization

the solutions they propose oversimplify the

collection, cleaning and physical organization of data. • Poor ETL instruments

• One-level-architecture → vertical decay of performance, complexity of user views.

Conclusions

•

Unrealistic

vision of the procedures necessary

for effective DW construction

this kind of solutions relative new

• Innovative methodologies requires

years of

gestation

proposed in formal terms

perceived by the market as a whole

tuned

successfully transposed to the end user (especially the SMEs)

Conclusions

• We can state a profile of the companies that makes use

of data warehousing systems:

 mostly medium to large companies

 in the market since long time

 correlation between the use of the DW and the percentage of

export

• the need for control over foreign operations and the usefulness of a centralized data warehouse is high;

 nature of the products may be related to the use of DW

• high-tech companies are more likely (from the cultural

Conclusions

• The

usefulness

of data warehousing tools is

still

not fully understood

in companies



difficulties

to quantify (not only in terms of

money) the ROI



lack

of a specialized figure within the

company

• The

adoption

of these tools is going to

increase

• This evolution must go hand in hand with the

transformation

of corporate culture that must